Document global-local Omni paper position and oracle evidence

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Xin Wang
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@@ -6,9 +6,10 @@ reference; it is not the experiment scheduler.
## One-sentence objective ## One-sentence objective
Determine whether strictly causal, speaker-grounded audiovisual evidence from Determine whether strictly causal global Omni context plus local audiovisual
Qwen2.5-Omni can improve an invisible egocentric wearer's **floor-entry** and floor evidence organized around visible people can improve an invisible
**floor-yield** behavior in natural multiparty conversation. egocentric wearer's **floor-entry** and **floor-yield** behavior in natural
multiparty conversation.
The paper is not simply “replace EgoSpeak's encoders with a newer backbone.” The paper is not simply “replace EgoSpeak's encoders with a newer backbone.”
The decisive test is whether correct person-aligned vision reduces false The decisive test is whether correct person-aligned vision reduces false
@@ -19,6 +20,7 @@ recall, without hurting addressed responses or yield behavior.
| Need | Authoritative file | | Need | Authoritative file |
|---|---| |---|---|
| Current paper thesis and claim boundary | [docs/global_local_omni_paper_position_2026-09-07.md](docs/global_local_omni_paper_position_2026-09-07.md) |
| Progressive feature-fusion implementation route | [docs/progressive_feature_fusion_route_2026-09-02.md](docs/progressive_feature_fusion_route_2026-09-02.md) | | Progressive feature-fusion implementation route | [docs/progressive_feature_fusion_route_2026-09-02.md](docs/progressive_feature_fusion_route_2026-09-02.md) |
| Current hypotheses, experiment gates and stopping rules | [`docs/omni_speaker_floor_experiment_plan_2026-08-30.md`](docs/omni_speaker_floor_experiment_plan_2026-08-30.md) | | Current hypotheses, experiment gates and stopping rules | [`docs/omni_speaker_floor_experiment_plan_2026-08-30.md`](docs/omni_speaker_floor_experiment_plan_2026-08-30.md) |
| Novelty boundary and claim restrictions | [`docs/multiparty_egocentric_floor_gap_audit_2026-08-30.md`](docs/multiparty_egocentric_floor_gap_audit_2026-08-30.md) | | Novelty boundary and claim restrictions | [`docs/multiparty_egocentric_floor_gap_audit_2026-08-30.md`](docs/multiparty_egocentric_floor_gap_audit_2026-08-30.md) |
@@ -72,6 +74,19 @@ result.
[`result record`](results/easycom_track_gru_residual_4ep_2026-09-07/README.md) [`result record`](results/easycom_track_gru_residual_4ep_2026-09-07/README.md)
and [`implementation note`](docs/easycom_track_gru_residual.md). and [`implementation note`](docs/easycom_track_gru_residual.md).
### Measured oracle-information screen
- A seed-0, four-epoch Session-12 development screen supplied transcript-derived
current/past speech activity only through the explicit analysis-only oracle
contract. `aggregate-visible` improved over the matched local-audio baseline
by `+6.96649` points at 0.2 seconds and `+2.91047` points in ten-horizon mean
mAP. Visibility-only and 1-second-delayed controls stayed near audio.
- Person identity continuity is not supported: `aggregate-visible` exceeded
`per-person`, while `per-person` and `shuffled-id` were effectively tied.
The result motivates a learned causal local active-speaker/floor-evidence
branch, but does not justify a track-continuity claim. See the immutable
[`result record`](results/easycom_oracle_information_4ep_2026-09-07/README.md).
### Current blocker ### Current blocker
`evaluate_floor_state_changes.py` counts a wearer transition anywhere in a `evaluate_floor_state_changes.py` counts a wearer transition anywhere in a
@@ -91,10 +106,12 @@ unfinished. This does not relax the paper claim: event numbers remain proxy
diagnostics until competing-risk censoring is fixed. diagnostics until competing-risk censoring is fixed.
1. **P0:** fix/freeze event attribution, splits and scenario definitions. 1. **P0:** fix/freeze event attribution, splits and scenario definitions.
2. **P1:** probe aggregate activity and per-person active-speaker grounding; 2. **P1:** confirm the aggregate/per-person oracle screen over seeds 1--2,
then train a causal visible-person active-speaker/floor-evidence estimator;
compare correct, wrong-person and time-shifted visual inputs. compare correct, wrong-person and time-shifted visual inputs.
3. **P2:** re-evaluate `G`, `G+A`, `G+A+pooled-V` under the frozen event protocol. 3. **P2:** re-evaluate `G`, `G+A`, `G+A+pooled-V` under the frozen event protocol.
4. **P3:** repair the matched anonymous-track-GRU residual optimization by 4. **P3:** only if learned person-organized evidence beats aggregate/no-ID
controls, repair the matched anonymous-track-GRU residual optimization by
replacing the scalar zero gate with a zero-initialized residual output replacing the scalar zero gate with a zero-initialized residual output
layer, and verify nonzero branch gradients on Session 12. Add broken-ID, layer, and verify nonzero branch gradients on Session 12. Add broken-ID,
wrong-time and remove-person controls only if that corrected screen improves. wrong-time and remove-person controls only if that corrected screen improves.
