10 papers
TimeThink: Reasoning with Time for Video LLMs
Handong Li, Longteng Guo, Zikang Liu +8
Video reasoning requires models to identify and verify temporally localized evidence within long video sequences. Recent Video Large Language Models (Video-LLMs) have shown promisi…
AdaSpark: Adaptive Sparsity for Efficient Long-Video Understanding
Handong Li, Zikang Liu, Longteng Guo +10
Processing long-form videos with Video Large Language Models (Video-LLMs) is computationally prohibitive. Current efficiency methods often compromise fine-grained perception throug…
EVA: Efficient Reinforcement Learning for End-to-End Video Agent
Yaolun Zhang, Ruohui Wang, Jiahao Wang +6
Video understanding with multimodal large language models (MLLMs) remains challenging due to the long token sequences of videos, which contain extensive temporal dependencies and r…
VRoPE: Rotary Position Embedding for Video Large Language Models
Zikang Liu, Longteng Guo, Yepeng Tang +6
Rotary Position Embedding (RoPE) has shown strong performance in text-based Large Language Models (LLMs), but extending it to video remains a challenge due to the intricate spatiot…
ELV-Halluc: Benchmarking Semantic Aggregation Hallucinations in Long Video Understanding
Hao Lu, Jiahao Wang, Yaolun Zhang +5
Video multimodal large language models (Video-MLLMs) have achieved remarkable progress in video understanding. However, they remain vulnerable to hallucination-producing content in…
BrainGPT: Unleashing the Potential of EEG Generalist Foundation Model by Autoregressive Pre-training
Tongtian Yue, Xuange Gao, Shuning Xue +4
Electroencephalogram (EEG) signals are pivotal in providing insights into spontaneous brain activity, highlighting their significant importance in neuroscience research. However, t…