{"total":42,"rows":[{"id":"2305.11738","title":"CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing","created":"2023-05-19","cited_by_count":783,"area":"lr"},{"id":"2308.03188","title":"Automatically Correcting Large Language Models: Surveying the landscape of diverse self-correction strategies","created":"2023-08-06","cited_by_count":238,"area":"lr"},{"id":"2511.08325","title":"AgentPRM: Process Reward Models for LLM Agents via Step-Wise Promise and Progress","created":"2025-11-11","cited_by_count":77,"area":"lr"},{"id":"2503.24370","title":"Effectively Controlling Reasoning Models through Thinking Intervention","created":"2025-03-31","cited_by_count":65,"area":"lr"},{"id":"2311.08719","title":"Think-in-Memory: Recalling and Post-thinking Enable LLMs with Long-Term Memory","created":"2023-11-15","cited_by_count":64,"area":"lr"},{"id":"2309.15028","title":"Don't throw away your value model! Generating more preferable text with Value-Guided Monte-Carlo Tree Search decoding","created":"2023-09-26","cited_by_count":60,"area":"lr"},{"id":"2505.13308","title":"Seek in the Dark: Reasoning via Test-Time Instance-Level Policy Gradient in Latent Space","created":"2025-05-19","cited_by_count":43,"area":"lr"},{"id":"2412.15797","title":"Ensembling Large Language Models with Process Reward-Guided Tree Search for Better Complex Reasoning","created":"2024-12-20","cited_by_count":40,"area":"lr"},{"id":"2501.02497","title":"A Survey of Test-Time Compute: From Intuitive Inference to Deliberate Reasoning","created":"2025-01-05","cited_by_count":40,"area":"lr"},{"id":"2305.14934","title":"GRACE: Discriminator-Guided Chain-of-Thought Reasoning","created":"2023-05-24","cited_by_count":35,"area":"lr"},{"id":"2307.02768","title":"Training Models to Generate, Recognize, and Reframe Unhelpful Thoughts","created":"2023-07-06","cited_by_count":31,"area":"lr"},{"id":"2301.00355","title":"Second Thoughts are Best: Learning to Re-Align With Human Values from Text Edits","created":"2023-01-01","cited_by_count":27,"area":"lr"},{"id":"2502.13943","title":"AdaptiveStep: Automatically Dividing Reasoning Step through Model Confidence","created":"2025-02-19","cited_by_count":24,"area":"lr"},{"id":"2503.22048","title":"ThinkEdit: Interpretable Weight Editing to Mitigate Overly Short Thinking in Reasoning Models","created":"2025-03-27","cited_by_count":17,"area":"lr"},{"id":"2507.13255","title":"Automating Steering for Safe Multimodal Large Language Models","created":"2025-07-17","cited_by_count":17,"area":"lr"},{"id":"2409.14026","title":"Uncovering Latent Chain of Thought Vectors in Language Models","created":"2024-09-21","cited_by_count":14,"area":"lr"},{"id":"2510.03595","title":"Decoupling Task-Solving and Output Formatting in LLM Generation","created":"2025-10-04","cited_by_count":9,"area":"lr"},{"id":"2504.18535","title":"TRACE Back from the Future: A Probabilistic Reasoning Approach to Controllable Language Generation","created":"2025-04-25","cited_by_count":8,"area":"lr"},{"id":"2407.21531","title":"Can LLMs \"Reason\" in Music? An Evaluation of LLMs' Capability of Music Understanding and Generation","created":"2024-07-31","cited_by_count":7,"area":"lr"},{"id":"2507.08390","title":"Inference-Time Scaling of Diffusion Language Models via Trajectory Refinement","created":"2025-07-11","cited_by_count":7,"area":"lr"},{"id":"2502.20684","title":"JAM: Controllable and Responsible Text Generation via Causal Reasoning and Latent Vector Manipulation","created":"2025-02-28","cited_by_count":5,"area":"lr"},{"id":"2209.08750","title":"Knowledge-based