Latent Reasoning

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Latest papers 69

14 papers in the last four weeks, up 367% on the four weeks before. 0.1% of all new papers.

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Invariant-Measure Reasoners: Stable Representations for Latent Reasoning
Oct 7, 2026Yuto Inui, Takuya Konishi, Yoshinobu KawaharaLatent Reasoning Continuous Latent Reasoning
The University of Osaka · RIKEN
CALR: Continuous Anchored Latent Reasoning via Render-of-Thought Compression
Oct 5, 2026Zhaoyang Wei, Bowen Jiang, Yanchao Hao +5Efficient Language Model Reasoning Latent Visual Reasoning
University of the Chinese Academy of Sciences · Tencent
What Matters for Latent Reasoning with Flow Matching
Oct 5, 2026Yassine Ouali, Adrian Bulat, Georgios TzimiropoulosFlow Matching Efficient Language Model Reasoning
Samsung AI Cambridge · Technical University of Iasi · Queen Mary University of London
SLVR: Structured Latent Visual Reasoning via Human-like Reasoning Flows
Oct 1, 2026Albert Gao, Bing Xue, Andrea ZanetteVisual Reasoning Latent Visual Reasoning
Carnegie Mellon University · Meta
Latent JEPA: Abstract Future Prediction for Latent Reasoning in Chemistry
Oct 1, 2026Xinjian Zhao, Yaoyao Xu, Xuemin Chen +2Molecular Optimization Joint-Embedding Predictive Architecture
School of Data Science, The Chinese University of Hong Kong, Shenzhen · Shanghai Artificial Intelligence Laboratory
AURAL: Adaptive Latent Reasoning with Joint Chunk for Speech Language Models
Oct 1, 2026Yuxiang Wang, Kunyu Feng, Yuancheng Wang +12RL for Language Model Reasoning Audio Reasoning
The Chinese University of Hong Kong, Shenzhen · Tencent Hunyuan · Tsinghua University +2
Principled Thoughts for Latent Recursive LLM Systems
Sep 28, 2026Fahd Seddik, Fatemeh FardContinuous Latent Reasoning Multi-Agent LLMs
FARD Lab, University of British Columbia, Okanagan, Canada
Not All Thinking is Created Equal: Latent Reasoning Discovers a Recurrent Search Algorithm for Depth Generalization
Sep 28, 2026Huzi Cheng, Zhewei ZhangLLM Reasoning with Graphs LLM Interpretability
University of Minnesota · Independent Researcher
VaME: Exploring Variational Latent Reasoning for Multimodal Embeddings
Sep 27, 2026Peixi Wu, Mingzhou Jiang, Feipeng Ma +11Multimodal IR Efficient Multimodal Inference
University of Science and Technology of China · Tsinghua University · Kuaishou +1
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
LoopCD: Loop-wise Contrastive Decoding for Improving Reasoning in Looped Language Models
Sep 21, 2026Byeongho Yu, Junhyuk So, Eunhyeok ParkContrastive Decoding Latent Reasoning
Department of Computer Science and Engineering Pohang University of Science and Technology (POSTECH) · Graduate School of Artificial Intelligence Pohang University of Science and Technology (POSTECH)
Schema-Anchored Latent Reasoning for Semantic Parsing-Based Knowledge Base Question Answering
Sep 17, 2026Guangze Gao, Zixuan Li, Sikui Zhang +5LLM Grounding Knowledge Graph Question Answering
Institute of Automation, Chinese Academy of Sciences China · Institute of Computing Technology, Chinese Academy of Sciences China · University of Chinese Academy of Sciences China
Learn Your Own Thoughts: Abstract Token Curriculum
Sep 17, 2026Khashayar Gatmiry, Avrajit Ghosh, Parsa Mirtaheri +4CoT Reasoning Curriculum Learning
UC San Diego · Google DeepMind and UC Berkeley
T-LoopFormer: Token-Level Elastic-Depth Looped Transformers for Latent Reasoning with Dynamic Routing
Sep 14, 2026Mingqian Yu, Wenpeng Zhang, Shaobo Cui +1KV Caching Recurrent Transformers
Institute of Automation Chinese Academy of Sciences Beijing, China · Independent Reasearcher
A*-Thought-V2: Efficient Latent Reasoning via Geometric Dynamics of LLM
Sep 7, 2026Xiaoang Xu, Siyuan Liu, Shuo Wang +13Efficient Language Model Reasoning Continuous Latent Reasoning
Beijing University of Posts and Telecommunications · OpenBMB · The Hong Kong Polytechnic University +2
DODR: Deterministic Operator-Driven Reasoning in Latent Space
Sep 4, 2026Weicai HuangLogical Reasoning Abductive Reasoning
Beijing MQPat Technologies, Co., Ltd.
Behaviour Is an Incomplete Measure of Reasoning Development: Cross-surface pre-arrival accessibility and the limits of developmental inference in a recurrent-depth reasoner
Aug 17, 2026Simon Lam-MuirLatent Reasoning Neural Algorithmic Reasoning
Prime Calibre, Australia
ENTLORE: A Graph-Grounded Benchmark for Latent Organizational Reasoning in Enterprise Question Answering
Aug 11, 2026Akrin Zheng, Alexander Wu, Alaia LiuGraph Retrieval-Augmented Generation Knowledge Graph Question Answering
INSIDE the Student's Mind: Jointly Modeling Latent Reasoning and Action in LLM Student Simulators
Aug 11, 2026Rose Niousha, Minwoo Kang, Narges NorouziLLM Fine-Tuning CoT Reasoning
Department of Electrical Engineering and Computer Sciences University of California, Berkeley
Think Deep, Speak Once: Relit, A Recursive Latent Implicit Transformer Framework
Aug 8, 2026Abhishek Panwar, Maheep Singh, Saksham BansalContinuous Latent Reasoning Efficient Language Model Inference
Indian Institute of Technology Roorkee, India
$\mathrm{R}{\scriptstyle\mathrm{EAL}}\mathrm{G}{\scriptstyle\mathrm{UARD}}$ : Reliable, Efficient, and Auditable LLM Safeguards via Latent Reasoning
Aug 4, 2026Zhinan Liu, Jie Li, Mingyu Kang +1LLM Auditing LLM Guardrails
Xiamen University · University of Science and Technology of China
The Ignition Is Real, and It Lives at the Readout: Latent composition, difficulty-clocked ignition, and the interface-constituted commit in a recurrent-depth reasoner
Aug 4, 2026Simon Lam-MuirCompositional Reasoning Representation Geometry in Language Models
Prime Calibre, Australia
GradCuit: Credit-Assigned Gradient Flow Enables Robust and Interpretable Test-Time Latent Reasoning
Aug 3, 2026Zhaoxin Yu, Qi Shen, Hengli Li +4Test-Time Optimization LLM Interpretability
NLCo Lab, Beijing Institute for General Artificial Intelligence · School of Artificial Intelligence, Beijing University of Posts and Telecommunications · School of Artificial Intelligence for Science, Peking University
Latent Thought Credit: Multi-Answer Credit Assignment for Latent Reasoning
Aug 3, 2026Xuyang Zhao, Liting Zhang, Zichen Xu +4Numerical Reasoning in Language Models RL for Language Model Reasoning
TMCC, College of Computer Science, Nankai University, Tianjin, China · Lingxi (Beijing) Technology Co., Ltd.
Hierarchical Latent Reasoning for LLM-based Recommendation
Jul 30, 2026Peiyu Hu, Siying Gu, Weihai Lu +8Sequential Recommendation RL for Language Model Reasoning
1Xi’an Jiaotong-Liverpool University · 2Xiaohongshu · 3Peking University +1
OneLatent: Latent Reasoning for Efficient Foundation Recommendation Models
Jul 29, 2026Hao Jiang, Peiru Du, Pengfei Yao +10LLM Inference Acceleration Large Language Model-Based Recommendation
Kuaishou Technology, Beijing, China
Penelope: Localized Latent Recurrence for Efficient Structured Reasoning
Jul 28, 2026Yutong Chen, Shouqian Shi, Xinran Liu +5Decoder-Only Language Models Recurrent Transformers
Not All LLM Reasoning is Visible in the Chain-of-Thought
Jul 24, 2026Vatsal Baherwani, Tom Goldstein, Ashwinee PandaCoT Faithfulness LLM Interpretability
New York University · University of Maryland · TogetherAI
J-CoT: Chain-of-Thought in J-Space
Jul 24, 2026Junde Wu, Jiayuan Zhu, Fengling Liu +2LLM Reasoning Latent Reasoning
University of Oxford · Stanford University
The Weight of Silence: A Causal Case for Weights Over the Scratchpad in Latent Chess Reasoning
Jul 23, 2026Ishan S. KshirsagarRL for Language Model Reasoning Continuous Latent Reasoning
Independent Researcher

