4 papers
When Personality Meets Quantization: A Layer-wise MBTI Analysis of Quantized LLMs
Yao Fu, Lijia Huang, Xiaomin Li +3
Personality is increasingly important in large language models (LLMs), as it shapes users' trust, engagement, and emotional experiences. While the Myers--Briggs Type Indicator (MBT…
The Vulnerability of LLM Rankers to Prompt Injection Attacks
Yu Yin, Shuai Wang, Bevan Koopman +1
Large Language Models (LLMs) have emerged as powerful re-rankers. Recent research has however showed that simple prompt injections embedded within a candidate document (i.e., jailb…
Pruning Weights but Not Truth: Safeguarding Truthfulness While Pruning LLMs
Yao Fu, Runchao Li, Xianxuan Long +4
Neural network pruning has emerged as a promising approach for deploying LLMs in low-resource scenarios while preserving downstream task performance. However, for the first time, w…
Cautious Next Token Prediction
Yizhou Wang, Lingzhi Zhang, Yue Bai +7
Next token prediction paradigm has been prevailing for autoregressive models in the era of LLMs. The current default sampling choice for popular LLMs is temperature scaling togethe…