2 citations · 3 across the 6 of their papers we have counts for
6 papers
Training AI Scientists to Replicate Research
Damon Falck, Samer Sabri, Anja Surina +8
The replicability of papers is a cornerstone of scientific knowledge, ensuring the reliability of existing results and providing a base for further experiments. The act of replicat…
Advancing Mathematics Research with AI-Driven Formal Proof Search
George Tsoukalas, Anton Kovsharov, Sergey Shirobokov +18
Large language models (LLMs) increasingly excel at mathematical reasoning, but their unreliability limits their utility in mathematics research. A mitigation is using LLMs to gener…
The Future of Facts: Tracing the Factual Generation-Verification Gap
Tim R. Davidson, Anja Surina, Caglar Gulcehre
Language models are becoming the default interface to factual knowledge, yet they often verify outputs more reliably than they generate them. This generation-verification gap (GV-g…
An Improved Last-Iterate Convergence Rate for Anchored Gradient Descent Ascent
Anja Surina, Arun Suggala, George Tsoukalas +5
We analyze the last-iterate convergence of the Anchored Gradient Descent Ascent algorithm for smooth convex-concave min-max problems. While previous work established a last-iterate…
Algorithm Discovery With LLMs: Evolutionary Search Meets Reinforcement Learning
Anja Surina, Amin Mansouri, Lars Quaedvlieg +4
Discovering efficient algorithms for solving complex problems has been an outstanding challenge in mathematics and computer science, requiring substantial human expertise over the…
The Role of Deep Learning Regularizations on Actors in Offline RL
Denis Tarasov, Anja Surina, Caglar Gulcehre
Deep learning regularization techniques, such as dropout, layer normalization, or weight decay, are widely adopted in the construction of modern artificial neural networks, often r…