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@@ -7,6 +7,7 @@ implemented or validated.
| Document | Role | | Document | Role |
|---|---| |---|---|
| [global_local_omni_paper_position_2026-09-07.md](global_local_omni_paper_position_2026-09-07.md) | Evidence-backed paper thesis after the causal oracle information screen |
| [progressive_feature_fusion_route_2026-09-02.md](progressive_feature_fusion_route_2026-09-02.md) | Gated route from pooled local evidence to Frame-set Attention, temporal person memory and Thinker adapters | | [progressive_feature_fusion_route_2026-09-02.md](progressive_feature_fusion_route_2026-09-02.md) | Gated route from pooled local evidence to Frame-set Attention, temporal person memory and Thinker adapters |
| [`omni_speaker_floor_experiment_plan_2026-08-30.md`](omni_speaker_floor_experiment_plan_2026-08-30.md) | Current hypotheses, experiment gates, main table and stopping rules | | [`omni_speaker_floor_experiment_plan_2026-08-30.md`](omni_speaker_floor_experiment_plan_2026-08-30.md) | Current hypotheses, experiment gates, main table and stopping rules |
| [`multiparty_egocentric_floor_gap_audit_2026-08-30.md`](multiparty_egocentric_floor_gap_audit_2026-08-30.md) | Novelty boundary, closest work and restricted claims | | [`multiparty_egocentric_floor_gap_audit_2026-08-30.md`](multiparty_egocentric_floor_gap_audit_2026-08-30.md) | Novelty boundary, closest work and restricted claims |
@@ -7,13 +7,14 @@ GRU/Transformer”作为最终主线。它只是一个 representation baseline
主问题应收敛为: 主问题应收敛为:
> 严格因果的 Omni 模型是否真正编码了多人场景中的“谁在何时说话、话语是否面向 > 严格因果的全局 Omni state 是否保留了多人场景中及时的局部视听 floor evidence;用
> wearer”这类视听 grounding;把这种逐人证据加入预测后,能否使不可见的 camera > 人物 crop 组织的局部分支补充这种信息后,能否使不可见的 camera wearer 更合理地进入
> wearer 更合理地进入或让出话轮? > 或让出话轮?进一步保留逐人 track continuity 是否真的提供 aggregate activity 之外的
> 增量,是实验问题而不是预设。
最重要的可证伪目标是: 最重要的可证伪目标是:
> 在相同 wearer 开口事件召回率下,正确对齐的逐人视觉应减少 other↔other 交谈期间 > 在相同 wearer 开口事件召回率下,正确对齐的局部视听证据应减少 other↔other 交谈期间
> 的错误开口预测;同时,不能降低对真正 addressed-to-wearer 接话事件的召回率,也 > 的错误开口预测;同时,不能降低对真正 addressed-to-wearer 接话事件的召回率,也
> 不能恶化 wearer 正在讲话时的让话预测。 > 不能恶化 wearer 正在讲话时的让话预测。
@@ -34,7 +35,7 @@ grounding,但它们尚未完整覆盖以下交集:
- 使用逐人/对象指向的视觉证据; - 使用逐人/对象指向的视觉证据;
- 用事件召回、错误开口率和响应延迟,而不只用逐帧未来活动 mAP。 - 用事件召回、错误开口率和响应延迟,而不只用逐帧未来活动 mAP。
更稳妥的论文表述是: 只有逐人控制通过后,才可使用下面的强表述:
> To our knowledge, this is the first study of strictly causal, > To our knowledge, this is the first study of strictly causal,
> speaker-grounded audiovisual forecasting of both floor-entry and floor-yield > speaker-grounded audiovisual forecasting of both floor-entry and floor-yield
@@ -45,6 +46,10 @@ grounding,但它们尚未完整覆盖以下交集:
“首个在线多人 EOT”。完整边界见 “首个在线多人 EOT”。完整边界见
[多人 egocentric floor gap audit](multiparty_egocentric_floor_gap_audit_2026-08-30.md)。 [多人 egocentric floor gap audit](multiparty_egocentric_floor_gap_audit_2026-08-30.md)。
在当前 oracle 结果下,更稳妥的主张是研究 **global Omni context 与 causal local AV
floor evidence 的互补性**。人物框/track 暂时只是组织局部观测的接口,不能写成已验证的
speaker grounding 或 identity-aware reasoning。
### 不足以成为贡献的内容 ### 不足以成为贡献的内容
- 仅把 EgoSpeak 的旧 backbone 换成 Qwen2.5-Omni; - 仅把 EgoSpeak 的旧 backbone 换成 Qwen2.5-Omni;
@@ -62,13 +67,13 @@ grounding,但它们尚未完整覆盖以下交集:
| 假设 | 问题 | 可观察证据 | | 假设 | 问题 | 可观察证据 |
|---|---|---| |---|---|---|
| H1 | 全局 Omni state 是否包含 aggregate floor 信息? | wearer/others 活动与未来活动 probe 优于简单先验和 encoder-only baseline | | H1 | 全局 Omni state 是否包含 aggregate floor 信息? | wearer/others 活动与未来活动 probe 优于简单先验和 encoder-only baseline |
| H2 | 全局 Omni state 是否可靠地区分画面中的不同说话人? | 匿名 person-slot active-speaker probe 明显优于随机/时序错位视觉 | | H2 | 真实因果 AV 能否恢复 oracle 所显示的 timely local floor evidence? | learned local branch 优于 audio、visibility、错人/错时和参数匹配控制,并恢复可报告比例的 oracle gap |
| H3 | 逐人 grounding 是否改变 wearer 的开口决策? | matched onset recall 下,other↔other 时段 false entry/min 显著下降 | | H3 | 逐人 continuity 是否提供 aggregate evidence 之外的增量? | correct track 稳定优于 aggregate、no-ID、shuffled/broken-ID 控制 |
| H4 | 这种抑制是否只是让模型更保守? | addressed-to-wearer response recall/latency 和 wearer yield 不退化 | | H4 | 这种抑制是否只是让模型更保守? | addressed-to-wearer response recall/latency 和 wearer yield 不退化 |
如果 H2 不成立,论文不能宣称原始 Omni 已经具有可靠 speaker grounding;这时逐人分支 如果 H2 不成立,论文不能宣称局部 AV 分支解决了 Omni 的 floor-evidence 缺口;应先审计
本身就是所需的适配模块。如果 H2 成立但 H3 不成立,则 representation 有说话者信息, 编码和时间对齐。如果 H2 成立但 H3 不成立,则采用简单 aggregate/person-set 分支,并
