12 papers
The Llama 4 Herd: Architecture, Training, Evaluation, and Deployment Notes
Redacted by arXiv
This document consolidates publicly reported technical details about Metas Llama 4 model family. It summarizes (i) released variants (Scout and Maverick) and the broader herd conte…
Lowest Span Confidence: A Zero-Shot Metric for Efficient and Black-Box Hallucination Detection in LLMs
Yitong Qiao, Licheng Pan, Yu Mi +4
Hallucinations in Large Language Models (LLMs), i.e., the tendency to generate plausible but non-factual content, pose a significant challenge for their reliable deployment in high…
A Survey on Unlearning in Large Language Models
Ruichen Qiu, Jiajun Tan, Jiayue Pu +3
Large Language Models (LLMs) demonstrate remarkable capabilities, but their training on massive corpora poses significant risks from memorized sensitive information. To mitigate th…
Detecting Stealthy Backdoor Samples based on Intra-class Distance for Large Language Models
Jinwen Chen, Hainan Zhang, Fei Sun +4
Stealthy data poisoning during fine-tuning can backdoor large language models (LLMs), threatening downstream safety. Existing detectors either use classifier-style probability sign…
PolyMath: Evaluating Mathematical Reasoning in Multilingual Contexts
Yiming Wang, Pei Zhang, Jialong Tang +12
In this paper, we introduce PolyMath, a multilingual mathematical reasoning benchmark covering 18 languages and 4 easy-to-hard difficulty levels. Our benchmark ensures difficulty c…
Reinforced Lifelong Editing for Language Models
Zherui Li, Houcheng Jiang, Hao Chen +5
Large language models (LLMs) acquire information from pre-training corpora, but their stored knowledge can become inaccurate or outdated over time. Model editing addresses this cha…