36 papers
HiEviDR-Bench: A Benchmark for Hierarchical Evidence Aggregation in Deep Research
Yubo Sun, Chunyi Peng, Yukun Yan +6
Deep research requires models to retrieve, connect, and synthesize evidence from large-scale heterogeneous sources to answer complex queries and produce analytical reports. Existin…
REFACT: Adaptive Fact Restatement for Compact and Faithful Chain-of-Thought Reasoning
Zhensheng Jin, Xin Dai, Zhenghao Liu +5
Large Language Models (LLMs) increasingly leverage long-form reasoning to solve complex tasks, yet their reasoning processes can deviate from the provided context when evidence is…
ParamMute: Suppressing Knowledge-Critical FFNs for Faithful Retrieval-Augmented Generation
Pengcheng Huang, Zhenghao Liu, Yukun Yan +8
Large language models (LLMs) integrated with retrieval-augmented generation (RAG) have improved factuality by grounding outputs in external evidence. However, they remain susceptib…
CheckRLM: Effective Knowledge-Thought Coherence Checking in Retrieval-Augmented Reasoning
Dingling Xu, Ruobing Wang, Qingfei Zhao +8
Reasoning Language Models (RLMs) have significantly improved performance on complex tasks by extending the reasoning chain. However, these chains are prone to containing factual er…
UniSVQ: 2-bit Unified Scalar-Vector Quantization
Haoyu Wang, Haiyan Zhao, Xingyu Yu +4
Post-training quantization at the 2-bit level enables low-cost deployment and inference acceleration for large language models (LLMs). Scalar quantization (SQ) and vector quantizat…
From Holistic Evaluation to Structured Criteria: Rubrics Across the Evolving LLM Landscape
Hao Chen, Ziyu Han, Yukun Yan +3
As Large Language Models (LLMs) advance toward open-ended autonomous agents, the mechanisms used to evaluate and guide their behavior must evolve accordingly. This work introduces…