但它没有转化为 floor-action 收益,也不能强行讲成成功故事。 明确 track identity 没有增量,不能强行讲成 speaker-continuity 故事。
## 4. 实验顺序 ## 4. 实验顺序
@@ -119,6 +124,16 @@ P1 的通过条件不是一个固定绝对阈值,而是:正确对齐的人
且三次随机种子置信区间不完全被简单 pooled baseline 覆盖。否则不要进入昂贵的 Thinker 且三次随机种子置信区间不完全被简单 pooled baseline 覆盖。否则不要进入昂贵的 Thinker
adapter 实验。 adapter 实验。
2026-09-07 的 seed-0 Session-12 oracle screen 给出了更精确的门控信号:完全对齐的
`aggregate-visible` 活动相对 local-audio baseline 提升 `+6.96649` 个点的 0.2 秒 mAP 和
`+2.91047` 个点的十 horizon mean mAP,而 visibility-only 和延迟 1 秒的活动接近 audio。
这支持“及时的局部 floor evidence 有信息价值”。但是 `aggregate-visible` 高于
`per-person`,且 `per-person` 与 `shuffled-id` 基本相同,因此当前结果不支持人物 ID
连续性。下一步优先学习可部署的 causal visible-person active-speaker/floor estimator;只有
正确逐人证据稳定优于 aggregate、no-ID、broken-continuity 和错时控制,才进入 track-aware
主方法。完整数值见
[`oracle result record`](../results/easycom_oracle_information_4ep_2026-09-07/README.md)。
### P2:建立 floor-action 基线,并证明普通池化视觉的局限 ### P2:建立 floor-action 基线,并证明普通池化视觉的局限
已有结果应重新放入同一个事件协议: 已有结果应重新放入同一个事件协议:
@@ -250,9 +265,10 @@ train 内 calibration/dev,不读取官方 test 结果做超参数搜索。
## 8. 最小可投稿版本与强版本 ## 8. 最小可投稿版本与强版本
**最小可投稿版本**:新的 wearer entry/yield 事件协议、Omni speaker-grounding 诊断、 **最小可投稿版本**:新的 wearer entry/yield 事件协议、global/local information audit、
EgoSpeak/encoder-only/Thinker/local-audio/pooled-video 强基线、EasyCom+Ego4D 复现,并清楚 EgoSpeak/encoder-only/Thinker/local-audio/pooled-video 强基线、至少一个从真实 AV 恢复
展示逐帧 mAP 隐藏的行为差异。 oracle local-floor gap 的模型,以及 EasyCom+Ego4D 复现;并清楚展示逐帧 mAP 隐藏的行为
差异。
**强版本**:在上述基础上,匿名逐人 causal fusion 在 matched wearer recall 下显著降低 **强版本**:在上述基础上,匿名逐人 causal fusion 在 matched wearer recall 下显著降低
third-party false entry,保持 addressed response 与 yield,并通过 wrong-person、time-shift、 third-party false entry,保持 addressed response 与 yield,并通过 wrong-person、time-shift、
@@ -27,8 +27,11 @@ mAP。它表现稳定,但与旧 pooled 结果的 split/dev 协议并不匹配
视觉控制,因此不能写成注意力优于 pooling。另加入两个仅用 视觉控制,因此不能写成注意力优于 pooling。另加入两个仅用
当前 sidecar 的 F5/F6 **screening** 模式:`audio-person-frame-set` 和 当前 sidecar 的 F5/F6 **screening** 模式:`audio-person-frame-set` 和
`gated-person-state-adapter`。前者没有 F4 人物历史,后者位于 Thinker readout 之后;二者 `gated-person-state-adapter`。前者没有 F4 人物历史,后者位于 Thinker readout 之后;二者
都不能写成完整 F5/F6。第一版 F3 `track-gru-residual` 已实现但尚待远程运行;F2、F4、 都不能写成完整 F5/F6。第一版 F3 `track-gru-residual` 已完成远程运行,但因 zero-gate
真正的 F5/F6 和 D1 仍然只是计划。 阻塞早期梯度只能记为优化失败,不能用于判断 track continuity。随后完成的 oracle
information screen 表明及时的 aggregate visible activity 有明显价值,而逐人历史与
shuffled-ID 无差别。因此当前优先级已从“继续加深 track 模型”改为“先从真实 AV 学出及时
的局部 floor evidence”;F2、F4、真正的 F5/F6 和 D1 仍然只是计划。
## 2. 不可改变的实验条件 ## 2. 不可改变的实验条件
@@ -70,7 +73,24 @@ P0 修正前的 entry/yield 数值只能称为 timing-derived proxy,不得作
| F6 | Thinker person-memory adapter | 旁路证据能否安全接入 Omni 内部 | D1 | | F6 | Thinker person-memory adapter | 旁路证据能否安全接入 Omni 内部 | D1 |
| D1 | 在线 detector + causal tracker | 部署管线与 provided-box 上限的差距 | 完整系统 | | D1 | 在线 detector + causal tracker | 部署管线与 provided-box 上限的差距 | 完整系统 |
F1 是下一项实现。F2 及以后不并行堆叠,避免无法判断收益来自哪一层。 F1 已完成初筛,但尚未通过视觉错位/错人和事件 gate。当前先执行下面的 oracle 驱动
学习步骤;F2 及以后仍不并行堆叠,避免无法判断收益来自哪一层。
### 3.1 Oracle 信息门对路线的修正
2026-09-07 的 Session 12 seed-0、四 epoch screen 使用严格 past/current-only 的
transcript-derived activity 作为 analysis-only sidecar。`aggregate-visible` 相对相同的
G+A baseline 提升 `+6.96649` 个点的 0.2 秒 mAP 和 `+2.91047` 个点的十 horizon mean
mAP;visibility-only 和延迟 1 秒的 activity 仍接近 G+A。这说明当前模型缺少的是及时的
局部 floor activity,而不只是“画面里有人”或额外参数。
但是 `aggregate-visible` 高于 `per-person`,且 `per-person` 与 `shuffled-id` 的差异仅为
`-0.05826`(0.2 秒)和 `-0.07725`(mean mAP)个百分点。当前 dense aggregate-others
目标没有显示人物 ID 连续性的额外信息价值。因此,下一项学习模块首先应是从因果音频与
人物 crop 估计 aggregate visible-person floor evidence,并报告它恢复了多少 oracle gap。
只有正确人物/时间的逐人表示进一步稳定优于 aggregate、no-ID、broken-continuity 和错时
控制,F3/F4 的 track 叙事才恢复为主线。完整结果见
[`oracle result record`](../results/easycom_oracle_information_4ep_2026-09-07/README.md)。
## 4. F0:冻结现有 pooling 基线 ## 4. F0:冻结现有 pooling 基线
@@ -286,14 +306,13 @@ README 必须写明 split、seed、checkpoint、输入特征版本、评测协
## 12. 最近执行顺序 ## 12. 最近执行顺序
1. 第一版 matched pooled/`track-gru-residual` dense-AP screen 已完成,但因 zero-gate 1. 用 seeds 1--2 复核六个 oracle 条件;只看 Session 12,不能根据 Sessions 1--3 调整结构。
gradient blockage 判为优化失败,不是 track continuity 的有效阴性结果。 2. 从真实因果 AV 学习 aggregate visible-person activity/floor evidence,和 G+A、visibility、
2. 先用零初始化 residual 输出层修正梯度路径,只在 Session 12 做 seed-0 诊断;确认分支 past-shift、wrong-person/wrong-time、参数匹配分支比较,并报告 oracle-gap recovery。