Oct 7, 2026J/K move · Enter open · S save

Invariant-Measure Reasoners: Stable Representations for Latent Reasoning

Yuto Inui, Takuya Konishi, Yoshinobu Kawahara

The University of Osaka · RIKEN

Latent Reasoning Continuous Latent Reasoning Latent Dynamics Modeling

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Latent reasoning models repeatedly update a latent state using the same recurrent block. As the recurrent depth increases, the sequence of latent states may converge to a compact subset of the state space without necessarily converging to a fixed point. Existing models typically predict by applying a prediction head to a single latent state. However, the latent state can continue to change even after many updates, potentially making predictions unstable across recurrent depths. To address this instability, we introduce invariant-measure reasoners (ImR), a framework that uses an invariant measure as a stable representation. This measure describes the long-run distribution of latent states on the compact subset and is invariant under updates by the recurrent block. ImR predicts from the expectation of the prediction head's output under this measure. We use ImR in two ways: fine-tuning only the prediction head of existing models and training models from scratch. Both approaches reduce prediction instability and improve accuracy in many settings on maze and Sudoku tasks. In some settings, models trained with ImR exhibit non-fixed-point behavior more frequently than existing models yet achieve high accuracy even with such behavior, unlike existing models. These results suggest that ImR can leverage otherwise destabilizing dynamics for latent reasoning.