3 papers
cs.CL2025
Vision-and-Language Training Helps Deploy Taxonomic Knowledge but Does Not Fundamentally Alter It
Yulu Qin, Dheeraj Varghese, Adam Dahlgren Lindström +3
Does vision-and-language (VL) training change the linguistic representations of language models in meaningful ways? Most results in the literature have shown inconsistent or margin…
cs.CL2025
RExBench: Can coding agents autonomously implement AI research extensions?
Nicholas Edwards, Yukyung Lee, Yujun Audrey Mao +3
Agents based on Large Language Models (LLMs) have shown promise for performing sophisticated software engineering tasks autonomously. In addition, there has been progress towards d…
cs.CL2024
A systematic investigation of learnability from single child linguistic input
Yulu Qin, Wentao Wang, Brenden M. Lake
Language models (LMs) have demonstrated remarkable proficiency in generating linguistically coherent text, sparking discussions about their relevance to understanding human languag…