8 papers
AIRA_2: Overcoming Bottlenecks in AI Research Agents
Karen Hambardzumyan, Nicolas Baldwin, Edan Toledo +22
Existing research has identified three structural performance bottlenecks in AI research agents: (1) synchronous single-GPU execution constrains sample throughput, limiting the ben…
APRES: An Agentic Paper Revision and Evaluation System
Bingchen Zhao, Jenny Zhang, Chenxi Whitehouse +8
Scientific discoveries must be communicated clearly to realize their full potential. Without effective communication, even the most groundbreaking findings risk being overlooked or…
AIRS-Bench: a Suite of Tasks for Frontier AI Research Science Agents
Alisia Lupidi, Bhavul Gauri, Thomas Simon Foster +34
LLM agents hold significant promise for advancing scientific research. To accelerate this progress, we introduce AIRS-Bench (the AI Research Science Benchmark), a suite of 20 tasks…
A Scalable Measure of Loss Landscape Curvature for Analyzing the Training Dynamics of LLMs
Dayal Singh Kalra, Jean-Christophe Gagnon-Audet, Andrey Gromov +4
Understanding the curvature evolution of the loss landscape is fundamental to analyzing the training dynamics of neural networks. The most commonly studied measure, Hessian sharpne…
What Does It Take to Be a Good AI Research Agent? Studying the Role of Ideation Diversity
Alexis Audran-Reiss, Jordi Armengol-Estapé, Karen Hambardzumyan +17
AI research agents offer the promise to accelerate scientific progress by automating the design, implementation, and training of machine learning models. However, the field is stil…
Scaling and Distilling Transformer Models for sEMG
Nicholas Mehlman, Jean-Christophe Gagnon-Audet, Michael Shvartsman +3
Surface electromyography (sEMG) signals offer a promising avenue for developing innovative human-computer interfaces by providing insights into muscular activity. However, the limi…