Analogical Reasoning in Neuro-symbolic Latent Spaces","created":"2022-09-19","cited_by_count":4,"area":"lr"},{"id":"2602.01849","title":"Self-Rewarding Sequential Monte Carlo for Masked Diffusion Language Models","created":"2026-02-02","cited_by_count":4,"area":"lr"},{"id":"2509.22510","title":"We Think, Therefore We Align LLMs to Helpful, Harmless and Honest Before They Go Wrong","created":"2025-09-26","cited_by_count":3,"area":"lr"},{"id":"2402.08498","title":"\"Reasoning\" with Rhetoric: On the Style-Evidence Tradeoff in LLM-Generated Counter-Arguments","created":"2024-02-13","cited_by_count":2,"area":"lr"},{"id":"2502.10411","title":"TrueReason: An Exemplar Personalised Learning System Integrating Reasoning with Foundational Models","created":"2025-01-23","cited_by_count":2,"area":"lr"},{"id":"2502.12776","title":"Portable Reward Tuning: Towards Reusable Fine-Tuning across Different Pretrained Models","created":"2025-02-18","cited_by_count":2,"area":"lr"},{"id":"2511.19131","title":"Eliciting Chain-of-Thought in Base LLMs via Gradient-Based Representation Optimization","created":"2025-11-24","cited_by_count":2,"area":"lr"},{"id":"2512.17206","title":"Reasoning Palette: Modulating Reasoning via Latent Contextualization for Controllable Exploration for (V)LMs","created":"2025-12-19","cited_by_count":2,"area":"lr"},{"id":"2602.20528","title":"Stop-Think-AutoRegress: Language Modeling with Latent Diffusion Planning","created":"2026-02-24","cited_by_count":2,"area":"lr"},{"id":"2210.12478","title":"DiscoSense: Commonsense Reasoning with Discourse Connectives","created":"2022-10-22","cited_by_count":1,"area":"lr"},{"id":"2601.01714","title":"Entropy-Aligned Decoding of LMs for Better Writing and Reasoning","created":"2026-01-05","cited_by_count":1,"area":"lr"},{"id":"2601.22536","title":"Decoding in Geometry: Alleviating Embedding-Space Crowding for Complex Reasoning","created":"2026-01-30","cited_by_count":1,"area":"lr"},{"id":"2604.02113","title":"Reliable Control-Point Selection for Steering Reasoning in Large Language Models","created":"2026-04-02","cited_by_count":1,"area":"lr"},{"id":"2604.11137","title":"From Answers to Arguments: Toward Trustworthy Clinical Diagnostic Reasoning with Toulmin-Guided Curriculum Goal-Conditioned Learning","created":"2026-04-13","cited_by_count":1,"area":"lr"},{"id":"2207.05155","title":"Can Language Models perform Abductive Commonsense Reasoning?","created":"2022-07-07","cited_by_count":0,"area":"lr"},{"id":"2510.22132","title":"Controllable Mathematical Reasoning via Self-Optimizing Thought Vectors","created":"2025-10-25","cited_by_count":0,"area":"lr"},{"id":"2605.02348","title":"Decoding-Time Debiasing via Process Reward Models: From Controlled Fill-in to Open-Ended Generation","created":"2026-05-04","cited_by_count":0,"area":"lr"},{"id":"2606.03624","title":"Bridging Auxiliary Constraints to Resolve Instruction Following in Large Reasoning Models","created":"2026-06-02","cited_by_count":0,"area":"lr"},{"id":"2607.10296","title":"SPARK: Susceptibility-Guided Profiling and Steering of Latent Reasoning States in Large Language Models","created":"2026-07-11","cited_by_count":0,"area":"lr"},{"id":"2608.02585","title":"GradCuit: Credit-Assigned Gradient Flow Enables Robust and Interpretable Test-Time Latent Reasoning","created":"2026-08-03","cited_by_count":0,"area":"lr"},{"id":"2609.33462","title":"SphMind: Towards Robust, Training-Free VLM-based Spatial Reasoning with a 360 Camera","created":"2026-09-27","cited_by_count":0,"area":"lr"}],"next_cursor":null}