{"total":73,"rows":[{"id":"2503.16419","title":"Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models","created":"2025-03-20","cited_by_count":464,"area":"lr"},{"id":"2502.21074","title":"CODI: Compressing Chain-of-Thought into Continuous Space via Self-Distillation","created":"2025-02-28","cited_by_count":225,"area":"lr"},{"id":"2503.24235","title":"A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?","created":"2025-03-31","cited_by_count":223,"area":"lr"},{"id":"2504.15895","title":"Dynamic Early Exit in Reasoning Models","created":"2025-04-22","cited_by_count":219,"area":"lr"},{"id":"2504.09858","title":"Reasoning Models Can Be Effective Without Thinking","created":"2025-04-14","cited_by_count":187,"area":"lr"},{"id":"2503.21614","title":"A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond","created":"2025-03-27","cited_by_count":132,"area":"lr"},{"id":"2504.10903","title":"Efficient Reasoning Models: A Survey","created":"2025-04-15","cited_by_count":95,"area":"lr"},{"id":"2505.16552","title":"Think Silently, Think Fast: Dynamic Latent Compression of LLM Reasoning Chains","created":"2025-05-22","cited_by_count":85,"area":"lr"},{"id":"2507.06203","title":"A Survey on Latent Reasoning","created":"2025-07-08","cited_by_count":81,"area":"lr"},{"id":"2505.12514","title":"Reasoning by Superposition: A Theoretical Perspective on Chain of Continuous Thought","created":"2025-05-18","cited_by_count":77,"area":"lr"},{"id":"2509.20317","title":"SIM-CoT: Supervised Implicit Chain-of-Thought","created":"2025-09-24","cited_by_count":70,"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":"2507.14417","title":"Inverse Scaling in Test-Time Compute","created":"2025-07-19","cited_by_count":50,"area":"lr"},{"id":"2505.19092","title":"Reinforced Latent Reasoning for LLM-based Recommendation","created":"2025-05-25","cited_by_count":47,"area":"lr"},{"id":"2509.02350","title":"Implicit Reasoning in Large Language Models: A Comprehensive Survey","created":"2025-09-02","cited_by_count":43,"area":"lr"},{"id":"2505.18454","title":"Hybrid Latent Reasoning via Reinforcement Learning","created":"2025-05-24","cited_by_count":32,"area":"lr"},{"id":"2510.04573","title":"LaDiR: Latent Diffusion Enhances LLMs for Text Reasoning","created":"2025-10-06","cited_by_count":29,"area":"lr"},{"id":"2505.18962","title":"System-1.5 Reasoning: Traversal in Language and Latent Spaces with Dynamic Shortcuts","created":"2025-05-25","cited_by_count":27,"area":"lr"},{"id":"2510.05069","title":"SwiReasoning: Switch-Thinking in Latent and Explicit for Pareto-Superior Reasoning LLMs","created":"2025-10-06","cited_by_count":22,"area":"lr"},{"id":"2511.06411","title":"SofT-GRPO: Surpassing Discrete-Token LLM Reinforcement Learning via Gumbel-Reparameterized Soft-Thinking Policy Optimization","created":"2025-11-09","cited_by_count":21,"area":"lr"},{"id":"2505.11225","title":"HAPO: Training Language Models to Reason Concisely via History-Aware Policy Optimization","created":"2025-05-16","cited_by_count":19,"area":"lr"},{"id":"2507.09662","title":"Towards Concise and Adaptive Thinking in Large Reasoning Models: A Survey","created":"2025-07-13","cited_by_count":18,"area":"lr"},{"id":"2509.18091","title":"OnePiece: Bringing Context Engineering and Reasoning to Industrial Cascade Ranking System","created":"2025-09-22","cited_by_count":18,"area":"lr"},{"id":"2509.23365","title":"Emergence of Superposition: Unveiling the Training Dynamics of Chain of Continuous Thought","created":"2025-09-27","cited_by_count":16,"area":"lr"},{"id":"2511.08577","title":"Think-at-Hard: Dynamic Looped Transformers for Improved Reasoning","created":"2025-11-11","cited_by_count":16,"area":"lr"},{"id":"2602.08783","title":"Dynamics