Physics-IQ benchmark reveals that generative video models exhibit limited physical understanding unrelated to their visual quality.
Physgame: Uncovering physical commonsense violations in gameplay videos
5 Pith papers cite this work. Polarity classification is still indexing.
5
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
roles
background 1polarities
background 1representative citing papers
PhyGround is a new benchmark with curated prompts, a 13-law taxonomy, large-scale human annotations, and an open physics-specialized VLM judge for evaluating physical reasoning in generative video models.
RESP uses reference-guided sequential prompting with VLMs to improve frame-level and video-level visual glitch detection in games by establishing per-video baselines.
Introduces the first benchmark for open-ended video game glitch detection with temporal localization and proposes GliDe, an agentic framework that achieves stronger performance than vanilla multimodal models.
TempGlitch is a controlled benchmark showing that 12 evaluated VLMs perform near chance level on detecting five types of temporal glitches in gameplay videos, with denser sampling and larger models providing no reliable improvement.
citing papers explorer
-
PhyGround: Benchmarking Physical Reasoning in Generative World Models
PhyGround is a new benchmark with curated prompts, a 13-law taxonomy, large-scale human annotations, and an open physics-specialized VLM judge for evaluating physical reasoning in generative video models.