87 citations · 419 across the 19 of their papers we have counts for
37 papers
HealMed: Multilingual Evaluation of Large Language Models in Medicine
Yingjian Chen, Fan Gao, Sherry T. Tong +42
We present HealMed, an expert-reviewed benchmark for multilingual evaluation of large language models in medicine. HealMed contains 1,000 examples in each of nine languages, drawn…
gpt-oss-120b & gpt-oss-20b Model Card
OpenAI, :, Sandhini Agarwal +124
We present gpt-oss-120b and gpt-oss-20b, two open-weight reasoning models that push the frontier of accuracy and inference cost. The models use an efficient mixture-of-expert trans…
Pisces: An Auto-regressive Foundation Model for Image Understanding and Generation
Zhiyang Xu, Jiuhai Chen, Zhaojiang Lin +10
Recent advances in large language models (LLMs) have enabled multimodal foundation models to tackle both image understanding and generation within a unified framework. Despite thes…
Out-of-Distribution Detection Methods Answer the Wrong Questions
Yucen Lily Li, Daohan Lu, Polina Kirichenko +4
To detect distribution shifts and improve model safety, many out-of-distribution (OOD) detection methods rely on the predictive uncertainty or features of supervised models trained…
reWordBench: Benchmarking and Improving the Robustness of Reward Models with Transformed Inputs
Zhaofeng Wu, Michihiro Yasunaga, Andrew Cohen +3
Reward models have become a staple in modern NLP, serving as not only a scalable text evaluator, but also an indispensable component in many alignment recipes and inference-time al…
Multimodal RewardBench: Holistic Evaluation of Reward Models for Vision Language Models
Michihiro Yasunaga, Luke Zettlemoyer, Marjan Ghazvininejad
Reward models play an essential role in training vision-language models (VLMs) by assessing output quality to enable aligning with human preferences. Despite their importance, the…