3 citations · 6 across the 11 of their papers we have counts for
9 papers · 1 filter
Semantic Head Specialization Guides Hybrid ViT Attention for Multimodal LLMs
Chenhong He, Lei Li, Shicheng Li +5
Hybrid attention dominates frontier LLMs, yet Vision Transformers (ViTs) in multimodal LLMs lack a satisfactory hybrid design, with no consensus on why certain attention patterns w…
TimeChat-Online: 80% Visual Tokens are Naturally Redundant in Streaming Videos
Linli Yao, Yicheng Li, Yuancheng Wei +11
The rapid growth of online video platforms, particularly live streaming services, has created an urgent need for real-time video understanding systems. These systems must process c…
TEMPLE: Incentivizing Temporal Understanding of Video Large Language Models via Progressive Pre-SFT Alignment
Shicheng Li, Lei Li, Kun Ouyang +7
Video Large Language Models (Video LLMs) have achieved significant success by adopting the paradigm of large-scale pre-training followed by supervised fine-tuning (SFT). However, e…
GIRAFFE: Design Choices for Extending the Context Length of Visual Language Models
Mukai Li, Lei Li, Shansan Gong +1
Visual Language Models (VLMs) demonstrate impressive capabilities in processing multimodal inputs, yet applications such as visual agents, which require handling multiple images an…
VL-RewardBench: A Challenging Benchmark for Vision-Language Generative Reward Models
Lei Li, Yuancheng Wei, Zhihui Xie +9
Vision-language generative reward models (VL-GenRMs) play a crucial role in aligning and evaluating multimodal AI systems, yet their own evaluation remains under-explored. Current…
VLFeedback: A Large-Scale AI Feedback Dataset for Large Vision-Language Models Alignment
Lei Li, Zhihui Xie, Mukai Li +7
As large vision-language models (LVLMs) evolve rapidly, the demand for high-quality and diverse data to align these models becomes increasingly crucial. However, the creation of su…