11 papers
Context Attribution with Multi-Armed Bandit Optimization
Deng Pan, Keerthiram Murugesan, Ting Hua +2
Understanding which parts of the retrieved context contribute to a large language model's generated answer is essential for building interpretable and trustworthy retrieval-augment…
Fast Explanations via Policy Gradient-Optimized Explainer
Deng Pan, Nuno Moniz, Nitesh Chawla
The challenge of delivering efficient explanations is a critical barrier that prevents the adoption of model explanations in real-world applications. Existing approaches often depe…
LabSafety Bench: Benchmarking LLMs on Safety Issues in Scientific Labs
Yujun Zhou, Jingdong Yang, Yue Huang +12
Artificial Intelligence (AI) is revolutionizing scientific research, yet its growing integration into laboratory environments presents critical safety challenges. Large language mo…
LLMs4All: A Review of Large Language Models Across Academic Disciplines
Yanfang Ye, Zheyuan Zhang, Tianyi Ma +26
Cutting-edge Artificial Intelligence (AI) techniques keep reshaping our view of the world. For example, Large Language Models (LLMs) based applications such as ChatGPT have shown t…
Intersectional Divergence: Measuring Fairness in Regression
Joe Germino, Nuno Moniz, Nitesh V. Chawla
Fairness in machine learning research is commonly framed in the context of classification tasks, leaving critical gaps in regression. In this paper, we propose a novel approach to…
BenchmarkCards: Standardized Documentation for Large Language Model Benchmarks
Anna Sokol, Elizabeth Daly, Michael Hind +4
Large language models (LLMs) are powerful tools capable of handling diverse tasks. Comparing and selecting appropriate LLMs for specific tasks requires systematic evaluation method…