实际改变 logits 后再跑三 seed。若修正后仍无增益,再决定是否比较 8/16/32 3. 若正确视觉没有稳定优于错时/错人控制,停止复杂 fusion,先修复局部编码或 AV 对齐。
observations;不要根据已经查看过的 Sessions 1--3 seed-0 结果调参。 4. 只有 learned person-organized evidence 优于 aggregate/no-ID 时,才用零初始化 residual
3. 若修正后的 track GRU 有稳定增益,补 broken-track、past-shift、no-ID 和 remove-person 输出层修复 track-GRU 梯度路径,并补 broken-track、past-shift 和 remove-person 控制。
控制;若仍无增益则停止该分支。 5. correct track 通过上述控制后,再实现 F4 person-conditioned audio/Omni history;否则
4. correct track 通过控制后,再实现 F4 person-conditioned audio/Omni history;否则回到 论文采用更简单的 global Omni + local aggregate floor-evidence 模型。
对齐审计,不直接堆更深 interaction。 6. 在形成论文事件结论前,仍须完成 P0 competing-risk censoring,并人工打印 response 与
5. 在形成论文事件结论前,仍须完成 P0 competing-risk censoring,并人工打印 response 与
yield 时间轴。当前事件结果只能称为 timing-derived proxy。 yield 时间轴。当前事件结果只能称为 timing-derived proxy。
+169 -90
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@@ -10,8 +10,8 @@
\newcommand{\vect}[1]{\boldsymbol{#1}} \newcommand{\vect}[1]{\boldsymbol{#1}}
\setlength{\emergencystretch}{2em} \setlength{\emergencystretch}{2em}
\title{WHEN SHOULD AN EGOCENTRIC CONVERSATIONAL AGENT SPEAK? PROBING AND \title{GLOBAL OMNI CONTEXT AND CAUSAL LOCAL AUDIOVISUAL EVIDENCE FOR
ADAPTING OMNI MODELS FOR MULTIPARTY FLOOR ACTION} EGOCENTRIC MULTIPARTY FLOOR-ACTION FORECASTING}
% TODO: Insert the final author list and affiliations after the ICASSP 2027 % TODO: Insert the final author list and affiliations after the ICASSP 2027
% review policy and author order are finalized. % review policy and author order are finalized.
@@ -24,26 +24,28 @@ ADAPTING OMNI MODELS FOR MULTIPARTY FLOOR ACTION}
\begin{abstract} \begin{abstract}
An egocentric conversational agent operating among several people must decide An egocentric conversational agent operating among several people must decide
whether to speak or keep listening before it generates a response. EgoSpeak whether to speak or keep listening before generating a response. Following
operationalizes this problem using recordings from human camera wearers: EgoSpeak, we use causal first-person audio--video as observation and the future
causal first-person audio--video forms the observation, and the wearer's future speaking behavior of the human camera wearer as an imitation target for this
speaking behavior forms the action target. The wearer is thus a data-collection agent decision. We ask whether a jointly pretrained Omni model exposes the
surrogate rather than the deployed system. EgoSpeak evaluates fine-grained floor cues required every 200~ms. Our global--local formulation
separately extracted audio--visual features with Transformer, GRU, and Mamba uses a causal global Omni readout for broad scene and conversational context,
temporal models; whether end-to-end pretrained omni models that jointly process while a causal local branch preserves recent mixed audio and a variable set of
raw audio and video expose the track-organized person observations. Anonymous tracks are an organizational
fine-grained cues required for a decision every 200~ms remains unclear. We interface whose incremental value must be established, not an assumption that
probe representative omni backbones using frozen readout, the model knows speaker identity. On EasyCom development data, a single-seed
parameter-efficient tuning, and causal side branches that preserve recent oracle analysis finds that perfectly aligned aggregate activity among visible
audio and visible-person evidence. The study tests whether a global omni state non-wearers improves 0.2-s mAP by 6.97 points and ten-horizon mean mAP by 2.91
underrepresents other-person activity and whether local evidence compensates points over global Omni plus recent audio. Person-resolved histories do not
without making the agent passive. An EasyCom event protocol measures false outperform an identity-shuffled control. This result motivates timely local
agent entries during multi-other exchanges at matched recall of wearer-derived floor evidence, while explicitly withholding a person-continuity claim. The
onset targets. Exploratory Qwen2.5-Omni-3B results motivate this hypothesis but full study compares frozen, parameter-efficient, and learned local variants
do not yet establish a cross-model limitation or determine the final adapter. and evaluates false agent entry at matched wearer-onset recall.
