{"total":120,"rows":[{"id":"2212.09561","title":"Large Language Models are Better Reasoners with Self-Verification","created":"2022-12-19","cited_by_count":307,"area":"lr"},{"id":"2209.00840","title":"FOLIO: Natural Language Reasoning with First-Order Logic","created":"2022-09-02","cited_by_count":235,"area":"lr"},{"id":"2206.02336","title":"Making Large Language Models Better Reasoners with Step-Aware Verifier","created":"2022-06-06","cited_by_count":233,"area":"lr"},{"id":"2404.02078","title":"Advancing LLM Reasoning Generalists with Preference Trees","created":"2024-04-02","cited_by_count":192,"area":"lr"},{"id":"2309.15402","title":"Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and Future","created":"2023-09-27","cited_by_count":184,"area":"lr"},{"id":"2302.12246","title":"Active Prompting with Chain-of-Thought for Large Language Models","created":"2023-02-23","cited_by_count":154,"area":"lr"},{"id":"2503.05179","title":"Sketch-of-Thought: Efficient LLM Reasoning with Adaptive Cognitive-Inspired Sketching","created":"2025-03-07","cited_by_count":117,"area":"lr"},{"id":"2205.11502","title":"On the Paradox of Learning to Reason from Data","created":"2022-05-23","cited_by_count":93,"area":"lr"},{"id":"2503.00031","title":"Efficient Test-Time Scaling via Self-Calibration","created":"2025-02-25","cited_by_count":75,"area":"lr"},{"id":"2411.00855","title":"Vision-Language Models Can Self-Improve Reasoning via Reflection","created":"2024-10-30","cited_by_count":69,"area":"lr"},{"id":"2404.15522","title":"LogicBench: Towards Systematic Evaluation of Logical Reasoning Ability of Large Language Models","created":"2024-04-23","cited_by_count":68,"area":"lr"},{"id":"2306.09841","title":"Are Large Language Models Really Good Logical Reasoners? A Comprehensive Evaluation and Beyond","created":"2023-06-16","cited_by_count":65,"area":"lr"},{"id":"2303.14725","title":"Natural Language Reasoning, A Survey","created":"2023-03-26","cited_by_count":61,"area":"lr"},{"id":"2503.23077","title":"Efficient Inference for Large Reasoning Models: A Survey","created":"2025-03-29","cited_by_count":61,"area":"lr"},{"id":"2305.19555","title":"Large Language Models Are Not Strong Abstract Reasoners","created":"2023-05-31","cited_by_count":53,"area":"lr"},{"id":"2502.15652","title":"Empowering LLMs with Logical Reasoning: A Comprehensive Survey","created":"2025-02-21","cited_by_count":51,"area":"lr"},{"id":"2305.11499","title":"RCOT: Detecting and Rectifying Factual Inconsistency in Reasoning by Reversing Chain-of-Thought","created":"2023-05-19","cited_by_count":47,"area":"lr"},{"id":"2502.19411","title":"Code to Think, Think to Code: A Survey on Code-Enhanced Reasoning and Reasoning-Driven Code Intelligence in LLMs","created":"2025-02-26","cited_by_count":47,"area":"lr"},{"id":"2201.11473","title":"Reasoning Like Program Executors","created":"2022-01-27","cited_by_count":45,"area":"lr"},{"id":"2404.04735","title":"MACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems","created":"2024-04-06","cited_by_count":41,"area":"lr"},{"id":"2310.00836","title":"Towards LogiGLUE: A Brief Survey and A Benchmark for Analyzing Logical Reasoning Capabilities of Language Models","created":"2023-10-02","cited_by_count":35,"area":"lr"},{"id":"2408.00114","title":"Inductive or Deductive? Rethinking the Fundamental Reasoning Abilities of LLMs","created":"2024-07-31","cited_by_count":29,"area":"lr"},{"id":"2411.12498","title":"Enhancing Reasoning Capabilities of LLMs via Principled Synthetic Logic Corpus","created":"2024-11-19","cited_by_count":29,"area":"lr"},{"id":"2203.08480","title":"E-KAR: A Benchmark for Rationalizing Natural Language Analogical Reasoning","created":"2022-03-16","cited_by_count":28,"area":"lr"},{"id":"2312.02143","title":"Competition-Level Problems are Effective LLM Evaluators","created":"2023-12-04","cited_by_count":25,"area":"lr"},{"id":"2504.08672","title":"Genius: A Generalizable and Purely Unsupervised Self-Training Framework For Advanced Reasoning","created":"2025-04-11","cited_by_count":24,"area":"lr"},{"id":"2409.17539","title":"Logic-of-Thought: