10 papers
Video Finetuning Improves Reasoning Between Frames
Ruiqi Yang, Tian Yun, Zihan Wang +1
Multimodal large language models (LLMs) have made rapid progress in visual understanding, yet their extension from images to videos often reduces to a naive concatenation of frame…
Can LLMs subtract numbers?
Mayank Jobanputra, Nils Philipp Walter, Maitrey Mehta +7
We present a systematic study of subtraction in large language models (LLMs). While prior benchmarks emphasize addition and multiplication, subtraction has received comparatively l…
From Prediction to Understanding: Will AI Foundation Models Transform Brain Science?
Thomas Serre, Ellie Pavlick
Generative pretraining (the "GPT" in ChatGPT) enables language models to learn from vast amounts of internet text without human supervision. This approach has driven breakthroughs…
What is an "Abstract Reasoner"? Revisiting Experiments and Arguments about Large Language Models
Tian Yun, Chen Sun, Ellie Pavlick
Recent work has argued that large language models (LLMs) are not "abstract reasoners", citing their poor zero-shot performance on a variety of challenging tasks as evidence. We rev…
LLMs model how humans induce logically structured rules
Alyssa Loo, Ellie Pavlick, Roman Feiman
A central goal of cognitive science is to provide a computationally explicit account of both the structure of the mind and its development: what are the primitive representational…
How Do Vision-Language Models Process Conflicting Information Across Modalities?
Tianze Hua, Tian Yun, Ellie Pavlick
AI models are increasingly required to be multimodal, integrating disparate input streams into a coherent state representation on which subsequent behaviors and actions can be base…