Continuous Latent Reasoning

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5 papers in the last four weeks, up 67% on the four weeks before. 0.0% of all new papers.

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Judging in Latent Space: Efficient Generative Reward Modeling via Semantics-Preserving Compression
Oct 7, 2026Mingqing Yuan, Xiaobo Liang, Junwei Yang +5Reward Modeling LLM-as-a-Judge
Soochow University · University of Cambridge · Chalmers University of Technology +3
Unrolled Flow Models for Reasoning
Oct 7, 2026Faissal Izermine, Hanru Bai, Oscar Davis +1Flow-Based Generative Modeling Flow Matching
Max Planck Institute for Intelligent Systems · ELLIS Institute Tübingen · ETH Zurich +3
Spatial Latent Reasoning for Embodied Reference Understanding
Oct 7, 2026Ling Li, Jianhui Zhong, Wei Liu +3Vision-Language Grounding Continuous Latent Reasoning
Tsinghua University · Dalian University of Technology · University of Science and Technology of China
Efficient Reasoning with Flow Language Models
Oct 7, 2026Hanru Bai, Faissal Izermine, Oscar Davis +1Efficient Language Model Reasoning Language Modeling
Max Planck Institute for Intelligent Systems · ETH Zurich · ELLIS Institute Tübingen +3
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
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
Reasoning with Continuous Latent Diffusion
Sep 28, 2026Xiang ChengNumerical Reasoning in Language Models Code Generation
Duke University Department of Electrical and Computer Engineering
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
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
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)
The Dynamics of Continuous Mixture Collapse in Language Models
Sep 2, 2026Ali BackourContinuous Latent Reasoning Representation Geometry in Language Models
Massachusetts Institute of Technology Cambridge, MA 02139
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
A Model with No Head and Many Thoughts
Aug 31, 2026Nikita Koriagin, Yaroslav Aksenov, George Bredis +3Efficient Language Model Reasoning LLM Inference Acceleration
1Yandex · 2T-Tech
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
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.
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
SLPO: Scaling Latent Reasoning via a Surrogate Policy
Jul 22, 2026Runyang You, Zhiyuan Liu, Yongqi Li +1Reinforcement Learning RL for Language Model Reasoning
The Hong Kong Polytechnic University · Sichuan University · Work done as an intern at PolyU.
Training Continuous Chain of Thought Models: A Tale of Two Regimes
Jul 18, 2026Varun Yerram, He He, Eunsol ChoiCoT Reasoning Continuous Latent Reasoning
Center for Data Science, New York University
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
Multimodal Continuous Reasoning via Asymmetric Mutual Variational Learning
Jul 1, 2026Shijie Li, Yilin Gao, Siyuan Yang +7Multimodal Large Language Models Latent Visual Reasoning
Shanghai Jiao Tong University · Ant Group
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
Why Struggle with Continuous Latents? Interpretable Discrete Latent Reasoning via Rendered Compression
Jun 29, 2026Shuochen Chang, Qingyang Liu, Shaobo Wang +8LLM Interpretability Efficient Language Model Reasoning
Shanghai Jiao Tong University · Tongji University
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.
Tyler: Typed Latent Reasoning for Language Models -- When to Think, What to Compute, and How Much to Allocate
Jun 15, 2026Hanyu Lin, Min Cai, Jiawei Wen +1Language Model Decoding Efficient Language Model Reasoning
1Shenzhen University · University of Alberta
Latent Thought Flow: Efficient Latent Reasoning in Large Language Models
Jun 15, 2026Xiandong Zou, Jing Huang, Jianshu Li +1RL for Language Model Reasoning Efficient Language Model Reasoning
Singapore Management University · Ant Group
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
Dropout-GRPO: Variational Stochasticity for Continuous Latent Reasoning
Jun 8, 2026Wooil JungRL for Language Model Reasoning Group Relative Policy Optimization
Why Limit the Residual Stream to Layers and Not Tokens? Persistent Memory for Continuous Latent Reasoning
Jun 5, 2026Mujtaba Farhan, Maheep ChaudharyMemory-Augmented Language Models Persistent Memory for Language Models
1Algoverse AI Research · 2Independent

Oct 7, 2026, cs.CLJ/K move · Enter open · S save

Judging in Latent Space: Efficient Generative Reward Modeling via Semantics-Preserving Compression

Mingqing Yuan, Xiaobo Liang, Junwei Yang, Ziwei Chen+4

Soochow University · University of Cambridge · Chalmers University of Technology+3

Reward Modeling LLM-as-a-Judge Continuous Latent Reasoning Efficient Language Model Inference

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Reward modeling often requires jointly representing and reasoning over multiple evaluation criteria, yet verbalizing this process token by token can incur substantial inference cost. Recent work on latent reasoning suggests that continuous states may support this computation more compactly. We introduce LatentGRM, a latent evaluation framework built on semantic chunking, compression, and reconstruction. By using the structure of rubric-guided evaluations to guide compression, LatentGRM learns compact continuous trajectories that support autonomous pairwise judgments without generating textual assessments. A separate interpreter reconstructs evaluation text from these trajectories, providing an offline view of the information retained under compression. Under matched training data and backbones, LatentGRM achieves competitive aggregate preference accuracy relative to explicit Supervised Fine-Tuning (SFT) judges at both 4B and 8B scales. Across four benchmark domains, LatentGRM-8B compresses evaluation trajectories by 8.9--9.2x and reduces total judge inference time by 6.1--7.0x at vote@5. Controlled rubric interventions show that criterion-dependent preference information is carried through the latent sequence. Together, these results demonstrate that continuous latent evaluation can substantially reduce inference cost while preserving competitive judgment quality.

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