\todo{After the train-side study is locked, name the selected backbones and \todo{After the train-side study is locked, replace the final two sentences
adapter and insert: frozen/PEFT/local deltas, multi-other false-entry reduction with the selected learned local variant and insert: its oracle-gap recovery,
at 80\% onset recall, onset/yield non-degradation, and 95\% intervals.} multi-other false-entry reduction at 80\% onset recall, onset/yield
non-degradation, and 95\% intervals. Mention track continuity only if its
controls separate.}
\end{abstract} \end{abstract}
\begin{keywords} \begin{keywords}
@@ -79,26 +81,39 @@ wav2vec2 feature extractors with Transformer/LSTR, single-layer GRU, and Mamba
temporal models, forecasting the camera wearer and aggregate other-person temporal models, forecasting the camera wearer and aggregate other-person
activity over the next two seconds \cite{kim2025egospeak}. Thus our novelty is activity over the next two seconds \cite{kim2025egospeak}. Thus our novelty is
not the task definition or the use of first-person data. The unresolved model not the task definition or the use of first-person data. The unresolved model
question is whether an end-to-end pretrained audio--visual omni backbone, question is whether a jointly pretrained audio--visual Omni backbone,
operating on causal raw media, exposes an adequate state for this dense operating on causal raw media, exposes an adequate state for this dense
floor-action controller. To our knowledge, such omni representations have not been floor-action controller. To our knowledge, such omni representations have not been
systematically evaluated or adapted for the EgoSpeak task. systematically evaluated or adapted for the EgoSpeak task.
Our working hypothesis is specific. An omni model may retain broad scene and Our working hypothesis is a representational decomposition. A global causal
speech semantics while its global causal state makes recent prosody, activity Omni state may retain broad scene, speech, and semantic context while making
boundaries, and individual visible-speaker motion difficult for a shallow recent prosody, activity boundaries, and localized person motion difficult for
5-Hz head to recover. This would appear as inaccurate prediction of a shallow 5-Hz controller to recover. A causal local branch therefore
other-person activity and poorly timed agent entries, especially in preserves recent mixed audio and a variable-size set of person observations
multiparty exchanges. A causal local side branch may compensate by preserving before fusing them back into the global state. The local set can be pooled
recent audio and anonymous person-level evidence before fusion with the global within a frame or organized into anonymous tracks across time. Whether that
state. This is a hypothesis to test, not an assumed omni-model deficiency: continuity adds useful information beyond aggregate activity is itself a
frozen, parameter-efficiently tuned, and locally augmented variants must be falsifiable question. Frozen, parameter-efficiently tuned, and locally
compared within each backbone. augmented variants must consequently be compared within each backbone.
An initial causal oracle screen sharpens this hypothesis. On held-out EasyCom
Session~12, perfectly timed aggregate activity from currently visible
non-wearers improves a matched global-plus-audio model by 6.97 points at 0.2~s
and 2.91 points in mean mAP. Visibility alone and activity delayed by one
second remain near the audio baseline. However, person-resolved histories are
weaker than aggregate histories and indistinguishable from histories whose
identity continuity is shuffled. Thus the current evidence supports the value
of timely local floor information, not a claim that person identity or track
continuity has already been exploited.
Voice Activity Projection (VAP) provides the broader future-activity view of Voice Activity Projection (VAP) provides the broader future-activity view of
turn taking \cite{ekstedt2022vap}. EgoSpeak's role-relative output preserves turn taking \cite{ekstedt2022vap}. EgoSpeak's role-relative output preserves
compatibility with that view, but its aggregate ``others'' channel discards compatibility with that view, but its aggregate ``others'' channel discards
whether the same or different visible people produced recent activity. whether the same or different visible people produced recent activity.
Our oracle result shows that this discarded distinction is not automatically
useful under the dense target: identity continuity must beat aggregate and
shuffled controls before it enters the method claim.
Moreover, conventional per-frame average precision can hide the behavioral Moreover, conventional per-frame average precision can hide the behavioral
failure of entering during an exchange between others. We therefore retain the failure of entering during an exchange between others. We therefore retain the
dense EgoSpeak target while adding event evaluation of agent entry and yield; dense EgoSpeak target while adding event evaluation of agent entry and yield;
@@ -121,37 +136,40 @@ direct, continuous agent floor-action prediction and whether causal local
evidence helps when the visible participant set changes. evidence helps when the visible participant set changes.
We call this task \emph{egocentric floor-action projection}. The study asks We call this task \emph{egocentric floor-action projection}. The study asks
four questions: (RQ1) how accurately a frozen global omni state predicts the four questions: (RQ1) how accurately a frozen global Omni state predicts the
wearer-derived agent target and other-person activity; (RQ2) whether standard wearer-derived agent target and other-person activity; (RQ2) whether timely
parameter-efficient tuning recovers missing performance; (RQ3) whether causal causal local audio and visible-person evidence complement that state; (RQ3)
local audio and person-level visual evidence provide complementary whether aggregate person-set evidence is sufficient or anonymous track
information; and (RQ4) whether any aggregate gain reduces false agent entries continuity adds measurable value; and (RQ4) whether any dense gain reduces
without making the controller globally passive. EasyCom is suitable because false agent entries without making the controller globally passive.
Parameter-efficient tuning is a matched adaptation control rather than an
assumed remedy. EasyCom is suitable because
it provides synchronized egocentric audio--video, per-person tracks, and voice it provides synchronized egocentric audio--video, per-person tracks, and voice
activity \cite{donley2021easycom}. Target-of-speech annotations, when used, are activity \cite{donley2021easycom}. Target-of-speech annotations, when used, are
analysis strata only and are never model input or required output. analysis strata only and are never model input or required output.
