Liang He

S KILL G YM : I NTERNALIZING L ARGE -S CALE H UMAN S KILLS INTO LLM S FOR R EAL -W ORLD P ROBLEM S OLVING

Behavior Pack Optimization for Video MLLM Post-Training

Video multimodal large language models (MLLMs) keep climbing video question answering benchmarks, yet shuffling the frames, masking the segment that supports the answer, or occluding the target object barely changes their predictions. The accuracy rests on appearance and language priors, not on the temporal evidence th...

Not All Visual Tokens Are Equally Safe to Remove:Consequence-Sensitive Visual Token Compression

Visual token compression for vision--language models (VLMs) has largely relied on criteria such as attention, redundancy, and uncertainty to maximize average accuracy under a fixed compute budget, implicitly assuming that all errors carry equal cost. However, the consequence of an incorrect prediction on downstream tas...