Who cites «STaR: Bootstrapping Reasoning With Reasoning» · page 3

585 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. ← the card

Kimi K2: Open Agentic Intelligence — 2025 · arXiv:2507.20534
LEMMA: Learning from Errors for MatheMatical Advancement in LLMs — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
LLM-Friendly Knowledge Representation for Customer Support — 2025 · Proceedings of the 31st International Conference on Computational Linguistics: Industry Track
LLMs Can Easily Learn to Reason from Demonstrations Structure, not content, is what matters! — 2025 · arXiv:2502.07374
LTRAG: Enhancing Autoformalization and Self-refinement for Logical Reasoning with Thought-Guided RAG — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
Language Models Can Easily Learn to Reason from Demonstrations — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
Language Models as Continuous Self-Evolving Data Engineers — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Language models can learn implicit multi-hop reasoning, but only if they have lots of training data — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Large Language Models as an Indirect Reasoner: Contrapositive and Contradiction for Automated Reasoning — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
Learning from Committee: Reasoning Distillation from a Mixture of Teachers with Peer-Review — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
Learning to Reason via Self-Iterative Process Feedback for Small Language Models — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
Learning to Reason without External Rewards — 2025 · arXiv:2505.19590
Leveraging Large Language Models for Bengali Math Word Problem Solving with Chain of Thought Reasoning — 2025 · arXiv:2505.21354
Logic-of-Thought: Injecting Logic into Contexts for Full Reasoning in Large Language Models — 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
MARGE: Improving Math Reasoning for LLMs with Guided Exploration — 2025 · arXiv:2505.12500
MetaLadder: Ascending Mathematical Solution Quality via Analogical-Problem Reasoning Transfer — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
Metastable Dynamics of Chain-of-Thought Reasoning: Provable Benefits of Search, RL and Distillation — 2025 · arXiv:2502.01694
Mining Hidden Thoughts from Texts: Evaluating Continual Pretraining with Synthetic Data for LLM Reasoning — 2025 · arXiv:2505.10182
Mitigating Tail Narrowing in LLM Self-Improvement via Socratic-Guided Sampling — 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
Monitoring Reasoning Models for Misbehavior and the Risks of Promoting Obfuscation — 2025 · arXiv:2503.11926
NL-Debugging: Exploiting Natural Language as an Intermediate Representation for Code Debugging — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention — 2025 · arXiv:2502.11089
NaturalReasoning: Reasoning in the Wild with 2.8M Challenging Questions — 2025 · arXiv:2502.13124
Offline Learning and Forgetting for Reasoning with Large Language Models — 2025 · arXiv:2504.11364
Offline Reinforcement Learning for LLM Multi-step Reasoning — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
On Memorization of Large Language Models in Logical Reasoning — 2025 · Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics
One More Question is Enough, Expert Question Decomposition (EQD) Model for Domain Quantitative Reasoning — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
Optima: Optimizing Effectiveness and Efficiency for LLM-Based Multi-Agent System — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
PAG: Multi-Turn Reinforced LLM Self-Correction with Policy as Generative Verifier — 2025 · arXiv:2506.10406
PORT: Preference Optimization on Reasoning Traces — 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
POSITION BIAS MITIGATES POSITION BIAS: Mitigate Position Bias Through Inter-Position Knowledge Distillation — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Physics Reasoner: Knowledge-Augmented Reasoning for Solving Physics Problems with Large Language Models — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
PrismRAG: Boosting RAG Factuality with Distractor Resilience and Strategized Reasoning — 2025 · arXiv:2507.18857
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models — 2025 · arXiv:2505.24864
Progressive Multimodal Reasoning via Active Retrieval — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Propose, Solve, Verify: Self-Play Through Formal Verification — 2025 · arXiv:2512.18160
QCRD: Quality-guided Contrastive Rationale Distillation for Large Language Models — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learning — 2025 · arXiv:2504.20073
RAcQUEt: Unveiling the Dangers of Overlooked Referential Ambiguity in Visual LLMs — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
ReFLAIR: Enhancing Multimodal Reasoning via Structured Reflection and Reward-Guided Learning — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning — 2025 · arXiv:2503.19470
ReSpAct: Harmonizing Reasoning, Speaking, and Acting Towards Building Large Language Model-Based Conversational AI Agents — 2025 · Proceedings of the 15th International Workshop on Spoken Dialogue Systems Technology
Reasoning Aware Self-Consistency: Leveraging Reasoning Paths for Efficient LLM Sampling — 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
Reasoning Models Can Be Effective Without Thinking — 2025 · arXiv:2504.09858
ReflectEvo: Improving Meta Introspection of Small LLMs by Learning Self-Reflection — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
Reflective Agreement: Combining Self-Mixture of Agents with a Sequence Tagger for Robust Event Extraction — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Reinforcement Learning for Reasoning in Small LLMs: What Works and What Doesn''t — 2025 · arXiv:2503.16219
Reinforcement Learning vs. Distillation: Understanding Accuracy and Capability in LLM Reasoning — 2025 · arXiv:2505.14216