The intended contributions are therefore: a controlled cross-backbone study The intended contributions are therefore: a controlled study of global Omni
of pretrained omni representations for EgoSpeak-style floor action; a representations for EgoSpeak-style floor action; an oracle information audit
lightweight local-evidence adaptation selected from that separates timely aggregate floor evidence from person continuity; a
pre-registered candidates; and a behavior-aligned event evaluation that maps global--local adaptation selected from progressively structured candidates;
wearer demonstrations to agent entry and yield decisions. Current and a behavior-aligned event evaluation that maps wearer demonstrations to
Qwen2.5-Omni observations are motivation, not a claim that all omni models agent entry and yield decisions. Current Qwen2.5-Omni observations are
intrinsically fail. Likewise, track-consistent cross-attention becomes the motivation, not a claim that all Omni models intrinsically fail. Likewise,
final method only if it beats pooled, no-ID, and capacity-matched controls. track-consistent cross-attention becomes the final method only if it beats
aggregate, shuffled/no-ID, and capacity-matched controls.
\begin{figure}[t] \begin{figure}[t]
\centering \centering
\fbox{\parbox[c][1.05in][c]{0.94\columnwidth}{\centering \fbox{\parbox[c][1.05in][c]{0.94\columnwidth}{\centering
\todo{After model selection, draw the final system figure. For now it must show \todo{After model selection, draw the final system figure. Show the shared
the shared experiment interface: raw causal AV; online face/head detection and interface: raw causal AV to a global Omni readout; a parallel recent-audio and
causal tracking; backbone-specific global readout; recent audio and a masked visible-person path; aggregate/no-ID/track-organized variants; residual fusion;
set of anonymous track states; the gated local adapter; and the common and the common $10\times3$ head. Draw the transcript-derived oracle only as a
$10\times3$ head. Mark causal cutoffs, trainable modules, parameter budgets, dashed, analysis-only upper-bound path. Mark causal cutoffs, provided versus
NULL/OFFSCREEN handling, and source-boundary resets.}}} online tracks, trainable modules, NULL/OFFSCREEN handling, and resets.}}}
\caption{Planned omni-model study for egocentric conversational floor action. \caption{Global context and causal local evidence for egocentric floor action.
The local adapter remains a candidate family until the controlled train-side Track organization is a controlled candidate, not a presupposed source of
comparison is complete.} speaker identity.}
\label{fig:method} \label{fig:method}
\end{figure} \end{figure}
@@ -207,13 +225,14 @@ expose a comparable causal state, report it as unsupported rather than inventing
a non-equivalent readout. Add future backbones only before the experiment a non-equivalent readout. Add future backbones only before the experiment
protocol is locked.} protocol is locked.}
\subsection{Candidate local-evidence adaptation} \subsection{Global context and causal local evidence}
The current hypothesis is that global omni states preserve broad semantic The global state $\vect g^{(m)}_t$ is responsible for broad scene and
context but may make recent prosody, activity boundaries, and individual conversational context, but is not assumed to retain every localized cue needed
visual motion difficult for a shallow floor head to recover. From the most for floor control. From the most
recent $L_a$ seconds, a causal local audio encoder produces $\vect a_t$. At recent $L_a$ seconds, a causal local audio encoder produces $\vect a_t$. At
time $t$, an online detector and tracker produce a variable-size anonymous set time $t$, provided boxes during method isolation---and an online detector and
tracker in the deployable condition---produce a variable-size anonymous set
$\mathcal P_t=\{(\vect v_{t,i},\vect b_{t,i},\vect r_{t,i})\}_{i=1}^{N_t}$, $\mathcal P_t=\{(\vect v_{t,i},\vect b_{t,i},\vect r_{t,i})\}_{i=1}^{N_t}$,
where $\vect v_{t,i}$ is a crop feature, $\vect b_{t,i}$ is box geometry, and where $\vect v_{t,i}$ is a crop feature, $\vect b_{t,i}$ is box geometry, and
$\vect r_{t,i}$ contains only causal reliability variables such as visibility, $\vect r_{t,i}$ contains only causal reliability variables such as visibility,
@@ -231,8 +250,8 @@ current person set by masked cross-attention,
W_q[\vect g^{(m)}_t;\vect a_t], W_q[\vect g^{(m)}_t;\vect a_t],
[\vect h_{\varnothing};\vect h_{t,1};\ldots;\vect h_{t,N_t}] [\vect h_{\varnothing};\vect h_{t,1};\ldots;\vect h_{t,N_t}]
\right), \\ \right), \\
\vect z^{(m)}_t &= \vect g^{(m)}_t+\tanh(\alpha)W_o\vect u_t, \vect z^{(m)}_t &= \vect g^{(m)}_t+W_o\vect u_t,
\qquad \alpha\vert_{\mathrm{init}}=0, \qquad W_o\vert_{\mathrm{init}}=0,
\label{eq:adapter} \label{eq:adapter}
\end{align} \end{align}
where $\vect h_{\varnothing}$ is a learned NULL/OFFSCREEN token. Padding is where $\vect h_{\varnothing}$ is a learned NULL/OFFSCREEN token. Padding is
@@ -243,14 +262,23 @@ reported. The operator is permutation equivariant
\cite{lee2019settransformer}; temporary tracker IDs provide continuity, not \cite{lee2019settransformer}; temporary tracker IDs provide continuity, not
identity semantics. identity semantics.
Equation~\eqref{eq:track} is a candidate organization of local evidence, not a
claim that recurrent identity is necessary. Simpler alternatives replace each
$\vect h_{t,i}$ with a current-frame observation or pool the set into one
aggregate vector. This distinction is important because the current oracle
screen favors aggregate activity and does not separate correct from shuffled
identity histories.
