2.1k citations · 2.1k across the 31 of their papers we have counts for
11 papers · 1 filter
Length Controlled Generation for Black-box LLMs
Yuxuan Gu, Wenjie Wang, Xiaocheng Feng +5
Large language models (LLMs) have demonstrated impressive instruction following capabilities, while still struggling to accurately manage the length of the generated text, which is…
Discrete Modeling via Boundary Conditional Diffusion Processes
Yuxuan Gu, Xiaocheng Feng, Lei Huang +5
We present an novel framework for efficiently and effectively extending the powerful continuous diffusion processes to discrete modeling. Previous approaches have suffered from the…
Advancing Large Language Model Attribution through Self-Improving
Lei Huang, Xiaocheng Feng, Weitao Ma +7
Teaching large language models (LLMs) to generate text with citations to evidence sources can mitigate hallucinations and enhance verifiability in information-seeking systems. Howe…
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…
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…
Investigating and Mitigating the Multimodal Hallucination Snowballing in Large Vision-Language Models
Weihong Zhong, Xiaocheng Feng, Liang Zhao +6
Though advanced in understanding visual information with human languages, Large Vision-Language Models (LVLMs) still suffer from multimodal hallucinations. A natural concern is tha…
An Information Bottleneck Perspective for Effective Noise Filtering on Retrieval-Augmented Generation
Kun Zhu, Xiaocheng Feng, Xiyuan Du +7
Retrieval-augmented generation integrates the capabilities of large language models with relevant information retrieved from an extensive corpus, yet encounters challenges when con…
Unveiling Entity-Level Unlearning for Large Language Models: A Comprehensive Analysis
Weitao Ma, Xiaocheng Feng, Weihong Zhong +4
Large language model unlearning has garnered increasing attention due to its potential to address security and privacy concerns, leading to extensive research in the field. However…
Ensemble Learning for Heterogeneous Large Language Models with Deep Parallel Collaboration
Yichong Huang, Xiaocheng Feng, Baohang Li +4
Large language models (LLMs) exhibit complementary strengths in various tasks, motivating the research of LLM ensembling. However, existing work focuses on training an extra reward…
Relay Decoding: Concatenating Large Language Models for Machine Translation
Chengpeng Fu, Xiaocheng Feng, Yichong Huang +5
Leveraging large language models for machine translation has demonstrated promising results. However, it does require the large language models to possess the capability of handlin…
Aligning Translation-Specific Understanding to General Understanding in Large Language Models
Yichong Huang, Baohang Li, Xiaocheng Feng +4
Large Language models (LLMs) have exhibited remarkable abilities in understanding complex texts, offering a promising path towards human-like translation performance. However, this…