4 papers
Would you still call this Dax? Novel Visual References in VLMs and Humans
Ada Defne Tür, Gaurav Kamath, Joyce Chai +2
Vision-language models (VLMs), like human learners, are frequently exposed to new visual concepts, but how they map novel visual references to language after exposure remains large…
Humans and LLMs Diverge on Probabilistic Inferences
Gaurav Kamath, Sreenath Madathil, Sebastian Schuster +2
Human reasoning often involves working over limited information to arrive at probabilistic conclusions. In its simplest form, this involves making an inference that is not strictly…
Build the web for agents, not agents for the web
Xing Han Lù, Gaurav Kamath, Marius Mosbach +1
Recent advancements in Large Language Models (LLMs) and multimodal counterparts have spurred significant interest in developing web agents -- AI systems capable of autonomously nav…
Language Models Largely Exhibit Human-like Constituent Ordering Preferences
Ada Defne Tur, Gaurav Kamath, Siva Reddy
Though English sentences are typically inflexible vis-Ã -vis word order, constituents often show far more variability in ordering. One prominent theory presents the notion that con…