Efficient Language Model Reasoning

Follow this topic Ask about this topic

Momentum

23 papers in the last four weeks, up 188% on the four weeks before. 0.2% of all new papers.

Jul 13Week of Sep 28

Latest papers 166

All topics

When to Think Deeply: Inhibitory Deliberation for LLM Reasoning
Jun 4, 2026Zhixuan He, Yue FengEfficient Language Model Reasoning Inference-Time Compute Allocation
University of Birmingham, United Kingdom
Agentic Chain-of-Thought Steering for Efficient and Controllable LLM Reasoning
Jun 2, 2026Yu Xia, Zhouhang Xie, Xin Xu +4Language Model Steering CoT Reasoning
University of California San Diego1 · Intuit AI Research2
HybridThinker: Efficient Chain-of-Thought Reasoning via Compressed Memory and Transient Thought Steps
Jun 2, 2026Xin Liu, Runsong Zhao, Xinyu Liu +8Memory-Augmented Language Models Efficient Language Model Reasoning
School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China · China Unicom Cloud-Link, China · NiuTrans Research, Shenyang, China
ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning
Jun 2, 2026Ziyan Liu, Xueda Shen, Yuzhe Gu +7Efficient Language Model Reasoning Preference Optimization
Shanghai Artificial Intelligence Laboratory · University of Science and Technology of China · MMLab, The Chinese University of Hong Kong
Geometric Latent Reasoning Induces Shorter Generations in LLMs
Jun 1, 2026Shashi Kumar, Yacouba Kaloga, Petr Motlicek +2Efficient Language Model Reasoning Continuous Latent Reasoning
Idiap Research Institute, Switzerland · EPFL, Switzerland · BUT, Czech Republic
Extreme Low-Bit Inference in Reasoning Models: Failure Modes and Targeted Recovery
Jun 1, 2026Ekaterina Alimaskina, Darya Rudas, Denis Shveykin +3LLM Quantization Efficient Language Model Reasoning
BRAIn Lab, Moscow, Russia
Thinking Economically: A Hierarchical Framework for Adaptive-Complexity Reasoning in LLMs
May 31, 2026Yubo Gao, Haotian Wu, Hong Chen +8LLM Inference Efficiency CoT Reasoning
The Hong Kong University of Science and Technology (Guangzhou) · The Hong Kong University of Science and Technology · Nanyang Technological University +1
ThinkSwitch: Context Distillation with LoRA and Weight Interpolation for Specific-Purpose Reasoning Tasks
May 31, 2026Dhruv Saini, Rohan PandeyEfficient Language Model Reasoning Language Model Distillation
Bellevue High School · DigitalOcean
Quantized Reasoning Models Think They Need to Think Longer, but They Do Not
May 29, 2026Sanae Lotfi, Polina Kirichenko, Steven Li +1Overthinking in Language Models CoT Reasoning
1FAIR at Meta · 2Meta AI
Unlocking the Working Memory of Large Language Models for Latent Reasoning
May 28, 2026Lukas Aichberger, Sepp HochreiterMemory-Augmented Language Models Efficient Language Model Reasoning
ELLIS Unit Linz and LIT AI Lab, Institute for Machine Learning, Johannes Kepler University Linz, Austria · NXAI GmbH, Linz, Austria
Reasoning with Sampling: Cutting at Decision Points
May 28, 2026Felix Zhou, Anay Mehrotra, Quanquan C. LiuMarkov Chain Monte Carlo Efficient Language Model Reasoning
Yale University · Stanford University
ESPO: Early-Stopping Proximal Policy Optimization
May 28, 2026Zihang Li, Rui Zhou, Yingcheng Shi +8Early Stopping Reinforcement Learning
1Tongyi Lab , Alibaba Group · 2Peking University
Teaching Language Models to Check Grounded Claim Factuality with Human Test-Taking Strategies
May 28, 2026Yuxuan Ye, Raul Santos-Rodriguez, Edwin SimpsonLLM Grounding Claim Verification
Intelligent Systems Laboratory University of Bristol United Kingdom
CORE: Contrastive Reflection Enables Rapid Improvements in Reasoning
May 27, 2026Linas Nasvytis, Simon Jerome Han, Ben Prystawski +3LLM Self-Refinement Efficient Language Model Reasoning
Stanford University
CIRF: Tokenizing Chain-of-Thoughts into Reusable Functional Units for Efficient Latent Reasoning in Large Language Models
May 27, 2026Yukyung Lee, Yumeng Shen, Jinhyeong Park +2CoT Reasoning Efficient Language Model Reasoning
Boston University · Hankuk University of Foreign Studies
Self-Consistency via Marginal Sharpening
May 27, 2026Aleksei Arzhantsev, Otmane Sakhi, Nicolas ChopinEfficient Language Model Reasoning Reasoning Consistency in Language Models
Criteo AI Lab, CREST IP Paris · Criteo AI Lab · ENSAE, Institut Polytechnique de Paris
Uncertainty-Aware Budget Allocation for Adaptive Test-Time Reasoning
May 26, 2026Manh Nguyen, Sunil Gupta, Hung LeEfficient Language Model Reasoning Adaptive Sampling
Applied Artificial Intelligence Initiative Deakin University, Australia
Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains
May 25, 2026Hui Xie, Jie Liu, Ziyue Qiao +1Efficient Language Model Reasoning LLM Inference Acceleration
Eindhoven University of Technology, Netherlands · School of Computing and Information Technology, Great Bay University, China
Beyond the Frontier: Stochastic Backtracking for Efficient Test-Time Scaling
May 24, 2026Dao Tran, Duc Anh Le, Ngoc Luu +3Inference-Time Scaling Efficient Language Model Reasoning
Qualcomm AI Research†
Learning to Reason Efficiently with A* Post-Training
May 23, 2026Andreas Opedal, Francesco Ignazio Re, Abulhair Saparov +3Process Reward Models RL for Language Model Reasoning
αETH Zürich · γPurdue University · βMPI for Intelligent Systems, Tübingen
HyperGuide: Hyperbolic Guidance for Efficient Multi-Step Reasoning in Large Language Models
May 22, 2026Yuyu Liu, Haotian Xu, Yanan He +3LLM Fine-Tuning Efficient Language Model Reasoning
Department of Computer Science Stony Brook University · Department of Applied Mathematics and Statistics Stony Brook University · Department of Computer Science Yale University +2
PathCal: State-Aware Reflection-Marker Calibration for Efficient Reasoning
May 21, 2026Lingyu Jiang, Zirui Li, Shuo Xing +6Efficient Language Model Reasoning Efficient Language Model Inference
1Tohoku University · 2Texas A&M University · 3Worcester Polytechnic Institute
CLORE: Content-Level Optimization for Reasoning Efficiency
May 21, 2026Yuyang Wu, Qiyao Xue, Guanxing Lu +4RL for Language Model Reasoning Efficient Language Model Reasoning
Carnegie Mellon University · University of North Carolina, Chapel Hill · University of Pittsburgh +1
When Do LLMs Reason? A Dynamical Systems View via Entropy Phase Transitions
May 20, 2026Wei Xia, Haoqing Wang, Zhi-Hong Deng +1Language Model Decoding CoT Reasoning
Samsung Research, Beijing, China · State Key Laboratory of General Artificial Intelligence, School of Intelligence Science and Technology, Peking University
Stop When Reasoning Converges: Semantic-Preserving Early Exit for Reasoning Models
May 17, 2026Dehai Min, Giovanni Vaccarino, Huiyi Chen +3Early Stopping CoT Reasoning
University of Illinois Chicago · Politecnico di Milano · University of Illinois Urbana-Champaign +1
Reasoning Can Be Restored by Correcting a Few Decision Tokens
May 16, 2026Changshuo Shen, Leheng Sheng, Yuxin Chen +2Efficient Language Model Reasoning Inference-Time Compute Allocation
University of Science and Technology of China, Hefei, China · National University of Singapore, Singapore
CAPS: Cascaded Adaptive Pairwise Selection for Efficient Parallel Reasoning
May 15, 2026Fangzhou Lin, Shuo Xing, Peiran Li +6Pairwise Comparison Pairwise Preference Evaluation
Texas A&M University · Georgia Institute of Technology · Tohoku University +1
Distribution Corrected Offline Data Distillation for Large Language Models
May 13, 2026Yumeng Zhang, Zhengbang Yang, Yevin Nikhel Goonatilake +1CoT Distillation Efficient Language Model Reasoning
George Mason University, Fairfax, VA, USA
Enhanced and Efficient Reasoning in Large Learning Models
May 13, 2026Leslie G. ValiantRepresentation Learning World Models
John A. Paulson School of Engineering and Applied Sciences Harvard University, Boston, MA 02134
STOP: Structured On-Policy Pruning of Long-Form Reasoning in Low-Data Regimes
May 13, 2026Chenjun Xu, Zhennan Zhou, Zhan Su +3LLM Pruning LLM Fine-Tuning
University of Washington · University of Montreal

