Expand targeted introduction and move method figure to page two

manuscript/targeted/main.tex

@@ -57,7 +57,14 @@ streaming, voice activity projection, conversational agents
 An egocentric conversational agent must decide \emph{when} to speak even
 though its camera wearer is usually invisible.  It hears a mixed conversation
 and sees other participants, but must anticipate its own speech from the
-observed stream before a turn boundary is known (Fig.~\ref{fig:task}).
+observed stream before a turn boundary is known (Fig.~\ref{fig:overview}).
+This decision differs from recognizing who is speaking now: the relevant
+evidence may be a brief pause, overlap, or response by someone in view, while
+the target is the wearer's \emph{future} activity.  It also differs from
+predicting a semantic end of turn or selecting an addressee.  We therefore
+study a deliberately narrower and measurable question: at each 200-ms
+cutoff, how well can a causal observer forecast background, wearer, and
+aggregate-other activity over the next 0.2--2.0~s?
 Anticipatory turn-taking has developed rapidly: VAP, audiovisual and triadic
 extensions, backchannel prediction, online end-of-turn detection, and event
 benchmarks address increasingly realistic timing decisions
@@ -65,16 +72,10 @@ benchmarks address increasingly realistic timing decisions
 lin2025backchannel,lee2024eot,qi2026muvap,jiang2026turnbench}.
 Their input viewpoints and target decisions, however, are not interchangeable
 with forecasting the future activity of an unseen wearer.
-
-\begin{figure}[H]
-\centering
-\includegraphics[width=\columnwidth]{figures/task_overview.pdf}
-\caption{Task, not an observed event example.  At each 5-Hz decision cutoff,
-only the past audio--video prefix is input; ten future activity states are
-targets.  ENTRY-like and YIELD-like refer to wearer activity transitions,
-not semantic floor ownership.}
-\label{fig:task}
-\end{figure}
+The distinction matters when comparing systems: a correct current-speaker
+label or an utterance-final response can conceal errors in the first few
+hundred milliseconds, precisely where a wearable agent must decide whether
+to wait or begin speaking.
 
 \textbf{Egocentric audiovisual conversation.}
 EgoSpeak is the closest wearer-centered predecessor: it extracts audio and
@@ -90,6 +91,13 @@ prediction in noise \cite{oconnorrussell2025noise}.  These studies make a
 broad ``first audiovisual turn-taking'' claim untenable.  What remains
 less examined is how a single causal first-person stream should expose
 recent audio--visual evidence to forecast the invisible wearer's activity.
+EgoSpeak establishes that compact audio and video representations can be
+fused for this task, but it does not answer whether a large integrated Omni
+representation makes those cutoff-local cues readily available to a small
+forecasting head.  Conversely, work on active speakers or addressees need
+not solve wearer anticipation: the visible interlocutor and the predicted
+speaker occupy different roles.  This leaves an architectural question,
+rather than a claim that audiovisual evidence itself is new.
 
 \textbf{Streaming Omni and temporal access.}
 Omni systems integrate modalities and support streaming interaction
@@ -106,21 +114,31 @@ recent modality features outside the Thinker state, while \emph{partial-tail
 refresh} (PTR) queries the observed prefix of the incomplete current block.
 SWE denotes temporal locality, not shallow encoder layers; the argument
 concerns this pipeline, not an intrinsic deficit of every Omni model.
+These interventions target different bottlenecks.  SWE asks whether recent
+encoder evidence improves prediction when the global state is held fixed;
+PTR asks whether the same integrated backbone benefits from a fresher readout
+without admitting future media.  A gain from one does not establish a gain
+from the other.  In particular, the effect of PTR requires a matched
+completed-only comparison at the same context cap, rather than comparison
+with a longer or shorter history.
 
-Our contributions are a causal SWE/PTR interface for 5-Hz wearer activity
-anticipation; an EasyCom analysis separating global, recent-audio,
-pooled-visual, and privileged visible-activity information; and a specified
-EasyCom--Ego4D evaluation with horizon, endpoint, and hard-slice diagnostics.
-Only EasyCom screening scores are currently available: matched PTR effects,
-Ego4D transfer, and event-level behavior remain open tests.
+This framing yields three concrete contributions.  First, we formulate a
+causal, 5-Hz wearer-activity forecast and specify SWE and PTR as separable
+ways to expose local evidence to a frozen Omni model.  Second, on EasyCom we
+compare global, recent-audio, and pooled-visual features, then use privileged
+past visible activity only as an information audit, not a deployable input.
+Third, we specify cross-dataset, endpoint, and hard-slice tests.  EasyCom
+screening is the only measured evidence; matched PTR, Ego4D transfer, and
+event behavior remain open.
 
 \begin{figure}[t]
 \centering
 \includegraphics[width=\columnwidth]{figures/system_overview_onecolumn.pdf}
-\caption{Two cutoff-aligned interfaces.  SWE supplies recent encoder-side
-audio and optional pooled person-crop vision to a frozen-Omni head.  PTR
-temporarily queries the observed current-block prefix while reusing completed
-2-s payloads.  Privileged past-activity labels are not model inputs.}
+\caption{Method overview at cutoff $t_n$. Top: SWE joins frozen Omni context
+with recent audio and optional pooled person-crop evidence in the forecasting
+head. Bottom: PTR reuses completed 2-s blocks and temporarily queries only
+the observed current-block tail at each 200-ms cutoff. The tail is not
+committed to persistent history.}
 \label{fig:overview}
 \end{figure}