Within Latent Chain-of-Thought: An Empirical Study of Causal Structure","created":"2026-02-09","cited_by_count":11,"area":"lr"},{"id":"2506.18810","title":"ConciseHint: Boosting Efficient Reasoning via Continuous Concise Hints during Generation","created":"2025-06-23","cited_by_count":10,"area":"lr"},{"id":"2603.01914","title":"AdaPonderLM: Gated Pondering Language Models with Token-Wise Adaptive Depth","created":"2026-03-02","cited_by_count":10,"area":"lr"},{"id":"2505.24550","title":"A*-Thought: Efficient Reasoning via Bidirectional Compression for Low-Resource Settings","created":"2025-05-30","cited_by_count":9,"area":"lr"},{"id":"2505.23701","title":"Can LLMs Reason Abstractly Over Math Word Problems Without CoT? Disentangling Abstract Formulation From Arithmetic Computation","created":"2025-05-29","cited_by_count":8,"area":"lr"},{"id":"2506.04182","title":"Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models","created":"2025-06-04","cited_by_count":8,"area":"lr"},{"id":"2510.02312","title":"KaVa: Latent Reasoning via Compressed KV-Cache Distillation","created":"2025-10-02","cited_by_count":8,"area":"lr"},{"id":"2510.24940","title":"SemCoT: Accelerating Chain-of-Thought Reasoning through Semantically-Aligned Implicit Tokens","created":"2025-10-28","cited_by_count":8,"area":"lr"},{"id":"2511.02360","title":"LaRe: Latent Refocusing for Multimodal Reasoning","created":"2025-11-04","cited_by_count":8,"area":"lr"},{"id":"2604.08299","title":"SeLaR: Selective Latent Reasoning in Large Language Models","created":"2026-04-09","cited_by_count":7,"area":"lr"},{"id":"2506.10716","title":"PREMISE: Scalable and Strategic Prompt Optimization for Efficient Mathematical Reasoning in Large Models","created":"2025-06-12","cited_by_count":5,"area":"lr"},{"id":"2603.15051","title":"Thinking in Latents: Adaptive Anchor Refinement for Implicit Reasoning in LLMs","created":"2026-03-16","cited_by_count":5,"area":"lr"},{"id":"2607.22925","title":"Not All LLM Reasoning is Visible in the Chain-of-Thought","created":"2026-07-24","cited_by_count":5,"area":"lr"},{"id":"2510.13170","title":"Putting on the Thinking Hats: A Survey on Chain of Thought Fine-tuning from the Perspective of Human Reasoning Mechanism","created":"2025-10-15","cited_by_count":4,"area":"lr"},{"id":"2512.00003","title":"Efficient Turing Machine Simulation with Transformers","created":"2025-09-28","cited_by_count":4,"area":"lr"},{"id":"2602.01148","title":"Capabilities and Fundamental Limits of Latent Chain-of-Thought","created":"2026-02-01","cited_by_count":4,"area":"lr"},{"id":"2602.04925","title":"Internalizing LLM Reasoning via Discovery and Replay of Latent Actions","created":"2026-02-04","cited_by_count":4,"area":"lr"},{"id":"2602.20945","title":"The Art of Efficient Reasoning: Data, Reward, and Optimization","created":"2026-02-24","cited_by_count":4,"area":"lr"},{"id":"2603.12372","title":"Efficient Reasoning with Balanced Thinking","created":"2026-03-12","cited_by_count":4,"area":"lr"},{"id":"2603.14602","title":"PA3: Policy-Aware Agent Alignment through Chain-of-Thought","created":"2026-03-15","cited_by_count":4,"area":"lr"},{"id":"2606.06447","title":"Latent Reasoning with Normalizing Flows","created":"2026-06-04","cited_by_count":4,"area":"lr"},{"id":"2505.16950","title":"Bottlenecked Transformers: Periodic KV Cache Consolidation for Generalised Reasoning","created":"2025-05-22","cited_by_count":3,"area":"lr"},{"id":"2509.21482","title":"Learning to Reason with Mixture of Tokens","created":"2025-09-25","cited_by_count":3,"area":"lr"},{"id":"2510.10168","title":"Concise Reasoning in the Lens of Lagrangian Optimization","created":"2025-10-11","cited_by_count":3,"area":"lr"},{"id":"2511.08983","title":"SpiralThinker: