Peter Clark
5 papers in the PaperMetrix corpus
Papers by this author
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Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning
2022 · arXiv (Cornell University)
Mathematical reasoning, a core ability of human intelligence, presents unique challenges for machines in abstract thinking and logical reasoning. Recent large pre-trained language models such as GPT-3 have achieved remarkable progress on mathematical reasoning tasks …
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Entailer: Answering Questions with Faithful and Truthful Chains of Reasoning
2022
Our goal is a question-answering (QA) system that can show how its answers are implied by its own internal beliefs via a systematic chain of reasoning. Such a capability would allow better understanding of why …
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ZebraLogic: On the Scaling Limits of LLMs for Logical Reasoning
2025 · arXiv (Cornell University)
We investigate the logical reasoning capabilities of large language models (LLMs) and their scalability in complex non-monotonic reasoning. To this end, we introduce ZebraLogic, a comprehensive evaluation framework for assessing LLM reasoning performance on logic …
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Complexity-Based Prompting for Multi-Step Reasoning
2022 · arXiv (Cornell University)
We study the task of prompting large-scale language models to perform multi-step reasoning. Existing work shows that when prompted with a chain of thoughts (CoT), sequences of short sentences describing intermediate reasoning steps towards a …
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Self-Refine: Iterative Refinement with Self-Feedback
2023 · arXiv (Cornell University)
Like humans, large language models (LLMs) do not always generate the best output on their first try. Motivated by how humans refine their written text, we introduce Self-Refine, an approach for improving initial outputs from …