3 papers
cs.CL2026
Disco-RAG: Discourse-Aware Retrieval-Augmented Generation
Dongqi Liu, Hang Ding, Qiming Feng +6
Retrieval-Augmented Generation (RAG) has emerged as an important means of enhancing the performance of large language models (LLMs) in knowledge-intensive tasks. However, most exis…
cs.CV2025
AdaVideoRAG: Omni-Contextual Adaptive Retrieval-Augmented Efficient Long Video Understanding
Zhucun Xue, Jiangning Zhang, Xurong Xie +4
Multimodal Large Language Models (MLLMs) perform well in video understanding but degrade on long videos due to fixed-length context and weak long-term dependency modeling. Retrieva…
cs.CL2025
LLM-Oriented Token-Adaptive Knowledge Distillation
Xurong Xie, Zhucun Xue, Jiafu Wu +5
Knowledge distillation (KD) is a key technique for compressing large-scale language models (LLMs), yet prevailing logit-based methods typically employ static strategies that are mi…