3 papers
cs.CL2025
Putnam-AXIOM: A Functional and Static Benchmark for Measuring Higher Level Mathematical Reasoning in LLMs
Aryan Gulati, Brando Miranda, Eric Chen +5
Current mathematical reasoning benchmarks for large language models (LLMs) are approaching saturation, with some achieving > 90% accuracy, and are increasingly compromised by train…
cs.LG2024
Out-of-Distribution Detection through Soft Clustering with Non-Negative Kernel Regression
Aryan Gulati, Xingjian Dong, Carlos Hurtado +3
As language models become more general purpose, increased attention needs to be paid to detecting out-of-distribution (OOD) instances, i.e., those not belonging to any of the distr…
cs.LG2024
An Evaluation Benchmark for Autoformalization in Lean4
Aryan Gulati, Devanshu Ladsaria, Shubhra Mishra +2
Large Language Models (LLMs) hold the potential to revolutionize autoformalization. The introduction of Lean4, a mathematical programming language, presents an unprecedented opport…