Relevant or Random: Can LLMs Truly Perform Analogical Reasoning? — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
Replacing thinking with tool usage enables reasoning in small language models — 2025 · arXiv:2507.05065
Rethinking Fine-Tuning when Scaling Test-Time Compute: Limiting Confidence Improves Mathematical Reasoning — 2025 · arXiv:2502.07154
Reverse Thinking Makes LLMs Stronger Reasoners — 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
Revisiting LLMs as Zero-Shot Time Series Forecasters: Small Noise Can Break Large Models — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
Revisiting Test-Time Scaling: A Survey and a Diversity-Aware Method for Efficient Reasoning — 2025 · arXiv:2506.04611
S$^2$-MAD: Breaking the Token Barrier to Enhance Multi-Agent Debate Efficiency — 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
SAND: Boosting LLM Agents with Self-Taught Action Deliberation — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
SATBench: Benchmarking LLMs'' Logical Reasoning via Automated Puzzle Generation from SAT Formulas — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training — 2025 · arXiv:2501.17161
SGIC: A Self-Guided Iterative Calibration Framework for RAG — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
SIFT: Grounding LLM Reasoning in Contexts via Stickers — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
SOCIAL SCAFFOLDS: A Generalization Framework for Social Understanding Tasks — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
STA-CoT: Structured Target-Centric Agentic Chain-of-Thought for Consistent Multi-Image Geological Reasoning — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
STORM-BORN: A Challenging Mathematical Derivations Dataset Curated via a Human-in-the-Loop Multi-Agent Framework — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
STaR-SQL: Self-Taught Reasoner for Text-to-SQL — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
SaRO: Enhancing LLM Safety through Reasoning-based Alignment — 2025 · arXiv:2504.09420
Safe: Enhancing Mathematical Reasoning in Large Language Models via Retrospective Step-aware Formal Verification — 2025 · arXiv:2506.04592
Satori: Reinforcement Learning with Chain-of-Action-Thought Enhances LLM Reasoning via Autoregressive Search — 2025 · arXiv:2502.02508
Scalable Complexity Control Facilitates Reasoning Ability of LLMs — 2025 · arXiv:2505.23013
Scaling Test-Time Compute Without Verification or RL is Suboptimal — 2025 · arXiv:2502.12118
Self-Correcting Code Generation Using Small Language Models — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
Self-Enhanced Reasoning Training: Activating Latent Reasoning in Small Models for Enhanced Reasoning Distillation — 2025 · arXiv:2502.12744
Self-Evolving Curriculum for LLM Reasoning — 2025 · arXiv:2505.14970
Self-Filtered Distillation with LLMs-generated Trust Indicators for Reliable Patent Classification — 2025 · arXiv:2510.05431
Self-Improving Transformers Overcome Easy-to-Hard and Length Generalization Challenges — 2025 · arXiv:2502.01612
Self-Taught Agentic Long Context Understanding — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Self-Taught Self-Correction for Small Language Models — 2025 · arXiv:2503.08681
Self-Training Elicits Concise Reasoning in Large Language Models — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
Self-Training Large Language Models for Tool-Use Without Demonstrations — 2025 · Findings of the Association for Computational Linguistics: NAACL 2025
Self-Training Large Language Models with Confident Reasoning — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
Self-Training Meets Consistency: Improving LLMs'' Reasoning with Consistency-Driven Rationale Evaluation — 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
Small Models Struggle to Learn from Strong Reasoners — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
Sparse Rewards Can Self-Train Dialogue Agents — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
Step-KTO: Optimizing Mathematical Reasoning through Stepwise Binary Feedback — 2025 · Proceedings of The 3rd Workshop on Mathematical Natural Language Processing (MathNLP 2025)
Superficial Self-Improved Reasoners Benefit from Model Merging — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Syzygy of Thoughts: Improving LLM CoT with the Minimal Free Resolution — 2025 · arXiv:2504.09566
T1: Advancing Language Model Reasoning through Reinforcement Learning and Inference Scaling — 2025 · arXiv:2501.11651
TRACT: Regression-Aware Fine-tuning Meets Chain-of-Thought Reasoning for LLM-as-a-Judge — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Teach Small Models to Reason by Curriculum Distillation — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Teaching LLMs to Plan, Not Just Solve: Plan Learning Boosts LLMs Generalization in Reasoning Tasks — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
TestNUC: Enhancing Test-Time Computing Approaches and Scaling through Neighboring Unlabeled Data Consistency — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity — 2025 · arXiv:2506.06941
The Quest for Efficient Reasoning: A Data-Centric Benchmark to CoT Distillation — 2025 · arXiv:2505.18759
The Race to Efficiency: A New Perspective on AI Scaling Laws — 2025 · arXiv:2501.02156
The Self-Improvement Paradox: Can Language Models Bootstrap Reasoning Capabilities without External Scaffolding? — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
Theorem Prover as a Judge for Synthetic Data Generation — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Theoretical Physics Benchmark (TPBench) -- a Dataset and Study of AI Reasoning Capabilities in Theoretical Physics — 2025 · arXiv:2502.15815
Think Clearly: Improving Reasoning via Redundant Token Pruning — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
Think Right, Not More: Test-Time Scaling for Numerical Claim Verification — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
Thinking Before You Speak: A Proactive Test-time Scaling Approach — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025