9 papers
Do Large Language Models Truly Understand Cross-cultural Differences?
Shiwei Guo, Sihang Jiang, Qianxi He +6
In recent years, large language models (LLMs) have demonstrated strong performance on multilingual tasks. Given its wide range of applications, cross-cultural understanding capabil…
RationAnomaly: Log Anomaly Detection with Rationality via Chain-of-Thought and Reinforcement Learning
Song Xu, Yilun Liu, Minggui He +10
Logs constitute a form of evidence signaling the operational status of software systems. Automated log anomaly detection is crucial for ensuring the reliability of modern software…
CultureScope: A Dimensional Lens for Probing Cultural Understanding in LLMs
Jinghao Zhang, Sihang Jiang, Shiwei Guo +7
As large language models (LLMs) are increasingly deployed in diverse cultural environments, evaluating their cultural understanding capability has become essential for ensuring tru…
R-Log: Incentivizing Log Analysis Capability in LLMs via Reasoning-based Reinforcement Learning
Yilun Liu, Ziang Chen, Song Xu +10
The growing complexity of log data in modern software systems has prompted the use of Large Language Models (LLMs) for automated log analysis. Current approaches typically rely on…
Emotion Knowledge Enhancement for Vision Large Language Models: A Self-Verification Approach for High-Quality Emotion Instruction Data Generation
Feifan Wang, Tengfei Song, Minggui He +5
Facial emotion perception in the vision large language model (VLLM) is crucial for achieving natural human-machine interaction. However, creating high-quality annotations for both…
ELSPR: Evaluator LLM Training Data Self-Purification on Non-Transitive Preferences via Tournament Graph Reconstruction
Yan Yu, Yilun Liu, Minggui He +9
Pairwise evaluation of large language models (LLMs) has become the dominant paradigm for benchmarking open-ended tasks, yet non-transitive preferences, where evaluators prefer A ov…