Parsel: A Unified Natural Language Framework for Algorithmic Reasoning

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LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code (2024, methodology): “Methods such as AlphaCode (Li et al., 2022), AlphaCode 2(Gemini Team et al., 2023), ALGO (Zhang et al., 2023d), Parsel (Zelikman et al., 2022), code cleaning (Jain et al., 2023), code explainations (Li et al., 2023a), analogical reasoning (Yasunaga et al., 2023), and AlphaCodium (Ridnik et al.,…”
Self-Collaboration Code Generation via ChatGPT (2023, unknown): “The work [Zelikman et al., 2022] applied LLMs to code generation and demonstrated significant improvement in the pass rate of generated complex programs.”
Text2Motion: from natural language instructions to feasible plans (2023, background): “Tangential works shift the planning medium from natural language to code [38, 51, 57] and embeds task queries, robot actions, solution samples, and fallback behaviors as programs in the prompt.”
Large Language Models as Analogical Reasoners (2023, background): “Several studies have extended this approach with more structured algorithms and search methods (Khot et al., 2022; Drozdov et al., 2022; Zelikman et al., 2022; Yao et al., 2023; Press et al., 2022; Khattab et al., 2022; Jung et al., 2022), as well as longer-horizon action and planning (Yao et al.,…”