Injecting Logic into Contexts for Full Reasoning in Large Language Models","created":"2024-09-26","cited_by_count":23,"area":"lr"},{"id":"2203.00357","title":"MERIt: Meta-Path Guided Contrastive Learning for Logical Reasoning","created":"2022-03-01","cited_by_count":22,"area":"lr"},{"id":"2205.12598","title":"RobustLR: Evaluating Robustness to Logical Perturbation in Deductive Reasoning","created":"2022-05-25","cited_by_count":22,"area":"lr"},{"id":"2501.14851","title":"JustLogic: A Comprehensive Benchmark for Evaluating Deductive Reasoning in Large Language Models","created":"2025-01-24","cited_by_count":22,"area":"lr"},{"id":"2307.01640","title":"Chain of Thought Prompting Elicits Knowledge Augmentation","created":"2023-07-04","cited_by_count":21,"area":"lr"},{"id":"2505.15801","title":"VerifyBench: Benchmarking Reference-based Reward Systems for Large Language Models","created":"2025-05-21","cited_by_count":20,"area":"lr"},{"id":"2310.12342","title":"Eliminating Reasoning via Inferring with Planning: A New Framework to Guide LLMs' Non-linear Thinking","created":"2023-10-18","cited_by_count":19,"area":"lr"},{"id":"2408.15778","title":"LogicGame: Benchmarking Rule-Based Reasoning Abilities of Large Language Models","created":"2024-08-28","cited_by_count":19,"area":"lr"},{"id":"2410.02108","title":"ReGenesis: LLMs can Grow into Reasoning Generalists via Self-Improvement","created":"2024-10-03","cited_by_count":18,"area":"lr"},{"id":"2405.04086","title":"Optimizing Language Model's Reasoning Abilities with Weak Supervision","created":"2024-05-07","cited_by_count":15,"area":"lr"},{"id":"2409.12929","title":"LogicPro: Improving Complex Logical Reasoning via Program-Guided Learning","created":"2024-09-19","cited_by_count":14,"area":"lr"},{"id":"2310.09107","title":"GLoRE: Evaluating Logical Reasoning of Large Language Models","created":"2023-10-13","cited_by_count":13,"area":"lr"},{"id":"2503.13288","title":"$\\phi$-Decoding: Adaptive Foresight Sampling for Balanced Inference-Time Exploration and Exploitation","created":"2025-03-17","cited_by_count":13,"area":"lr"},{"id":"2404.04293","title":"Reason from Fallacy: Enhancing Large Language Models' Logical Reasoning through Logical Fallacy Understanding","created":"2024-04-04","cited_by_count":12,"area":"lr"},{"id":"2205.08794","title":"LogiGAN: Learning Logical Reasoning via Adversarial Pre-training","created":"2022-05-18","cited_by_count":11,"area":"lr"},{"id":"2410.02229","title":"CodePMP: Scalable Preference Model Pretraining for Large Language Model Reasoning","created":"2024-10-03","cited_by_count":10,"area":"lr"},{"id":"2205.10714","title":"Interpretable Proof Generation via Iterative Backward Reasoning","created":"2022-05-22","cited_by_count":9,"area":"lr"},{"id":"2410.07035","title":"PositionID: LLMs can Control Lengths, Copy and Paste with Explicit Positional Awareness","created":"2024-10-09","cited_by_count":9,"area":"lr"},{"id":"2505.13346","title":"J4R: Learning to Judge with Equivalent Initial State Group Relative Policy Optimization","created":"2025-05-19","cited_by_count":9,"area":"lr"},{"id":"2203.08992","title":"AdaLoGN: Adaptive Logic Graph Network for Reasoning-Based Machine Reading Comprehension","created":"2022-03-16","cited_by_count":8,"area":"lr"},{"id":"2205.00731","title":"Logiformer: A Two-Branch Graph Transformer Network for Interpretable Logical Reasoning","created":"2022-05-02","cited_by_count":8,"area":"lr"},{"id":"2305.13718","title":"Exploring Self-supervised Logic-enhanced Training for Large Language Models","created":"2023-05-23","cited_by_count":8,"area":"lr"},{"id":"2306.04031","title":"Certified Deductive Reasoning with Language Models","created":"2023-06-06","cited_by_count":8,"area":"lr"},{"id":"2310.05450","title":"Empower Nested Boolean Logic via Self-Supervised Curriculum Learning","created":"2023-10-09","cited_by_count":7,"area":"lr"},{"id":"2311.17438","title":"CLOMO: Counterfactual Logical Modification with Large Language