3 papers
cs.CL2025
DATE-LM: Benchmarking Data Attribution Evaluation for Large Language Models
Cathy Jiao, Yijun Pan, Emily Xiao +6
Data attribution methods quantify the influence of training data on model outputs and are becoming increasingly relevant for a wide range of LLM research and applications, includin…
cs.CV2025
The in-context inductive biases of vision-language models differ across modalities
Kelsey Allen, Ishita Dasgupta, Eliza Kosoy +1
Inductive biases are what allow learners to make guesses in the absence of conclusive evidence. These biases have often been studied in cognitive science using concepts or categori…
cs.CV2025
Decoupling the components of geometric understanding in Vision Language Models
Eliza Kosoy, Annya Dahmani, Andrew K. Lampinen +4
Understanding geometry relies heavily on vision. In this work, we evaluate whether state-of-the-art vision language models (VLMs) can understand simple geometric concepts. We use a…