Latent Reasoning through an Iterative Process with Text-Latent Interleaving","created":"2025-11-12","cited_by_count":3,"area":"lr"},{"id":"2602.14077","title":"GTS: Inference-Time Scaling of Latent Reasoning with a Learnable Gaussian Thought Sampler","created":"2026-02-15","cited_by_count":3,"area":"lr"},{"id":"2602.19049","title":"IAPO: Information-Aware Policy Optimization for Token-Efficient Reasoning","created":"2026-02-22","cited_by_count":3,"area":"lr"},{"id":"2607.22629","title":"Masked Distillation: Internalizing the Chain-of-Thought in Language Models","created":"2026-06-18","cited_by_count":3,"area":"lr"},{"id":"2510.12167","title":"Towards Inference-time Scaling for Continuous Space Reasoning","created":"2025-10-14","cited_by_count":2,"area":"lr"},{"id":"2512.02240","title":"Lightweight Latent Reasoning for Narrative Tasks","created":"2025-12-01","cited_by_count":2,"area":"lr"},{"id":"2512.24014","title":"iCLP: Large Language Model Reasoning with Implicit Cognition Latent Planning","created":"2025-12-30","cited_by_count":2,"area":"lr"},{"id":"2602.14917","title":"BFS-PO: Best-First Search for Large Reasoning Models","created":"2026-02-16","cited_by_count":2,"area":"lr"},{"id":"2603.17449","title":"TRiMS: Real-Time Tracking of Minimal Sufficient Length for Efficient Reasoning via RL","created":"2026-03-18","cited_by_count":2,"area":"lr"},{"id":"2604.26355","title":"Shorthand for Thought: Compressing LLM Reasoning via Entropy-Guided Supertokens","created":"2026-04-29","cited_by_count":2,"area":"lr"},{"id":"2605.28600","title":"Transformers Provably Learn to Internalize Chain-of-Thought","created":"2026-05-27","cited_by_count":2,"area":"lr"},{"id":"2505.22202","title":"Latent Reasoning via Sentence Embedding Prediction","created":"2025-05-28","cited_by_count":1,"area":"lr"},{"id":"2601.22730","title":"ImgCoT: Compressing Long Chain of Thought into Compact Visual Tokens for Efficient Reasoning of Large Language Model","created":"2026-01-30","cited_by_count":1,"area":"lr"},{"id":"2602.01198","title":"A State-Transition Framework for Efficient LLM Reasoning","created":"2026-02-01","cited_by_count":1,"area":"lr"},{"id":"2605.20075","title":"CopT: Contrastive On-Policy Thinking with Continuous Spaces for General and Agentic Reasoning","created":"2026-05-19","cited_by_count":1,"area":"lr"},{"id":"2606.02842","title":"Spectral-Progressive Thought Flow for Lightweight Multimodal Reasoning","created":"2026-06-01","cited_by_count":1,"area":"lr"},{"id":"2606.02871","title":"Adaptive Latent Agentic Reasoning","created":"2026-06-01","cited_by_count":1,"area":"lr"},{"id":"2608.01593","title":"Latent Thought Credit: Multi-Answer Credit Assignment for Latent Reasoning","created":"2026-08-03","cited_by_count":1,"area":"lr"},{"id":"2604.07490","title":"Enabling Intrinsic Reasoning over Dense Geospatial Embeddings with DFR-Gemma","created":"2026-04-08","cited_by_count":0,"area":"lr"},{"id":"2606.02248","title":"Geometric Latent Reasoning Induces Shorter Generations in LLMs","created":"2026-06-01","cited_by_count":0,"area":"lr"},{"id":"2606.05859","title":"TARPO: Token-Wise Latent-Explicit Reasoning via Action-Routing Policy Optimization","created":"2026-06-04","cited_by_count":0,"area":"lr"},{"id":"2606.07108","title":"DyCon: Dynamic Reasoning Control via Evolving Difficulty Modeling","created":"2026-06-05","cited_by_count":0,"area":"lr"},{"id":"2610.03839","title":"SYNLAT: Syntax-Aligned Text-Latent Compression for Chain-of-Thought Reasoning","created":"2026-10-02","cited_by_count":0,"area":"lr"},{"id":"2610.17189","title":"Soft Teacher Forcing","created":"2026-10-12","cited_by_count":0,"area":"lr"}],"next_cursor":null}