Fix 'too long to render' on Review-World-Models and Reviews: split link-dense mega-lines
Both pages hit GitHub-wiki's render budget after recent growth. Root cause was
single lines packed with 15-17 wikilinks (O(n^2) emphasis/link parsing) — the
same trigger as the earlier RSS survey. Split the pure link-list lines into
shorter lines (content and all links preserved; max wikilinks-per-line 17->7
in World-Models, 15->6 in Reviews). No links removed.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
IROS 2026: add 5 full-paper analyses + reflect into existing in-depth reviews
Full-paper pages (abstract-verified from official program):
- IROS-2026-AtomVLA: subtask-aware VLA + latent-WM scoring for offline GRPO (WAM lens)
- IROS-2026-3D-FlowMatch-Actor: CMU/NVIDIA unified single/dual-arm 3D policy,
+41.4% PerAct2, ~30x faster (bimanual SOTA)
- IROS-2026-EquiBim: symmetry-equivariant bimanual policy
- IROS-2026-IMLE-VLA: single-step cIMLE action head, 55Hz, LIBERO 98.0% (efficiency)
- IROS-2026-ICLR-Visual-Reasoning: in-context imitation with image-space reasoning traces
Reflected IROS 2026 into existing reviews:
- Review-World-Models: WAM-as-critic row (AtomVLA offline GRPO)
- Review-In-Context-Imitation: ICLR-visual-reasoning + RoboSSM
- Review-VLA-Memory: structured-vs-parametric memory row (GaussMemory/PROMPT vs TempoFit/RoboSSM)
- Review-Multitask-VLA: VLA-RL / LAR-MoE / AtomVLA / MoE-humanoid
- Review-Realtime-Execution: single-step head row (IMLE-VLA)
- Review-Humanoid-VLA: IROS bimanual/whole-body trend (3DFA/EquiBim/ULTRA/CEER/MoE-VLA)
Linked all from the IROS 2026 survey.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
DYNA-2: add detailed architecture, WAM comparison, and insights sections
- Detailed model structure (mixture-of-transformers, hand-pose pseudo-
actions, flow-matching co-training, mermaid diagram) with the key
structural fact: video prediction is a co-training objective DROPPED at
inference (action head never sees z_t) -> reactive real-time policy.
- New 'How DYNA-2 differs from other WAMs' section: comparison table +
three axes (data purity, world-model-at-inference reactive vs
co-generate, fitted transfer law vs ablation) vs DreamZero/omega-0/
Cosmos-Policy/DreamGen/DreamDojo/EgoScale.
- New 'Key insights' section (39/39 future-pred ablation, human-video
vs teleop, free-at-inference world-modeling, threshold emergence,
authors' own lower-bound/compute caveats).
- Refined DYNA-2 entry in Review-World-Models to note reactive decoupling.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Escape pipe in all in-table wikilinks wiki-wide (202 links, 17 files)
GitHub-wiki table cells read a wikilink's separator | as a column
delimiter, splitting the cell and breaking the link. Escape to \| in
every table-row wikilink (Home nav, RSS-2026-Papers, topic surveys).
Prose wikilinks left as plain | (render correctly outside tables).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Add DYNA-2 in-depth review (Dyna Robotics World-Action Model launch)
Company announcement (Aug 10, 2026), not a paper: WAM on ~1M h human
egocentric video with no robot data in pre-training, joint next-frame+
next-action, claimed first human-to-robot scaling law smooth over
1k->1M h (~50x EgoScale), 87% vs 46% zero-shot over DYNA-1. Reviewed
with an explicit vendor-claim caveat (no technical paper/benchmark/
weights). Filed under Latest Papers; cross-linked from World-Models,
Human-Video-Transfer, Reviews.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Add Latest Papers tracker + omega-0 and Stellar VLA in-depth reviews
New Latest-Papers.md preprint tracker (pre-publication reviews) and two
figure-illustrated in-depth reviews: omega-0 (arXiv 2608.06375, whole-
body humanoid latent-predictive World Action Model; 81.8% on 11
household tasks vs 44.5% psi-0; ships 40h omega-HOME dataset) and
Stellar VLA (arXiv 2511.18085, continual imitation learning with a
Dirichlet-Process knowledge space + knowledge-routed MoE, 1% replay).
Cross-linked from Home, Reviews, sidebar, Humanoid-VLA, World-Models.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Add DreamZero in-depth review (World Action Models are Zero-shot Policies)
NVIDIA's 14B video-diffusion World Action Model (arXiv 2602.15922):
jointly predicts video+action, >2x over SOTA VLAs on unseen-env/
unseen-object real-robot evals, 38x inference stack (DreamZero-Flash)
for 7 Hz closed-loop control, video-only cross-embodiment transfer.
