3 papers
cs.CL2025
Improving Contextual Faithfulness of Large Language Models via Retrieval Heads-Induced Optimization
Lei Huang, Xiaocheng Feng, Weitao Ma +9
Ensuring contextual faithfulness in retrieval-augmented large language models (LLMs) is crucial for building trustworthy information-seeking systems, particularly in long-form ques…
cs.CL2024
GlobeSumm: A Challenging Benchmark Towards Unifying Multi-lingual, Cross-lingual and Multi-document News Summarization
Yangfan Ye, Xiachong Feng, Xiaocheng Feng +6
News summarization in today's global scene can be daunting with its flood of multilingual content and varied viewpoints from different sources. However, current studies often negle…
cs.CL2024
Extending Context Window of Large Language Models from a Distributional Perspective
Yingsheng Wu, Yuxuan Gu, Xiaocheng Feng +5
Scaling the rotary position embedding (RoPE) has become a common method for extending the context window of RoPE-based large language models (LLMs). However, existing scaling metho…