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cs.CL2024
Lost in the Logic: An Evaluation of Large Language Models' Reasoning Capabilities on LSAT Logic Games
Saumya Malik
In this thesis, I evaluate the performance of Large Language Models (LLMs) on the Law School Admissions Test (LSAT), specifically the Logic Games section of the test. I focus on th…
cs.CL2024
QuRating: Selecting High-Quality Data for Training Language Models
Alexander Wettig, Aatmik Gupta, Saumya Malik +1
Selecting high-quality pre-training data is important for creating capable language models, but existing methods rely on simple heuristics. We introduce QuRating, a method for sele…