EMNLP Findings2024
LaRS: Latent Reasoning Skills for Chain-of-Thought Reasoning
Zifan Xu, Haozhu Wang, Dmitriy Bespalov, Xian Wu, Peter Stone, Yanjun Qi
Abstract
Chain-of-thought (CoT) prompting is a popular in-context learning (ICL) approach for large language models (LLMs), especially when tackling complex reasoning tasks. Traditional
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Cited by top-tier papers4
- Hybrid Latent Reasoning via Reinforcement LearningZhenrui Yue, Bowen Jin, Huimin Zeng, Honglei Zhuang et al.NeurIPS 2025 · 28 citations
- The CoT Encyclopedia: Analyzing, Predicting, and Controlling how a Reasoning Model will ThinkSeongyun Lee, Seungone Kim, Minju Seo, Yongrae Jo et al.ICLR 2026 · 6 citations
- Your Reasoning Model Knows What Counts: Self-Guided Chain-of-Thought Pruning for Efficient ReasoningZi-Ao Ma, Xian-Ling Mao, Tian Lan, Chen Xu et al.ACL 2026
- CHOIR: Harmonizing Structured Persona Diversity for Robust Collaborative LLM ReasoningXiangjue Dong, Cong Wang, Maria Teleki, Millennium Bismay et al.ACL 2026
Builds on19
- Language Models are Few-Shot LearnersTom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah et al.NeurIPS 2020 · 64,255 citations
- Chain-of-Thought Prompting Elicits Reasoning in Large Language ModelsJason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma et al.NeurIPS 2022 · 22,562 citations
- Large Language Models are Zero-Shot ReasonersTakeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo et al.NeurIPS 2022 · 8,168 citations
- Deberta: decoding-Enhanced Bert with Disentangled AttentionPengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu ChenICLR 2021 · 3,729 citations
- Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order SensitivityYao Lu, Max Bartolo, Alastair Moore, Sebastian Riedel et al.ACL 2022 · 1,494 citations
Related papers
- Training Nonlinear Transformers for Chain-of-Thought Inference: A Theoretical Generalization AnalysisHongkang Li, Songtao Lu, Pin-Yu Chen, Xiaodong Cui et al.ICLR 2025
- Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What MattersBoshi Wang, Sewon Min, Xiang Deng, Jiaming Shen et al.ACL 2023 · 100 citations
- Why Prompt Design Matters and Works: A Complexity Analysis of Prompt Search Space in LLMsXiang Zhang, Juntai Cao, Chenyu You, Dujian DingACL 2025 · 21 citations
- Decomposed Prompting: A Modular Approach for Solving Complex TasksTushar Khot, Harsh Trivedi, Matthew Finlayson, Yao Fu et al.ICLR 2023 · 94 citations
- Unveiling Factual Recall Behaviors of Large Language Models through Knowledge NeuronsYifei Wang, Yuheng Chen, Wanting Wen, Yu Sheng et al.EMNLP 2024 · 3 citations
