4 citations · 5 across the 16 of their papers we have counts for
6 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…
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…
Learning Fine-Grained Grounded Citations for Attributed Large Language Models
Lei Huang, Xiaocheng Feng, Weitao Ma +8
Despite the impressive performance on information-seeking tasks, large language models (LLMs) still struggle with hallucinations. Attributed LLMs, which augment generated text with…
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…