collaborators

15 papers

cs.CL2026

SEEK: Steering LLM Reasoning for RAG via Internal Reasoning Sketches

Xinze Li, Yuqing Lan, Zhenghao Liu +7

Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by incorporating external knowledge into the generation process. Benefiting from the reasoning capabiliti…

cs.CV2026

MemoryCard: Topic-Aware Multi-Modal Clue Compression for Long-Video Question Answering

Qing Yang, Pengcheng Huang, Xinze Li +6

Long-video question answering remains challenging for Vision-Language Models (VLMs), as answer-relevant evidence is often sparse, transient, and temporally dispersed across lengthy…

cs.CL2026

Finding What Matters: Anchoring Context Knowledge with Evolving Indices for Iterative Retrieval

Mingyan Wu, Zhenghao Liu, Xinze Li +7

Retrieval-Augmented Generation (RAG) has become a dominant paradigm for mitigating hallucinations in Large Language Models (LLMs) by incorporating external knowledge. However, exis…

cs.CL2026

MetaMem: Evolving Meta-Memory for Knowledge Utilization through Self-Reflective Symbolic Optimization

Haidong Xin, Xinze Li, Zhenghao Liu +6

Existing memory systems enable Large Language Models (LLMs) to support long-horizon human-LLM interactions by persisting historical interactions beyond limited context windows. How…

cs.CL2026

Chunks as Arms: Multi-Armed Bandit-Guided Sampling for Long-Context LLM Preference Optimization

Shaohua Duan, Pengcheng Huang, Xinze Li +7

Long-context modeling is critical for a wide range of real-world tasks, including long-context question answering, summarization, and complex reasoning tasks. Recent studies have e…

cs.CL2026

HIPPO: Enhancing the Table Understanding Capability of LLMs through Hybrid-Modal Preference Optimization

Haolan Wang, Zhenghao Liu, Xinze Li +7

Tabular data contains rich structural semantics and plays a crucial role in organizing and manipulating information. Recent methods employ Multi-modal Large Language Models (MLLMs)…