6 papers
Controlling Repetition in Protein Language Models
Jiahao Zhang, Zeqing Zhang, Di Wang +1
Protein language models (PLMs) have enabled advances in structure prediction and de novo protein design, yet they frequently collapse into pathological repetition during generation…
RAG-Anything: All-in-One RAG Framework
Zirui Guo, Xubin Ren, Lingrui Xu +2
Retrieval-Augmented Generation (RAG) has emerged as a fundamental paradigm for expanding Large Language Models beyond their static training limitations. However, a critical misalig…
LSM-OPD: Boosting Scan in LSM-Trees by Enabling Direct Computing on Compressed Data
Jianfeng Huang, Ziyao Wang, Lin Yuan +5
Scan-based operations, such as backstage compaction and value filtering, have emerged as the main bottleneck for LSM-Trees in supporting contemporary data-intensive applications. F…
Retrieval-Augmented Prompt for OOD Detection
Ruisong Han, Zongbo Han, Jiahao Zhang +2
Out-of-Distribution (OOD) detection is crucial for the reliable deployment of machine learning models in-the-wild, enabling accurate identification of test samples that differ from…
Distilling Desired Comments for Enhanced Code Review with Large Language Models
Yongda Yu, Lei Zhang, Guoping Rong +9
There has been a growing interest in using Large Language Models (LLMs) for code review thanks to their proven proficiency in code comprehension. The primary objective of most revi…
TombRaider: Entering the Vault of History to Jailbreak Large Language Models
Junchen Ding, Jiahao Zhang, Yi Liu +3
Warning: This paper contains content that may involve potentially harmful behaviours, discussed strictly for research purposes. Jailbreak attacks can hinder the safety of Large Lan…