Latent Reasoning

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

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HALO: Hybrid Adaptive Latent Reasoning for Language Models
May 3, 2026Micah ZhangLLM Inference Acceleration Adaptive Computation
Lockheed Martin
State Stream Transformer (SST) V2: Parallel Training of Nonlinear Recurrence for Latent Space Reasoning
Apr 30, 2026Thea AvissRecurrent Neural Networks Recurrent Transformers
Fifth Dimension
Latent-GRPO: Group Relative Policy Optimization for Latent Reasoning
Apr 30, 2026Jingcheng Deng, Zihao Wei, Liang Pang +4Reinforcement Learning RL for Language Model Reasoning
State Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences · University of Chinese Academy of Sciences · 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
LEPO: Latent Reasoning Policy Optimization for Large Language Models
Apr 20, 2026Yuyan Zhou, Jiarui Yu, Hande Dong +4Reinforcement Learning RL for Language Model Reasoning
Tencent · Zhejiang University · Shanghai Jiao Tong University
LLM Reasoning Is Latent, Not the Chain of Thought
Apr 17, 2026Wenshuo WangLLM Interpretability CoT Reasoning
School of Future Technology, South China University of Technology, China
How Do Latent Reasoning Methods Perform Under Weak and Strong Supervision?
Feb 25, 2026Yingqian Cui, Zhenwei Dai, Bing He +7Latent Reasoning Continuous Latent Reasoning
Amazon · Michigan State 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
Scaling Latent Reasoning via Looped Language Models
Oct 29, 2025Rui-Jie Zhu, Zixuan Wang, Kai Hua +30Language Model Pretraining Implicit Reasoning in Language Models
1ByteDance Seed · 2UC Santa Cruz · 3Princeton University +8

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HALO: Hybrid Adaptive Latent Reasoning for Language Models

Micah Zhang

Lockheed Martin

LLM Inference Acceleration Adaptive Computation Latent Reasoning

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We study how to improve a frozen pretrained language model with a small amount of adaptive extra computation. A simple approach is to add additional refinement steps on top of the backbone hidden states, but fixed extra refinement can be wasteful: a one-step refinement head may be too weak, while forcing a second full-sequence refinement step everywhere can increase compute without improving transfer. We introduce HALO, a hybrid adaptive latent-refinement method that combines a coarse refinement stage with selective second-stage latent refinement on a subset of tokens chosen by token scoring and monotonic token halting. On the main public benchmark comparison built from MMLU-Pro and GPQA-Diamond, HALO achieves the best overall average among the paper-facing methods, outperforming the frozen backbone, fixed-1, and fixed-2. Internal analysis further shows that HALO reaches nearly the same token-accuracy level as fixed-2 while using fewer average applied refine steps than fixed-1 and far fewer than fixed-2. These results suggest that the key advantage is not simply more refinement, but a better allocation of refinement: HALO achieves the strongest paper-facing result while also using less measured controller compute than either fixed baseline.