LIVE PULSE
4.0 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.2 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src2.0 Apple ships rebuilt Siri with Google Gemini, but not in the EU — 2 src1.8 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions — 2 src1.4 Sam Altman says OpenAI will not go public in 2026, citing AI safety concerns — 5 src1.1 OpenAI contractors review real ChatGPT conversations to rate responses, report says — 2 src1.1 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.1 Study examines issue bias in LLMs used as writing assistants before Swedish 2026 election — 1 src1.1 Study Audits Misalignment in Multi-Modal World Models — 1 src1.1 Retrieval-Grounded Reasoning Approach Proposed for Universal Multimodal Embeddings — 1 src4.0 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.2 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src2.0 Apple ships rebuilt Siri with Google Gemini, but not in the EU — 2 src1.8 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions — 2 src1.4 Sam Altman says OpenAI will not go public in 2026, citing AI safety concerns — 5 src1.1 OpenAI contractors review real ChatGPT conversations to rate responses, report says — 2 src1.1 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.1 Study examines issue bias in LLMs used as writing assistants before Swedish 2026 election — 1 src1.1 Study Audits Misalignment in Multi-Modal World Models — 1 src1.1 Retrieval-Grounded Reasoning Approach Proposed for Universal Multimodal Embeddings — 1 src
HEATPULSEAI MAGAZINES
FLIP · FOLLOW · SAVE
Log inSign up
papersTODAY 04:00 UTC

Probing Video Foundation Models for Intuitive Physics Representations

A study examines whether pretrained video foundation models hold intuitive-physics information in their frozen representations. Using frozen-feature probing on the IntPhys2 benchmark, the authors compare how this information differs across model families, layers, and probe types. The work is a cross-listed arXiv replacement submission in cs.AI and cs.LG.

IntPhys2 benchmarkarXiv preprintsfrozen-feature probingintuitive physicsrepresentation interpretabilityvideo foundation models

COVERAGE · 2 REPORTS · LINKS GO TO THE ORIGINAL OUTLETS

arXiv cs.AIHow Do Video Foundation Models Encode Intuitive Physics? Probing Across Pretraining Paradigms ↗TODAY 04:00 UTC
arXiv cs.LGHow Do Video Foundation Models Encode Intuitive Physics? Probing Across Pretraining Paradigms ↗TODAY 04:00 UTC

MORE LIKE THIS

papersarXiv Paper Tests How Vision-Language Models Choose Physical Experimentsheat 0.1
papersBenchmark and Method Proposed for Think-with-Video Reasoning in Generative Modelsheat 0.1
papersPIVOT Method Uses Physics Cues to Detect AI-Generated Audio-Videoheat 1.1
papersStudy finds video models store correct physics but fail to apply itheat 1.1