Restructure targeted comparison tables and method names

manuscript/targeted/main.tex

@@ -34,7 +34,7 @@ models and streaming Omni assistants address related problems, but the
 cutoff-level availability of local evidence in an integrated Omni state is
 underexplored for this wearer-centered task.  We examine two interfaces:
 short-window encoder evidence (SWE) supplies recent audio and optional
-person-crop vision directly to a frozen-Omni forecasting head; partial-tail
+causal visual evidence directly to a frozen-Omni forecasting head; partial-tail
 refresh (PTR) queries only the observed prefix of the current audiovisual
 block at each 200-ms cutoff.  On EasyCom, the exploratory global-plus-audio
 screen reaches 81.72\% mAP at 0.2~s and 65.11\% over ten horizons, versus
@@ -123,7 +123,7 @@ evidence at each causal cutoff (Fig.~\ref{fig:overview}). EasyCom screens
 suggest that global context and local audio are complementary; gains from
 pooled vision and isolated PTR effects remain unproven. This study makes
 three contributions: (1) short-window encoder evidence (SWE) supplies recent
-audio and optional person-crop vision to a frozen-Omni forecasting head;
+audio and optional visual encoder evidence to a frozen-Omni forecasting head;
 (2) partial-tail refresh (PTR) queries the observed current-block prefix
 without committing it to persistent history; and (3) detailed EasyCom
 analyses accompany a specified Ego4D transfer protocol. Matched PTR,
@@ -133,7 +133,7 @@ Ego4D scores, and event behavior remain pending.
 \centering
 \includegraphics[width=\columnwidth]{figures/system_overview_onecolumn.pdf}
 \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
+with recent audio and optional local visual 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.}
@@ -212,30 +212,39 @@ pending, so PTR is a causal access rule rather than a demonstrated gain.
 \subsection{Short-Window Feature Extraction}
 
 We define every local observation by its prediction cutoff, before applying
-any encoder-specific preprocessing. The default audio branch encodes the
+any encoder-specific preprocessing. We denote the default Qwen-audio branch
+by $\A$: it encodes the
 mixed waveform in $[t_n-1\,\mathrm{s},t_n)$ with the frozen Qwen2.5-Omni
-audio encoder and averages valid output tokens. A wav2vec~2.0 convolutional
-audio representation, as used by EgoSpeak \cite{kim2025egospeak}, is an
-encoder-choice control; it must use the same one-second input interval and
+audio encoder and averages valid output tokens. We denote by $\A_{\rm E}$
+the wav2vec~2.0 convolutional representation used by EgoSpeak
+\cite{kim2025egospeak}. This encoder-choice control must use the same
+one-second input interval and
 forecasting head before differences can be attributed to the encoder. It is
 not the source of the reported $\G+\A$ result.
 
-For vision, a single-frame variant uses the latest frame strictly before
-$t_n$; the pooled person-crop variant averages frozen Qwen vision tokens
+We denote three visual branches by \emph{Pool}, \emph{SVA}, and \emph{TSVA}.
+Pool averages frozen Qwen vision tokens
 within provided boxes, across visible people, and over valid 2-FPS frames
 in the preceding second. These pooled features summarize appearance but
 discard person identity and explicit motion. Boxes are dataset-provided,
 not predictions from an evaluated online detector. Two no-box full-frame
-alternatives retain the post-merger spatial-token grid: F2 lets the
-global--audio query attend to the latest causal frame; F3 first encodes up
+alternatives retain the post-merger spatial-token grid. Spatial visual
+attention (SVA) lets the global--audio query attend to the latest frame
+strictly before $t_n$; temporal spatial visual attention (TSVA) first encodes up
 to two observations at each matching grid location in chronological order
-with a shared GRU, then applies the same query to the resulting grid. F3
-links image coordinates, not people or tracks. Its difference from F2
+with a shared GRU, then applies the same query to the resulting grid. TSVA
+links image coordinates, not people or tracks. Its difference from SVA
 confounds additional history and temporal capacity, so it cannot alone
 establish a motion or speaker-grounding mechanism. Empty or unavailable
 local evidence is indicated by the validity masks, never filled with a
 future observation.
 
