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#Visual Memory (2)

WaterfallPagination
joshhhhhan/VISTAMIT

VISTA: A Visual Harness That Lets Multimodal Models Play ARC-AGI-3 From Raw Pixels

MIT's VISTA gives a general-purpose multimodal model raw PNG observations, free-form language reasoning and a lossless archive of every environment frame, then lets it play ARC-AGI-3. With Claude Opus 5.0 it completes all 25 public games and all 183 levels at a perfect RHAE of 100, using 56% fewer actions than first-time human players; with GPT-5.6 Sol it scores 98.27, all without any program synthesis.

ARC-AGI-3Embodied AIVisual Reasoning
Python1700
G0.5: One Autoregressive Stream for Robot Reasoning and Action

G0.5: One Autoregressive Stream for Robot Reasoning and Action

G0.5 is a pretrained autoregressive VLA in which a single transformer decoder emits reasoning and action tokens under one objective. A cross-embodiment action tokenizer, a native chain-of-thought stream, and a visual memory module make this tractable at foundation-model scale, letting the pretrained VLM capabilities carry over to physical behavior. It surpasses pi-0.5 and GR00T-N1.7 across 7 regimes including real-world R1 robot fine-tuning, BEHAVIOR Challenge, DROID zero-shot transfer, LIBERO, RoboTwin 2.0 and SimplerEnv.

Yicheng Liu, Zibin Dong, Baijun YeAug 12, 2026
VLAGalaxeaFoundation ModelsAug 12, 2026