We have 4 of 28 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
This work introduces HarnessEval-W, an agentified evaluation pipeline that brings the harness paradigm from the LLM ecosystem to world model benchmarking, and applies HarnessEval-W to 18 representative world models over 330 evaluation cases.
UMM-Reflection is introduced, which applies reinforcement learning (RL) to complete reflection trajectories inside one unified model: sibling trajectories share one initial image, so the group-relative advantage compares reflection strategies, and one trajectory-level advantage updates both the reflection tokens and th...
The Evaluation Agent framework is proposed, which employs human-like strategies for efficient, dynamic, multi-round evaluations, offering detailed, user-tailored analyses and is efficient, promptable, explainable, and scalable across models and tools.
Apple-PI is introduced, the first benchmark that anchors video-model evaluation explicitly in physical laws, and is positioned as a diagnostic foundation for guiding future video models toward world models with law-grounded physical intelligence.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
