Latent CoT Reasoning

CoT: Chain-of-Thought

Follow this topic Ask about this topic

Momentum

3 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

Jul 13Week of Sep 28

Latest papers 28

All topics

Next Thoughts Are Distributions: Generative Autoregressive Reasoning in the Latent Space
Sep 27, 2026Yang Li, Yi Wang, Shiyuan Huang +3Numerical Reasoning in Language Models Continuous Latent Reasoning
Rutgers University · Amazon · University of Illinois at Urbana-Champaign
Structural Process Supervision for Latent Chain-of-Thought Reasoning
Sep 9, 2026Yiqi Li, Xu Chen, Chen Ju +5Representation Learning Process Supervision
Shanghai Jiao Tong University · Taobao & Tmall Group
Think Wider: Mitigating Latent Rank Collapse in Implicit Chain-of-Thought Reasoning
Sep 7, 2026Yuwen Hao, Menglin YangSpectral Regularization Continuous Latent Reasoning
The Hong Kong University of Science and Technology (Guangzhou)
Latent Recurrent Thoughts: Recurrent Refinement of Proposed Latents for Reasoning with Frozen LLMs
Sep 1, 2026Zhaoliang Chen, Jie FuEfficient Language Model Reasoning Continuous Latent Reasoning
Emory University · IQuest Research
Does Out-of-Sight Equal Out-of-Mind in CoT Monitorability?
Aug 5, 2026Pedro Ferreira, Wilker Aziz, Ivan TitovCoT Monitoring Latent CoT Reasoning
University of Amsterdam · University of Edinburgh
Final Checkpoints Are Not Enough: Analyzing Latent Reasoning Faithfulness Along Training Trajectories
Jul 7, 2026Hengyu Jin, Shu Yang, Di WangCoT Faithfulness Continuous Latent Reasoning
Tongji University · Provable Responsible AI and Data Analytics (PRADA) Lab · King Abdullah University of Science and Technology
CoLT: Teaching Multi-Modal Models to Think with Chain of Latent Thoughts
Jun 30, 2026Lianyu Hu, Shengqian Qin, Zeqin Liao +4Efficient Multimodal Inference Efficient Language Model Reasoning
Nanyang Technological University, Singapore · Shanghai Jiao Tong University, China · NKIARI, Shenzhen Futian, China +2
Bridging the Gap Between Latent and Explicit Reasoning with Looped Transformers
Jun 30, 2026Ying Fan, Anej Svete, Kangwook LeeCoT Reasoning Recurrent Transformers
Microsoft Research · 2ETH Zürich · 3KRAFTON +1
Interpreting Latent CoT Reasoning as Dynamical Systems
Jun 20, 2026Sabari Iyyappan Duraipandian, Shreya Sanjay Boyane, Manju Nagesh +3Latent Dynamics Modeling LLM Interpretability
1San Jose State University. · 2Worcester Polytechnic Institute. · 3George Mason University. +1
What Makes Effective Supervision in Latent Chain-of-Thought: An Information-Theoretic Analysis
Jun 18, 2026Xinghao Chen, Chak Tou Leong, Wenjin Guo +3Continuous Latent Reasoning Process Supervision
Ningbo Institute of Digital Twin, Eastern Institute of Technology, Ningbo, China · Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China.
Demystifying Hidden-State Recurrence: Switchable Latent Reasoning with On-Policy Reinforcement Learning
Jun 11, 2026Jiayu Yang, Chao Chen, Shengen Wu +6RL for Language Model Reasoning Mechanistic Interpretability
HKUST(GZ) · University of Cambridge · NTU +2
Observable Patterns Are Not Explanations: A Causal-Geometric Analysis of Latent Reasoning Models
Jun 10, 2026Darpan Aswal, Thomas Palmeira Ferraz, Yongxin Zhou +1Continuous Latent Reasoning Causal Interpretability
Université Grenoble Alpes, CNRS, Grenoble INP, LIG · Université Paris-Saclay · NAVER LABS Europe
LoRi: Low-Rank Distillation for Implicit Reasoning
Jun 3, 2026Ryan Solgi, Jiayi Tian, Zheng ZhangCoT Distillation Mathematical Reasoning
University of California-Santa Barbara, USA
Adaptive Latent Agentic Reasoning
Jun 1, 2026Dongwon Jung, Peng Shi, Yi Zhang +2Agentic Reasoning LLM Agents
University of California, Davis · University of Waterloo · Greenshoe, Inc.
The Chain Holds, the Answer Folds: Trace-Answer Dissociation in Reasoning Models Under Adversarial Pressure
May 27, 2026Yubo Li, Ramayya Krishnan, Rema PadmanCoT Faithfulness Reasoning Evaluation
Carnegie Mellon University
Transformers Provably Learn to Internalize Chain-of-Thought
May 27, 2026Yixiao Huang, Hanlin Zhu, Zixuan Wang +4Transformer CoT Reasoning
UC Berkeley · Princeton 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
Unified Synthesis of Compositional Speech and Sound from Free-Form Text Prompts
May 27, 2026Yuyue Wang, Xihua Wang, Xin Cheng +2Text-to-Audio Generation Audio Generation
Renmin University of China
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
Latent Chain-of-Thought Improves Structured-Data Transformers
May 11, 2026Carson Dudley, Samet OymakCoT Reasoning Time Series Forecasting
RuPLaR : Efficient Latent Compression of LLM Reasoning Chains with Rule-Based Priors From Multi-Step to One-Step
May 10, 2026Xiaocheng Luo, Kang Wang, Zaifu Zhan +2LLM Compression CoT Compression
School of Computer Science and Technology, Soochow University, Suzhou, 215006, Jiangsu, PR China · Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, 55455, MN, USA
LaTER: Efficient Test-Time Reasoning via Latent Exploration and Explicit Verification
May 8, 2026Xuan Li, Yining Wang, Yuchen Liu +7CoT Reasoning Efficient Language Model Reasoning
University of Science and Technology of China · Unisound AI Technology Co., Ltd · MAIS, Institute of Automation, Chinese Academy of Sciences
Thinking Without Words: Efficient Latent Reasoning with Abstract Chain-of-Thought
Apr 24, 2026Keshav Ramji, Tahira Naseem, Ramón Fernandez AstudilloEfficient Language Model Reasoning Implicit Reasoning in Language Models
IBM Research AI
Think in Latent Thoughts: A New Paradigm for Gloss-Free Sign Language Translation
Apr 16, 2026Yiyang Jiang, Li Zhang, Xiao-Yong Wei +1Sign Language Translation Video-Language Models
The Hong Kong Polytechnic University · Sichuan University
Beyond Dense States: Sparse Transcoders as Causally Testable Operators for LLM Latent Reasoning
Feb 2, 2026Yadong Wang, Haodong Chen, Yu Tian +3Sparse Autoencoders Continuous Latent Reasoning
Nanjing University of Aeronautics and Astronautics · State Key Laboratory of Ocean Sensing, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, 311215, China · Security Capability Center
Latent Chain-of-Thought as Planning: Decoupling Reasoning from Verbalization
Jan 29, 2026Jiecong Wang, Hao Peng, Zhanyi Wang +2LLM Planning Efficient Language Model Reasoning
Beihang University · Didi Chuxing
Triggering Chain-of-Thought via Latent Feature Interventions in Large Language Models
Jan 12, 2026Zhenghao He, Guangzhi Xiong, Bohan Liu +2LLM Interpretability CoT Reasoning
University of Virginia, USA
Reasoning Beyond Language: A Comprehensive Survey on Latent Chain-of-Thought Reasoning
May 22, 2025Xinghao Chen, Anhao Zhao, Heming Xia +7CoT Reasoning LLM Reasoning
Department of Computing, The Hong Kong Polytechnic University · Ningbo Digital Twin Institute, Eastern Institute of Technology, Ningbo, China

