3 papers
cs.CV2026
Sparse-to-Dense: A Free Lunch for Lossless Acceleration of Video Understanding in LLMs
Xuan Zhang, Cunxiao Du, Sicheng Yu +4
Due to the auto-regressive nature of current video large language models (Video-LLMs), the inference latency increases as the input sequence length grows, posing challenges for the…
cs.CL2026
LightTransfer: Your Long-Context LLM is Secretly a Hybrid Model with Effortless Adaptation
Xuan Zhang, Fengzhuo Zhang, Cunxiao Du +4
Scaling language models to handle longer contexts introduces substantial memory challenges due to the growing cost of key-value (KV) caches. Motivated by the efficiency gains of hy…
cs.CL2024
Reinforcement Retrieval Leveraging Fine-grained Feedback for Fact Checking News Claims with Black-Box LLM
Xuan Zhang, Wei Gao
Retrieval-augmented language models have exhibited promising performance across various areas of natural language processing (NLP), including fact-critical tasks. However, due to t…