Models","created":"2023-11-29","cited_by_count":7,"area":"lr"},{"id":"2401.05787","title":"Chain of Evidences and Evidence to Generate: Prompting for Context Grounded and Retrieval Augmented Reasoning","created":"2024-01-11","cited_by_count":7,"area":"lr"},{"id":"2505.11854","title":"Evaluating the Logical Reasoning Abilities of Large Reasoning Models","created":"2025-05-17","cited_by_count":7,"area":"lr"},{"id":"2511.01365","title":"The Ouroboros of Benchmarking: Reasoning Evaluation in an Era of Saturation","created":"2025-11-03","cited_by_count":7,"area":"lr"},{"id":"2410.21779","title":"Leveraging LLMs for Hypothetical Deduction in Logical Inference: A Neuro-Symbolic Approach","created":"2024-10-29","cited_by_count":6,"area":"lr"},{"id":"2504.02810","title":"Generative Evaluation of Complex Reasoning in Large Language Models","created":"2025-04-03","cited_by_count":6,"area":"lr"},{"id":"2505.17225","title":"Reasoning Model is Stubborn: Diagnosing Instruction Overriding in Reasoning Models","created":"2025-05-22","cited_by_count":6,"area":"lr"},{"id":"2512.12008","title":"Hold Onto That Thought: Assessing KV Cache Compression On Reasoning","created":"2025-12-12","cited_by_count":6,"area":"lr"},{"id":"2212.09282","title":"APOLLO: A Simple Approach for Adaptive Pretraining of Language Models for Logical Reasoning","created":"2022-12-19","cited_by_count":5,"area":"lr"},{"id":"2401.05190","title":"DCR: Divide-and-Conquer Reasoning for Multi-choice Question Answering with LLMs","created":"2024-01-10","cited_by_count":5,"area":"lr"},{"id":"2502.16428","title":"Visual Reasoning Evaluation of Grok, Deepseek Janus, Gemini, Qwen, Mistral, and ChatGPT","created":"2025-02-23","cited_by_count":5,"area":"lr"},{"id":"2506.04575","title":"Are LLMs Stable Formal Logic Translators in Logical Reasoning Across Linguistically Diversified Texts?","created":"2025-06-05","cited_by_count":5,"area":"lr"},{"id":"2301.08913","title":"Unifying Structure Reasoning and Language Model Pre-training for Complex Reasoning","created":"2023-01-21","cited_by_count":4,"area":"lr"},{"id":"2404.07017","title":"Improving Language Model Reasoning with Self-motivated Learning","created":"2024-04-10","cited_by_count":4,"area":"lr"},{"id":"2503.05891","title":"MastermindEval: A Simple But Scalable Reasoning Benchmark","created":"2025-03-07","cited_by_count":4,"area":"lr"},{"id":"2505.09825","title":"KRISTEVA: Close Reading as a Novel Task for Benchmarking Interpretive Reasoning","created":"2025-05-14","cited_by_count":4,"area":"lr"},{"id":"2505.15712","title":"TurnaboutLLM: A Deductive Reasoning Benchmark from Detective Games","created":"2025-05-21","cited_by_count":4,"area":"lr"},{"id":"2508.01533","title":"ReasonAct: Progressive Training for Fine-Grained Video Reasoning in Small Models","created":"2025-08-03","cited_by_count":4,"area":"lr"},{"id":"2601.08134","title":"How Reliable are Confidence Estimators for Large Reasoning Models? A Systematic Benchmark on High-Stakes Domains","created":"2026-01-13","cited_by_count":4,"area":"lr"},{"id":"2210.11265","title":"Disentangling Reasoning Capabilities from Language Models with Compositional Reasoning Transformers","created":"2022-10-20","cited_by_count":3,"area":"lr"},{"id":"2210.12487","title":"MetaLogic: Logical Reasoning Explanations with Fine-Grained Structure","created":"2022-10-22","cited_by_count":3,"area":"lr"},{"id":"2306.15273","title":"IDOL: Indicator-oriented Logic Pre-training for Logical Reasoning","created":"2023-06-27","cited_by_count":3,"area":"lr"},{"id":"2404.18130","title":"Logic Agent: Enhancing Validity with Logic Rule Invocation","created":"2024-04-28","cited_by_count":3,"area":"lr"},{"id":"2405.11880","title":"Quantifying In-Context Reasoning Effects and Memorization Effects in LLMs","created":"2024-05-20","cited_by_count":3,"area":"lr"},{"id":"2409.14495","title":"Thought-Path Contrastive Learning via Premise-Oriented Data Augmentation for Logical Reading Comprehension","created":"2024-09-22","cited_by_count":3,"area":"lr"},{"id":"2509.18458","title":"CogniLoad: A Synthetic Natural Language Reasoning