3 papers
cs.AI2025
RefGrader: Automated Grading of Mathematical Competition Proofs using Agentic Workflows
Hamed Mahdavi, Pouria Mahdavinia, Samira Malek +7
State-of-the-art (SOTA) LLMs have progressed from struggling on proof-based Olympiad problems to solving most of the IMO 2025 problems, with leading systems reportedly handling 5 o…
cs.CL2025
ATLAS: Learning to Optimally Memorize the Context at Test Time
Ali Behrouz, Zeman Li, Praneeth Kacham +5
Transformers have been established as the most popular backbones in sequence modeling, mainly due to their effectiveness in in-context retrieval tasks and the ability to learn at s…
cs.AI2025
Brains vs. Bytes: Evaluating LLM Proficiency in Olympiad Mathematics
Hamed Mahdavi, Alireza Hashemi, Majid Daliri +6
Recent advances in large language models (LLMs) have shown impressive progress in mathematical reasoning tasks. However, current evaluation benchmarks predominantly focus on the ac…