We have 3 of 8 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.
QuantWM is presented, a training-free 2-bit KV cache quantization framework for video world models that significantly improves visual quality and temporal consistency, while outperforming existing methods across benchmarks with up to 6.20 KV cache memory compression and limited additional overhead.
SkillProx is introduced, a proximal-gradient-inspired forward--backward framework that couples closed-loop diagnostic evolution with utility-aware proximal refinement and demonstrates the complementary effects of closed-loop diagnosis and proximal refinement.
Omni-RewardBench is introduced, the first benchmark for comprehensive evaluation of ORMs across modalities and demonstrates that current OLLMs fall short as reward models, revealing several common failure modes such as perception failure, modality dominance failure, and cross-modal fusion failure.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