+The shorthand $\G$, $\G+\A$, and $\G+\A+$SVA identifies the three Omni
+rows in the cross-dataset table; $\G+\A+$Pool, $\G+\A+$TSVA, and
+$\G+\A_{\rm E}$ isolate visual or audio choices. Released EgoSpeak A+V
+is an external baseline, not an encoder choice within our frozen-Omni head.
+An unmeasured label specifies a comparison, not a result.
+
 As a distinct, privileged short-window feature, we also derive visible
 non-wearer speech activity from transcript annotations \emph{before} each
 cutoff. Each visible participant contributes a two-second binary history
@@ -253,7 +262,7 @@ or a performance upper bound.
 \caption{Measured EasyCom screens (\%). Panel A: deployable models; Panel B:
 three-seed privileged past-activity audit, which is not deployable. Mean is
 ten-horizon dense mAP; On/Off are raw wearer endpoint AP, not semantic events.
-F3 is a no-box, two-frame causal full-frame screen; it and the historical
+TSVA is a no-box, two-frame causal full-frame screen; it and the historical
 deployable rows are exploratory seed-0 runs with unmatched head/training
 details. F1 has three seeds. Dashes are unavailable, not zero.}
 \label{tab:main}
@@ -272,7 +281,7 @@ Omni global $\G$ & 73.446 & 77.867 & 60.849 & -- & -- \\\\
 Omni $\G+\A$ & 81.723 & 85.066 & 65.109 & 25.960 & 45.251 \\\\
 Omni $\G+\A+$pooled-$\V$ & 82.027 & 85.086
 & 65.400 & 26.019 & 45.371 \\\\
-No-box full-frame F3 & 82.380 & -- & 65.540 & -- & -- \\\\
+No-box full-frame TSVA & 82.380 & -- & 65.540 & -- & -- \\\\
 Current-frame person set F1 & $81.777{\pm}0.156$ & --
 & $64.951{\pm}0.095$ & -- & -- \\\\
 Matched-width $\G$ (L2) & -- & -- & -- & -- & -- \\\\
@@ -425,12 +434,13 @@ threshold-free quantities average ten horizons.  They are not one-event-one-
 vote detection, semantic ENTRY/YIELD, or evidence of addressee understanding.
 
 \textbf{Comparisons.}
-We evaluate released EgoSpeak MiniROADA A+V; recent audio $\A$; global Omni
-$\G$; $\G+\A$; and $\G+\A+$pooled-$\V$.  A three-seed current-frame
-frame-set attention screen tests whether a richer person aggregation is
-already sufficient.  Because that screen used Session~12 model selection
-whereas the historical pooled row did not, their difference is diagnostic,
-not a matched causal attribution.
+The cross-dataset main matrix contains released EgoSpeak A+V and the three
+Omni variants defined in Sec.~\ref{sec:method}. Missing SVA and Ego4D
+cells remain blank until measured. EasyCom-only encoder choices serve as
+diagnostic ablations rather than extra cross-dataset main rows. A three-seed
+current-frame person-set attention
+screen used Session~12 model selection whereas the historical pooled row did
+not; their difference is not a matched causal attribution.
 
 \textbf{Pre-specified analyses.}
 We freeze six control families: (L) capacity and recency, (T) tail
@@ -444,10 +454,11 @@ one run.  The source retains unmeasured hypotheses and falsifiers.
 
 \subsection{EasyCom: Local Encoder Evidence}
 
-Table~\ref{tab:main} shows that recent encoder-side audio $\A$ is strong at
-0.2~s while integrated $\G$ is slightly stronger on the ten-horizon mean.
-Their seed-0 fusion gains 4.60 mean-mAP points over $\A$ and 4.26 over
-$\G$.  Relative to released EgoSpeak, $\G+\A$ gains 7.52 points at
+Table~\ref{tab:main} anchors the measured EasyCom comparison. In a separate
+audio-only screen, recent encoder-side $\A$ reaches 79.69\% at 0.2~s and
+60.51\% mean mAP; integrated $\G$ is slightly stronger on the ten-horizon
+mean. Their seed-0 fusion gains 4.60 mean-mAP points over $\A$ and 4.26
+over $\G$. Relative to released EgoSpeak, $\G+\A$ gains 7.52 points at
 0.2~s and 3.92 mean-mAP points.  Raw wearer offset AP rises by 7.23
 points, onset AP by only 1.47: dense gains do not imply equal improvement
 at both activity boundaries.
@@ -524,15 +535,16 @@ not real-time deployment. \\
 
 \subsection{EasyCom: Visual Evidence and Ablations}
 
-Adding pooled $\V$ to $\G+\A$ produces only +0.304 points at 0.2~s and
+Table~\ref{tab:visual} separates visual screens from the cross-dataset main
+matrix. Adding Pool to $\G+\A$ produces only +0.304 points at 0.2~s and
 +0.291 mean mAP.  Its wearer increment is +0.020 at 0.2~s and +0.061 when
 averaged over horizons; onset/offset changes are +0.059/+0.120.  A richer
 current-frame person-set model is stable across seeds but reaches lower mean
 mAP than the historical pooled row under a non-matched selection protocol.
 These results do not support a claim of learned speaker grounding. A separate
-seed-0 no-box full-frame F3 screen reaches 82.38\% at 0.2~s and 65.54\%
+seed-0 no-box full-frame TSVA screen reaches 82.38\% at 0.2~s and 65.54\%
 mean mAP, versus 81.72/65.11\% for the existing $\G+\A$ row under the same
-causal-valid dense protocol. F3 adds a two-frame 2-FPS token history and a
+causal-valid dense protocol. TSVA adds a two-frame 2-FPS token history and a
 shared GRU, while head capacity and training batch differ; raw boundary
 metrics and repeat seeds are unavailable. Thus the +0.66/+0.43-point
 difference does not isolate visual motion or floor behavior.

