most citedBrokenMath: A Benchmark for Sycophancy in Theorem Proving with LLMs

3 citations · 3 across the 1 of their papers we have counts for

collaborators

6 papers

cs.AI20253 cited

BrokenMath: A Benchmark for Sycophancy in Theorem Proving with LLMs

Ivo Petrov, Jasper Dekoninck, Martin Vechev

Large language models (LLMs) have recently shown strong performance on mathematical benchmarks. At the same time, they are prone to hallucination and sycophancy, often providing co…

cs.CL2025

The Open Proof Corpus: A Large-Scale Study of LLM-Generated Mathematical Proofs

Jasper Dekoninck, Ivo Petrov, Kristian Minchev +13

In recent months, large language models (LLMs) have made significant progress in mathematical proof generation, but further advancement is hindered by the lack of a large-scale, hi…

cs.AI2025

MathArena: Evaluating LLMs on Uncontaminated Math Competitions

Mislav Balunović, Jasper Dekoninck, Ivo Petrov +2

The rapid advancement of reasoning capabilities in large language models (LLMs) has led to notable improvements on mathematical benchmarks. However, many of the most commonly used…

cs.LG2025

GRAIN: Exact Graph Reconstruction from Gradients

Maria Drencheva, Ivo Petrov, Maximilian Baader +2

Federated learning claims to enable collaborative model training among multiple clients with data privacy by transmitting gradient updates instead of the actual client data. Howeve…

cs.CL2025

Proof or Bluff? Evaluating LLMs on 2025 USA Math Olympiad

Ivo Petrov, Jasper Dekoninck, Lyuben Baltadzhiev +5

Recent math benchmarks for large language models (LLMs) such as MathArena indicate that state-of-the-art reasoning models achieve impressive performance on mathematical competition…

cs.AI2025

MathConstruct: Challenging LLM Reasoning with Constructive Proofs

Mislav Balunović, Jasper Dekoninck, Nikola Jovanović +2

While Large Language Models (LLMs) demonstrate impressive performance in mathematics, existing math benchmarks come with significant limitations. Many focus on problems with fixed…