Cited by: Self-Consistency Improves Chain of Thought Reasoning in Language Models

27 citation edges inside this catalog. A title match is weaker evidence than an identifier match. Zero entries does not mean no citations on the web.

• Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP
  arxiv:2212.14024 · evidence: id
• Multimodal Chain-of-Thought Reasoning in Language Models
  arxiv:2302.00923 · evidence: title
• Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution
  arxiv:2309.16797 · evidence: id
• Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine
  arxiv:2311.16452 · evidence: title
• Language Agents as Optimizable Graphs
  arxiv:2402.16823 · evidence: id
• Automated Design of Agentic Systems
  arxiv:2408.08435 · evidence: title
• Gödel Agent: A Self-Referential Agent Framework for Recursive Self-Improvement
  arxiv:2410.04444 · evidence: id
• Scaling of Search and Learning: A Roadmap to Reproduce o1 from Reinforcement Learning Perspective
  arxiv:2412.14135 · evidence: title
• rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking
  arxiv:2501.04519 · evidence: title
• Communicating Activations Between Language Model Agents
  arxiv:2501.14082 · evidence: id
• LIMO: Less is More for Reasoning
  arxiv:2502.03387 · evidence: id
• LADDER: Self-Improving LLMs Through Recursive Problem Decomposition
  arxiv:2503.00735 · evidence: title
• The First Few Tokens Are All You Need: An Efficient and Effective Unsupervised Prefix Fine-Tuning Method for Reasoning Models
  arxiv:2503.02875 · evidence: title
• TTRL: Test-Time Reinforcement Learning
  arxiv:2504.16084 · evidence: id
• The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning
  arxiv:2505.15134 · evidence: id
• Can Large Reasoning Models Self-Train?
  arxiv:2505.21444 · evidence: title
• Curriculum Reinforcement Learning from Easy to Hard Tasks Improves LLM Reasoning
  arxiv:2506.06632 · evidence: title
• CDE: Curiosity-Driven Exploration for Efficient Reinforcement Learning in Large Language Models
  arxiv:2509.09675 · evidence: id
• Single-stream Policy Optimization
  arxiv:2509.13232 · evidence: title
• Compute as Teacher: Turning Inference Compute Into Reference-Free Supervision
  arxiv:2509.14234 · evidence: title
• SIM-CoT: Supervised Implicit Chain-of-Thought
  arxiv:2509.20317 · evidence: title
• Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering
  arxiv:2604.08224 · evidence: title
• Structured Scaling of AI Discovery Across Diverse Scientific Domains
  arxiv:2604.19341 · evidence: title
• Reliable Chain-of-Thought via Prefix Consistency
  arxiv:2605.07654 · evidence: title