Sep 27, 2026, cs.AIJ/K move · Enter open · S save

Next Thoughts Are Distributions: Generative Autoregressive Reasoning in the Latent Space

Yang Li, Yi Wang, Shiyuan Huang, Yang Liu+2

Rutgers University · Amazon · University of Illinois at Urbana-Champaign

Numerical Reasoning in Language Models Continuous Latent Reasoning Latent Reasoning Latent CoT Reasoning

Open paper AskPDF arXiv

Reasoning problems often admit multiple valid ways to proceed. Continuous reasoning promises to move computation beyond language tokens into a more compact latent space, but representing several plausible ways to think next remains difficult. We introduce Autoregressive Thought Flow (ATF), which models the next continuous thought as a multimodal distribution. A causal autoregressive model performs the reasoning computation, while a lightweight diffusion head generates a plausible next thought from the resulting condition. The sampled thought is fed back into the model, allowing continuous reasoning to unfold for a variable number of steps while preserving the pretrained backbone. Across mathematical reasoning tasks, ATF improves accuracy with compact latent traces and benefits from reinforcement learning and additional test-time thinking. Multi-sample evaluation shows broader solution coverage, indicating that its multimodal predictions capture useful diversity among reasoning paths. Our results suggest that continuous reasoning is more effective when multiple possible next thoughts remain available rather than being collapsed into a single prediction.

Momentum

Related topics

Latest papers 28