This decomposition is informed by MuVAP: its global audio representation This decomposition is informed by MuVAP: its global audio representation
queries same-frame causal ASD track representations, followed by temporal queries same-frame causal ASD track representations, followed by temporal
modeling and gated global-to-speaker fusion \cite{qi2026muvap}. We retain the modeling and gated global-to-speaker fusion \cite{qi2026muvap}. We retain the
useful separation between global floor dynamics and person-grounded evidence, useful separation between global floor dynamics and person-organized evidence,
but not its role-relative output: our fixed target is the invisible wearer's but not its role-relative output: our fixed target is the invisible wearer's
entry/yield action, not the next visible speaker. The zero-initialized gate entry/yield action, not the next visible speaker. The zero-initialized residual
also follows the conservative adapter principle used to inject visual evidence output follows the conservative adapter principle used to inject visual
into strong audio models \cite{rouditchenko2024whisperflamingo}. Local evidence evidence without perturbing the base prediction at initialization
\cite{rouditchenko2024whisperflamingo}. Unlike a zero scalar gate, it permits
the residual output layer to receive a gradient immediately. Local evidence
is derived from the same causal raw media, not close microphones, transcripts, is derived from the same causal raw media, not close microphones, transcripts,
speaker labels, global identity anchors, or future frames. speaker labels, global identity anchors, or future frames.
@@ -258,8 +286,10 @@ We evaluate candidates in increasing structural complexity: pooled recent
audio/vision; a capacity-matched temporal branch; a per-frame person set with audio/vision; a capacity-matched temporal branch; a per-frame person set with
no cross-time identity; a shared track-wise temporal encoder; and person--audio no cross-time identity; a shared track-wise temporal encoder; and person--audio
cross-attention as in Eqs.~\eqref{eq:track}--\eqref{eq:adapter}. Only a cross-attention as in Eqs.~\eqref{eq:track}--\eqref{eq:adapter}. Only a
candidate that improves the pre-registered event metric over simpler and candidate that improves the pre-registered event metric over simpler,
capacity-matched controls becomes the final method. A limited latent aggregate, identity-shuffled, and capacity-matched controls becomes the final
method. If person continuity does not separate from those controls, the final
model remains a global-plus-local aggregate floor-evidence model. A limited latent
bottleneck is tested only if large visible sets make full person attention a bottleneck is tested only if large visible sets make full person attention a
runtime bottleneck; it is not assumed to improve accuracy. runtime bottleneck; it is not assumed to improve accuracy.
@@ -339,6 +369,18 @@ clip-local anonymous participant tracks; its per-person voice coverage on the
433-clip EgoSpeak split must be audited before reporting the same multi-other 433-clip EgoSpeak split must be audited before reporting the same multi-other
event analysis. event analysis.
\textbf{Oracle information audit.}
Before selecting a learned local module, we measure what information could in
principle complement the global state. Analysis-only sidecars expose
transcript-derived speech activity no later than the current cutoff under six
conditions: local audio, visibility only, one-second-delayed activity, timely
aggregate visible activity, per-person histories, and histories with their
cross-time identity assignments shuffled. These labels never enter a
deployable model. The audit separates three hypotheses that ordinary feature
ablation conflates: the value of seeing people, the value of knowing current
visible-other activity, and the incremental value of preserving who produced
that activity.
\textbf{Backbone comparison.} \textbf{Backbone comparison.}
The initial study covers Qwen2.5-Omni-3B, Qwen2.5-Omni-7B, and The initial study covers Qwen2.5-Omni-3B, Qwen2.5-Omni-7B, and
MiniCPM-o~4.5. For each backbone $m$, we first compare its frozen causal state MiniCPM-o~4.5. For each backbone $m$, we first compare its frozen causal state
@@ -383,9 +425,11 @@ confirmatory three-seed run.}
For each backbone we compare: frozen global state $G_m$; PEFT $P_m$; $G_m$ For each backbone we compare: frozen global state $G_m$; PEFT $P_m$; $G_m$
plus recent local audio; and $G_m$ plus pooled local audio--visual evidence. plus recent local audio; and $G_m$ plus pooled local audio--visual evidence.
This compact matrix tests the representation hypothesis before investing in a This compact matrix tests the representation hypothesis before investing in a
complex fusion module. If local vision survives three seeds and the event complex fusion module. The first learned target after the oracle audit is a
gate, we then compare a parameter-matched temporal branch without person causal estimator of timely aggregate visible-person floor evidence. Only if
continuity, a separately trained per-frame/no-ID set branch, and a person-organized features survive three seeds, visual time/person corruptions,
and the event gate do we compare a parameter-matched temporal branch without
person continuity, a separately trained per-frame/no-ID set branch, and a
track-consistent masked cross-attention branch. Provided-track and online-track track-consistent masked cross-attention branch. Provided-track and online-track
inputs are reported separately. On a frozen track-aware checkpoint, a clip-consistent inputs are reported separately. On a frozen track-aware checkpoint, a clip-consistent
global renaming must leave outputs unchanged, whereas \emph{broken global renaming must leave outputs unchanged, whereas \emph{broken
@@ -419,6 +463,36 @@ after the architecture is frozen.}
\section{Results and Analysis} \section{Results and Analysis}
\label{sec:results} \label{sec:results}
\begin{table}[t]
\caption{Causal oracle-information screen on EasyCom development Session~12
(seed 0, four epochs). Oracle speech activity is analysis-only. Values are
percentages under the causal-valid protocol.}
\label{tab:oracle}
\centering
\small
\begin{tabular}{lcc}
\hline
Input condition & 0.2-s mAP & Mean mAP\\
\hline
Global + local audio & 72.58 & 58.77\\
Visibility only & 71.95 & 58.86\\
Activity delayed by 1 s & 72.02 & 58.90\\
Aggregate visible activity & \textbf{79.55} & \textbf{61.68}\\
Per-person activity histories & 78.80 & 61.11\\
Identity-shuffled histories & 78.86 & 61.19\\
\hline
\end{tabular}
\end{table}
Table~\ref{tab:oracle} establishes an information opportunity, not a deployable
result. Timely aggregate activity among visible non-wearers provides a large
gain, while visibility alone and stale activity do not. However, preserving
person-resolved history gives no advantage over destroying its cross-time
identity assignment, and both trail the aggregate representation. The learned
method must therefore first recover useful local floor evidence; person-track
continuity is retained only if subsequent no-ID and broken-track controls
separate.
\begin{table}[t] \begin{table}[t]
\caption{Exploratory Qwen2.5-Omni-3B local-branch evidence on EasyCom test \caption{Exploratory Qwen2.5-Omni-3B local-branch evidence on EasyCom test
Sessions 1--3. Values are percentages from one seed, not a cross-backbone or Sessions 1--3. Values are percentages from one seed, not a cross-backbone or
@@ -441,9 +515,9 @@ $\Delta$ visual & +0.30 & +0.02 & +0.29\\
Table~\ref{tab:preliminary} shows why aggregate mAP alone is insufficient. Table~\ref{tab:preliminary} shows why aggregate mAP alone is insufficient.
