3 papers
cs.CL2024
WorldMedQA-V: a multilingual, multimodal medical examination dataset for multimodal language models evaluation
João Matos, Shan Chen, Siena Placino +13
Multimodal/vision language models (VLMs) are increasingly being deployed in healthcare settings worldwide, necessitating robust benchmarks to ensure their safety, efficacy, and fai…
cs.CL2024
Identifying Task Groupings for Multi-Task Learning Using Pointwise V-Usable Information
Yingya Li, Timothy Miller, Steven Bethard +1
The success of multi-task learning can depend heavily on which tasks are grouped together. Naively grouping all tasks or a random set of tasks can result in negative transfer, with…
cs.CL2023
Measuring Pointwise -Usable Information In-Context-ly
Sheng Lu, Shan Chen, Yingya Li +3
In-context learning (ICL) is a new learning paradigm that has gained popularity along with the development of large language models. In this work, we adapt a recently proposed hard…