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cs.CL2025
Self-supervised Analogical Learning using Language Models
Ben Zhou, Sarthak Jain, Yi Zhang +4
Large language models have been shown to suffer from reasoning inconsistency issues. That is, they fail more in situations unfamiliar to the training data, even though exact or ver…
cs.CL2024
MMLU-SR: A Benchmark for Stress-Testing Reasoning Capability of Large Language Models
Wentian Wang, Sarthak Jain, Paul Kantor +3
We propose MMLU-SR, a novel dataset designed to measure the true comprehension abilities of Large Language Models (LLMs) by challenging their performance in question-answering task…