35 citations · 71 across the 23 of their papers we have counts for
7 papers · 1 filter
Learning Linear Attention in Polynomial Time
Morris Yau, Ekin Akyürek, Jiayuan Mao +3
Previous research has explored the computational expressivity of Transformer models in simulating Boolean circuits or Turing machines. However, the learnability of these simulators…
Can Large Language Models Understand Symbolic Graphics Programs?
Zeju Qiu, Weiyang Liu, Haiwen Feng +7
Against the backdrop of enthusiasm for large language models (LLMs), there is a growing need to scientifically assess their capabilities and shortcomings. This is nontrivial in par…
Evaluating Large Vision-and-Language Models on Children's Mathematical Olympiads
Anoop Cherian, Kuan-Chuan Peng, Suhas Lohit +3
Recent years have seen a significant progress in the general-purpose problem solving abilities of large vision and language models (LVLMs), such as ChatGPT, Gemini, etc.; some of t…
Representational Alignment Supports Effective Machine Teaching
Ilia Sucholutsky, Katherine M. Collins, Maya Malaviya +11
A good teacher should not only be knowledgeable, but should also be able to communicate in a way that the student understands -- to share the student's representation of the world.…
LLM and Simulation as Bilevel Optimizers: A New Paradigm to Advance Physical Scientific Discovery
Pingchuan Ma, Tsun-Hsuan Wang, Minghao Guo +5
Large Language Models have recently gained significant attention in scientific discovery for their extensive knowledge and advanced reasoning capabilities. However, they encounter…
How to guess a gradient
Utkarsh Singhal, Brian Cheung, Kartik Chandra +4
How much can you say about the gradient of a neural network without computing a loss or knowing the label? This may sound like a strange question: surely the answer is "very little…
What Planning Problems Can A Relational Neural Network Solve?
Jiayuan Mao, Tomás Lozano-Pérez, Joshua B. Tenenbaum +1
Goal-conditioned policies are generally understood to be "feed-forward" circuits, in the form of neural networks that map from the current state and the goal specification to the n…