6 papers · 1 filter
Can Large Language Models Identify Implicit Suicidal Ideation? An Empirical Evaluation
Tong Li, Shu Yang, Junchao Wu +6
We present a comprehensive evaluation framework for assessing Large Language Models' (LLMs) capabilities in suicide prevention, focusing on two critical aspects: the Identification…
Understanding the Repeat Curse in Large Language Models from a Feature Perspective
Junchi Yao, Shu Yang, Jianhua Xu +3
Large language models (LLMs) have made remarkable progress in various domains, yet they often suffer from repetitive text generation, a phenomenon we refer to as the "Repeat Curse"…
Fraud-R1 : A Multi-Round Benchmark for Assessing the Robustness of LLM Against Augmented Fraud and Phishing Inducements
Shu Yang, Shenzhe Zhu, Zeyu Wu +7
We introduce Fraud-R1, a benchmark designed to evaluate LLMs' ability to defend against internet fraud and phishing in dynamic, real-world scenarios. Fraud-R1 comprises 8,564 fraud…
Exploring the Personality Traits of LLMs through Latent Features Steering
Shu Yang, Shenzhe Zhu, Liang Liu +3
Large language models (LLMs) have significantly advanced dialogue systems and role-playing agents through their ability to generate human-like text. While prior studies have shown…
A Hopfieldian View-based Interpretation for Chain-of-Thought Reasoning
Lijie Hu, Liang Liu, Shu Yang +6
Chain-of-Thought (CoT) holds a significant place in augmenting the reasoning performance for large language models (LLMs). While some studies focus on improving CoT accuracy throug…
Dialectical Alignment: Resolving the Tension of 3H and Security Threats of LLMs
Shu Yang, Jiayuan Su, Han Jiang +5
With the rise of large language models (LLMs), ensuring they embody the principles of being helpful, honest, and harmless (3H), known as Human Alignment, becomes crucial. While exi…