activity
20222026
most citedA Distributional Lens for Multi-Aspect Controllable Text Generation

4 citations · 5 across the 16 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

cs.CL2024

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…

cs.LG2024

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…

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…

cs.CL2024

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…

cs.CV2024★ 1 cited

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…

cs.CL2024

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…