Fig. 4 architecture embedded. Cross-linked from World Models review,
Home lab-programs, Reviews catalog, and sidebar.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Weave ICML 2026 evidence into deep-dive surveys; revise three verdicts
14 State-of-the-Field sections gain ICML 2026 findings from the
99-paper index: recipes and latent-action supervision (VLANeXt,
From-Pixels-to-Tokens, XR-1), MoT dual-systems and shortcut counters,
the 9-paper efficiency cluster (Reflex 50Hz, GridS -76% FLOPs, XPU
profile, latent reasoning -90%), reward/critic and model-based RL
(VLAC, VLAW +39.2%), memory (HiMe/SOMA/CAPS), world models (DreamDojo
44kh, LAC-WM, dWorldEval), dexterous (DexMachina/DECO/Tabero/CTSRL),
cross-embodiment (OXE-AugE, latent motion codes), evaluation
(LIBERO-Gen, VLA-Arena, FixBench, TRAP). Verdicts revised: forgetting
milder than assumed; discrete-token verdict scoped to robot-action
auxiliaries; WM-evaluator action gap first crack. Home synced.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Decision map: prominent deep-dive links + uniform detail-page template
Home fold-outs now lead with a heading-level "Deep dive ->" link and
compress trend/approaches/limitations into a labeled 3-row table.
The 12 detail-page State-of-the-Field sections are rewritten to one
template (Verdict quote + Trend + Approaches-and-trade-offs +
optional Established-findings + Limitations, dated Aug 2026); the
three standalone surveys get matching headers with structure legends.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Survey-depth topic pages: 12 State-of-the-Field updates + 3 new surveys
Each decision-map topic's detail page now carries a dated July-2026
survey section: trend arc through the latest venues, approach
taxonomy with definitions and trade-offs, and current limitations.
Three previously page-less topics get dedicated surveys:
Human-Video Transfer (emergence/decoupling/synthesis fork + decision
guide), VLA Evaluation (indictment + 2026 toolkit + emerging norms),
Real-Time Execution (RTC->Legato arc + approach comparison). Home
fold-outs link the full surveys; Reviews catalog updated.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Fix broken tables: escape unescaped pipes inside wikilinks in table rows
ICLR.md (and 12 other pages) had [[label|Page]] wikilinks with raw pipes inside
GFM table cells, which the GitHub-wiki renderer reads as column separators —
mangling the table. Escaped the wikilink-internal pipes to \| (matching the
convention already used by CVPR/NeurIPS/CoRL pages); table column separators
left intact.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Add in-depth review: OmniVTA (visuo-tactile world modeling) + 2026 tactile-VLA analysis
New Review-OmniVTA page (arXiv 2603.19201): 4-module visuo-tactile world model
(TactileVAE + two-stream contact-evolution predictor + contact-aware fusion policy
+ 60Hz Reflexive Latent Tactile Controller), OmniViTac dataset (21k+ traj / 86 tasks /
100+ objects), GelSight Mini; beats Diffusion Policy / FoAR, closed-loop >> open-loop.
Includes a 4-camp analysis of 2026 tactile-VLA research (ICRA 2026: FD-VLA, SaTA,
ManipForce, TranTac, FreeTacMan, Multi-Modal Consensus, DOT-Sim; CVPR 2026: HapticVLA),
framing the sensor-in-loop (OmniVTA) vs sensor-free (FD-VLA/HapticVLA) fault line.
Adds a new "predictive reference for reflexive control" world-model role. Linked from
Dexterous/Architecture/World-Models reviews + Home + sidebar. 0 dangling links.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
World Models review: add Family F — WM + inverse-dynamics action decoding
New §3 model family (compositional, cuts across A–D): world model predicts the
future, an inverse-dynamics / latent-action model decodes the action.
- generate-then-decode (UniPi, HiP, VLP, RoboDreamer; DreamGen data-factory use)
- disentangled forward+inverse pretraining (DeFI)
- latent-action IDM from action-free video (villa-X, UniVLA, ViPRA, Human-Video-Pretraining)
Pros (decouple what-to-do from how-to-act; action-free/cross-embodiment pretraining)
+ cons (inverse-dynamics drift → shift to co-generation / goal-pose / π0.7 token-direct).
Added matching row to the §7 comparison table. 0 dangling links.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Add in-depth review: World Models for Robot Learning
New cross-paper, model-centric review (sibling to Review-VLA-Architecture's
Category E usage taxonomy). Two axes — what the WM predicts (pixel video-diffusion /
AR-token / latent-JEPA / 3D-4D-geometry / structured-cue) x how robotics uses it
(backbone / RL-env / data-factory / planner / evaluator / aux-loss). Synthesizes
in-wiki pages (Cosmos-Policy, Genie-Envisioner, WMPO, Ctrl-World, WorldGym, DreamGen,
VLA-RFT, DreamVLA, Geometry-4D, ...) + external landscape (Cosmos, Genie 3, V-JEPA 2,
DINO-WM, NWM). Latest trends, pros/cons per family, six tensions, decision guide.
Linked from Home + sidebar. 0 dangling links.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>