Jun 4, 2026, cs.CLJ/K move · Enter open · S save

When to Think Deeply: Inhibitory Deliberation for LLM Reasoning

Zhixuan He, Yue Feng

University of Birmingham, United Kingdom

Efficient Language Model Reasoning Inference-Time Compute Allocation LLM Routing Efficient Language Model Inference LLM Mathematical Reasoning

Open paper AskPDF arXiv

Reasoning Large Language Models can improve problem-solving performance through deliberative inference, but invoking slow reasoning for every input is computationally expensive and often unnecessary. We propose IDPR, a framework for response-conditioned inhibitory deliberation. IDPR first generates a concise intuitive answer and then uses an inhibition controller to decide whether that specific response should be released or suppressed in favor of slow reasoning. Unlike input-only routers, the inhibition controller conditions on the fast answer and fast-side evidence, including confidence, logit margin, parseability, and generation cost. We train the controller from paired fast-slow outcomes and select the inhibition threshold on a held-out validation set under an accuracy-first slow-call budget. On a held-out 5,000-example mathematical reasoning test set, IDPR invokes slow reasoning on only 8.20% of examples and improves accuracy from 47.90% to 48.92%. Under the same slow-call budget, random routing decreases accuracy to 46.76%, while the strongest confidence-based baseline reaches 48.22%. IDPR also achieves the highest corrective precision, showing that response-conditioned inhibition better identifies fast answers that benefit from slow reasoning.

Momentum

Related topics

Latest papers 166