Pooled vision gives a small gain, while immediate wearer AP is nearly Pooled vision gives a small gain, while immediate wearer AP is nearly
unchanged. This is compatible with either weak but useful social grounding or unchanged. This is compatible with either useful generic local context or
generic visual regularization; only matched-recall event evaluation and regularization; it is not evidence of person grounding. Only matched-recall
track-continuity controls can distinguish them. event evaluation and visual-alignment controls can distinguish these cases.
A separate Qwen-3B dense-cache diagnostic gave 58.16 mean mAP for its frozen A separate Qwen-3B dense-cache diagnostic gave 58.16 mean mAP for its frozen
readout and 56.20 for one LoRA recipe. Because that diagnostic used a different readout and 56.20 for one LoRA recipe. Because that diagnostic used a different
feature protocol, it is not combined numerically with feature protocol, it is not combined numerically with
@@ -522,10 +596,11 @@ rejected PEFT recipes and fusion candidates to supplementary material unless
they directly explain the selected method.} they directly explain the selected method.}
\textbf{Qualitative evidence.} \textbf{Qualitative evidence.}
For a multi-other exchange, visualize per-person speech activity and track IDs, For a multi-other exchange, visualize annotation-derived per-person activity
wearer ground truth, the frozen-global and selected-local wearer-entry scores, as an analysis reference, provided track IDs when applicable, wearer ground
and the single frozen threshold on one physical time axis. If the selected truth, the frozen-global and selected-local wearer-entry scores, and the single
candidate is track-aware, also show its broken-continuity score. A useful frozen threshold on one physical time axis. If the selected candidate is
track-aware, also show its broken-continuity score. A useful
example shows the frozen baseline rising at an other-speaker boundary while example shows the frozen baseline rising at an other-speaker boundary while
the selected adapter remains below threshold; a companion positive example the selected adapter remains below threshold; a companion positive example
must show that a real wearer onset is not suppressed. must show that a real wearer onset is not suppressed.
@@ -541,17 +616,21 @@ event result and cannot establish it alone.}
\label{sec:conclusion} \label{sec:conclusion}
We study when an egocentric agent should enter or yield a multiparty floor, not We study when an egocentric agent should enter or yield a multiparty floor, not
merely whether someone will speak. The central question is model-agnostic: merely whether someone will speak. The working decomposition is global Omni
whether frozen or parameter-efficiently adapted omni representations expose context plus causal local audiovisual floor evidence. The current
the fine-grained floor cues required by a 5-Hz controller, and whether causal Qwen2.5-Omni-3B oracle audit supports the second term: timely aggregate
local evidence closes any gap. Dense activity forecasting supplies a common visible-other activity is informative beyond the global state and recent
target, while matched-recall event evaluation tests whether an apparent gain mixed audio. It does not support the stronger claim that participant identity
actually prevents intrusions during multi-other exchanges. Current Qwen-3B or track continuity adds value, because per-person histories do not beat an
results are exploratory motivation only. \todo{After the controlled study, identity-shuffled control. Dense activity forecasting supplies a comparable
state which backbone/adapter was selected, whether the representation pattern target, while matched-recall event evaluation must determine whether a learned
generalized beyond Qwen, the quantitative false-entry and onset/yield results, local estimator actually prevents intrusions during multi-other exchanges
and the main deployment limitation. Do not infer success from aggregate mAP or without suppressing valid wearer entry or yield. \todo{After the controlled
selected examples alone.} study, state which learned local variant was selected, how much of the oracle
gap it recovered, whether the pattern generalized beyond Qwen, the
quantitative false-entry and onset/yield results, and the main deployment
limitation. If no learned variant passes these tests, conclude with the
information audit rather than claiming a track-based solution.}
\bibliographystyle{IEEEbib} \bibliographystyle{IEEEbib}
\bibliography{references} \bibliography{references}
+1
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@@ -15,6 +15,7 @@ readers to the right comparison.
| [`easycom_transition_auxiliary_4ep_2026-08-27/`](easycom_transition_auxiliary_4ep_2026-08-27/README.md) | Supervised transition head and expected-reward objectives | | [`easycom_transition_auxiliary_4ep_2026-08-27/`](easycom_transition_auxiliary_4ep_2026-08-27/README.md) | Supervised transition head and expected-reward objectives |
| [`easycom_encoder_only_1s_4ep_2026-08-28/`](easycom_encoder_only_1s_4ep_2026-08-28/README.md) | Encoder-only A/V/AV versus global-Thinker local-feature baselines | | [`easycom_encoder_only_1s_4ep_2026-08-28/`](easycom_encoder_only_1s_4ep_2026-08-28/README.md) | Encoder-only A/V/AV versus global-Thinker local-feature baselines |
| [`easycom_track_gru_residual_4ep_2026-09-07/`](easycom_track_gru_residual_4ep_2026-09-07/README.md) | Matched pooled/anonymous-track-GRU screen and near-zero residual-gate diagnosis | | [`easycom_track_gru_residual_4ep_2026-09-07/`](easycom_track_gru_residual_4ep_2026-09-07/README.md) | Matched pooled/anonymous-track-GRU screen and near-zero residual-gate diagnosis |
| [`easycom_oracle_information_4ep_2026-09-07/`](easycom_oracle_information_4ep_2026-09-07/README.md) | Causal aggregate/per-person oracle information value and identity-continuity control |
## Interpretation rules ## Interpretation rules