manuscript/targeted/tables_compact.tex

@@ -1,13 +1,11 @@
 % Active result tables. A dash denotes an unreported or unmeasured value.
 \begin{table*}[t]
-\caption{Dense future-activity mAP (\%) by prediction horizon. EasyCom
-scores use Sessions~1--3; the complete ten-horizon curves are reported for
-EgoSpeak, $\G+\A$, and F3. Other archived screens provide only 0.2-s and
-ten-horizon mean scores, so intermediate cells are not interpolated.
-Ego4D transfer is pending. Mean averages all ten horizons, including where
-the individual values are unavailable. F3 and the fusion rows are exploratory
-seed-0 runs; F1 reports a three-seed mean. These rows are not all
-capacity- or training-matched.}
+\caption{Dense future-activity mAP (\%) at ten horizons on EasyCom and
+Ego4D. Each dataset has the same four-method comparison. EasyCom values
+are measured on Sessions~1--3; $\G$ has only archived 0.2-s and mean
+scores, and SVA awaits evaluation. Ego4D scores are pending. Dashes are unreported or unmeasured,
+not zero; intermediate scores are never interpolated. The available Omni
+rows are exploratory and not all training-matched.}
 \label{tab:main}
 \centering\ninept
 \renewcommand{\arraystretch}{0.91}
@@ -19,20 +17,39 @@ Dataset / model & .2 & .4 & .6 & .8 & 1.0 & 1.2 & 1.4 & 1.6 & 1.8 & 2.0 & Mean \
 \midrule
 \multicolumn{12}{@{}l}{\emph{EasyCom (measured)}} \\
 EgoSpeak A+V & 74.20 & 68.35 & 64.31 & 61.13 & 59.77 & 58.81 & 57.50 & 57.09 & 55.95 & 54.82 & 61.19 \\
-Recent $\A$ & 79.69 & -- & -- & -- & -- & -- & -- & -- & -- & -- & 60.51 \\
 Omni $\G$ & 73.45 & -- & -- & -- & -- & -- & -- & -- & -- & -- & 60.85 \\
-$\G+\A$ & 81.72 & 75.92 & 70.38 & 66.46 & 63.81 & 61.37 & 60.00 & 58.32 & 56.95 & 56.16 & 65.11 \\
-$\G+\A+$pooled-$\V$ & 82.03 & -- & -- & -- & -- & -- & -- & -- & -- & -- & 65.40 \\
-Full-frame F3 & 82.38 & 76.42 & 70.78 & 66.35 & 63.93 & 61.87 & 60.41 & 59.11 & 57.61 & 56.53 & 65.54 \\
-Person-set F1 & 81.78 & -- & -- & -- & -- & -- & -- & -- & -- & -- & 64.95 \\
+Omni $\G+\A$ & 81.72 & 75.92 & 70.38 & 66.46 & 63.81 & 61.37 & 60.00 & 58.32 & 56.95 & 56.16 & 65.11 \\
+Omni $\G+\A+\mathrm{SVA}$ & -- & -- & -- & -- & -- & -- & -- & -- & -- & -- & -- \\
 \midrule
 \multicolumn{12}{@{}l}{\emph{Ego4D (transfer pending)}} \\
+EgoSpeak A+V & -- & -- & -- & -- & -- & -- & -- & -- & -- & -- & -- \\
 Omni $\G$ & -- & -- & -- & -- & -- & -- & -- & -- & -- & -- & -- \\
-$\G+\A$ & -- & -- & -- & -- & -- & -- & -- & -- & -- & -- & -- \\
+Omni $\G+\A$ & -- & -- & -- & -- & -- & -- & -- & -- & -- & -- & -- \\
+Omni $\G+\A+\mathrm{SVA}$ & -- & -- & -- & -- & -- & -- & -- & -- & -- & -- & -- \\
 \bottomrule
 \end{tabular*}
 \end{table*}
 
+\begin{table}[t]
+\caption{EasyCom visual-encoding screens (\%). Branch names are defined
+in Sec.~\ref{sec:method}. Available rows are exploratory and not
+capacity- or training-matched.}
+\label{tab:visual}
+\centering\ninept
+\renewcommand{\arraystretch}{0.92}
+\setlength{\tabcolsep}{4pt}
+\begin{tabular}{@{}lcc@{}}
+\toprule
+Visual branch on $\G+\A$ & mAP$_{.2}$ & Mean \\
+\midrule
+None & 81.72 & 65.11 \\
+Pool & 82.03 & 65.40 \\
+SVA & -- & -- \\
+TSVA & 82.38 & 65.54 \\
+\bottomrule
+\end{tabular}
+\end{table}
+
 \begin{table}[t]
 \caption{EasyCom privileged past-activity audit (\%). Three-seed mean
 $\pm$ sample SD. The extra activity cues are not deployable inputs; W is