4 papers
Any Large Language Model Can Be a Reliable Judge: Debiasing with a Reasoning-based Bias Detector
Haoyan Yang, Runxue Bao, Cao Xiao +4
LLM-as-a-Judge has emerged as a promising tool for automatically evaluating generated outputs, but its reliability is often undermined by potential biases in judgment. Existing eff…
ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation
Xiaomeng Yang, Lei Lu, Qihui Fan +5
Diffusion models have demonstrated exceptional capabilities in generating high-fidelity images. However, their iterative denoising process results in significant computational over…
All-in-One Tuning and Structural Pruning for Domain-Specific LLMs
Lei Lu, Zhepeng Wang, Runxue Bao +7
Existing pruning techniques for large language models (LLMs) targeting domain-specific applications typically follow a two-stage process: pruning the pretrained general-purpose LLM…
Unlocking Memorization in Large Language Models with Dynamic Soft Prompting
Zhepeng Wang, Runxue Bao, Yawen Wu +6
Pretrained large language models (LLMs) have revolutionized natural language processing (NLP) tasks such as summarization, question answering, and translation. However, LLMs pose s…