Benchmark With Tunable Length, Intrinsic Difficulty, and Distractor Density","created":"2025-09-22","cited_by_count":3,"area":"lr"},{"id":"2601.12444","title":"Large Language Model for OWL Proofs","created":"2026-01-18","cited_by_count":3,"area":"lr"},{"id":"2603.29500","title":"Learning to Generate Formally Verifiable Step-by-Step Logic Reasoning via Structured Formal Intermediaries","created":"2026-03-31","cited_by_count":3,"area":"lr"},{"id":"2207.01450","title":"Discourse-Aware Graph Networks for Textual Logical Reasoning","created":"2022-07-04","cited_by_count":2,"area":"lr"},{"id":"2301.02983","title":"Mind Reasoning Manners: Enhancing Type Perception for Generalized Zero-shot Logical Reasoning over Text","created":"2023-01-08","cited_by_count":2,"area":"lr"},{"id":"2302.05963","title":"Analyzing the Effectiveness of the Underlying Reasoning Tasks in Multi-hop Question Answering","created":"2023-02-12","cited_by_count":2,"area":"lr"},{"id":"2305.14569","title":"Few-shot Unified Question Answering: Tuning Models or Prompts?","created":"2023-05-23","cited_by_count":2,"area":"lr"},{"id":"2312.11720","title":"Assessing Logical Reasoning Capabilities of Encoder-Only Transformer Models","created":"2023-12-18","cited_by_count":2,"area":"lr"},{"id":"2410.08437","title":"Autonomous Evaluation of LLMs for Truth Maintenance and Reasoning Tasks","created":"2024-10-11","cited_by_count":2,"area":"lr"},{"id":"2505.14684","title":"Mind the Gap: Bridging Thought Leap for Improved Chain-of-Thought Tuning","created":"2025-05-20","cited_by_count":2,"area":"lr"},{"id":"2510.11031","title":"LogiNumSynth: Synthesizing Joint Logical-Numerical Reasoning Problems for Language Models","created":"2025-10-13","cited_by_count":2,"area":"lr"},{"id":"2601.18595","title":"A Balanced Neuro-Symbolic Approach for Commonsense Abductive Logic","created":"2026-01-26","cited_by_count":2,"area":"lr"},{"id":"2306.12069","title":"Modeling Hierarchical Reasoning Chains by Linking Discourse Units and Key Phrases for Reading Comprehension","created":"2023-06-21","cited_by_count":1,"area":"lr"},{"id":"2405.19109","title":"PathReasoner: Modeling Reasoning Path with Equivalent Extension for Logical Question Answering","created":"2024-05-29","cited_by_count":1,"area":"lr"},{"id":"2507.00092","title":"Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models","created":"2025-06-30","cited_by_count":1,"area":"lr"},{"id":"2510.21853","title":"Policy Optimization Prefers The Path of Least Resistance","created":"2025-10-22","cited_by_count":1,"area":"lr"},{"id":"2601.15482","title":"Martingale Foresight Sampling: A Principled Approach to Inference-Time LLM Decoding","created":"2026-01-21","cited_by_count":1,"area":"lr"},{"id":"2602.02863","title":"\"I May Not Have Articulated Myself Clearly\": Diagnosing Dynamic Instability in LLM Reasoning at Inference Time","created":"2026-02-02","cited_by_count":1,"area":"lr"},{"id":"2602.12665","title":"Evaluating Robustness of Reasoning Models on Parameterized Logical Problems","created":"2026-02-13","cited_by_count":1,"area":"lr"},{"id":"2602.21044","title":"LogicGraph : Benchmarking Multi-Path Logical Reasoning via Neuro-Symbolic Generation and Verification","created":"2026-02-24","cited_by_count":1,"area":"lr"},{"id":"2603.17169","title":"How Clued up are LLMs? Evaluating Multi-Step Deductive Reasoning in a Text-Based Game Environment","created":"2026-03-17","cited_by_count":1,"area":"lr"},{"id":"2605.02442","title":"Measuring AI Reasoning: A Guide for Researchers","created":"2026-05-04","cited_by_count":1,"area":"lr"},{"id":"2605.06444","title":"SCRuB: Social Concept Reasoning under Rubric-Based Evaluation","created":"2026-05-07","cited_by_count":1,"area":"lr"},{"id":"2605.28247","title":"IRDS: Interpretable RLVR Data Selection via Verifier-Coupled Sparse Autoencoder Coverage","created":"2026-05-27","cited_by_count":1,"area":"lr"},{"id":"2606.05025","title":"Invariant Gradient Alignment for Robust Reasoning Distillation","created":"2026-06-03","cited_by_count":1,"area":"lr"}],"next_cursor":"100"}