Algorithmic Reasoning

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8 papers in the last four weeks, against 2 the four weeks before. 0.1% of all new papers.

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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
Recurrent Looped Transformer
Oct 6, 2026Yifan Zhang, Jichen Feng, Shihan QinLength Generalization Recurrent Transformers
Princeton University · University of Pennsylvania
Neural Algorithmic Reasoning for Graph Saddle Point Problems
Oct 5, 2026Samantha Chen, Jesse He, Coleman Clougherty +2Primal-Dual Optimization Graph Neural Networks
Oberlin College · Department of Computer Science, Oberlin College · University of California, San Diego +2
What Limits Recursive Reasoning Models: Optimization, Architecture and Test-Time Scaling
Sep 30, 2026Yuliana Shakhvalieva, Dmitrii Kharchev, Viacheslav Bezrukov +4Neural Algorithmic Reasoning Recurrent Transformers
RND NLP, DAIMLD, Russian Federation
Reasoning with Neural Cellular Automata
Sep 28, 2026Mayalen Etcheverry, Pietro Miotti, Aidan Sirbu +7Neural Cellular Automata Neural Network Generalization
Google Paradigms of Intelligence Team · School of Computer Science, McGill University · Mila - Quebec AI Institute +4
TCSAlgBench: Benchmarking Automated Proving for Research-Level Theoretical Computer Science
Sep 28, 2026Chutong Yang, Xiyuan Zhang, Yu Huang +7Mathematical Reasoning Benchmarks Automated Theorem Proving
Department of Computer Science, The University of Texas at Austin · Amazon · Department of Statistics and Data Science, The Wharton School, University of Pennsylvania
RLVR landscapes for iterated multiplications can be benign: Insights from spin-glass theory
Sep 23, 2026Noa Rubin, Zohar RingelReinforcement Learning Maximum Entropy RL
Racah Institute of Physics The Hebrew University of Jerusalem
Scaling of Capability and Efficiency at Inference Time in Large Reasoning Models
Sep 22, 2026Moritz Laber, Zohair Shafi, Germans Savcisens +6LLM Inference Efficiency Language Model Scaling Laws
Northeastern University, Boston, Massachusetts, USA · Complexity Science Hub Vienna, Vienna, Austria · Santa Fe Institute, Santa Fe, New Mexico, USA
When Recursive Models Finish Computing
Sep 22, 2026Hare Krishna, Shubham Singh, Stephen Ebert +1Recurrent Neural Networks Algorithmic Reasoning
Weinberg Institute, Department of Physics, University of Texas at Austin · Department of Urban and Environmental Policy Planning, Tufts University · Zyphra Technologies, San Francisco, CA, USA +2
Beyond Embedding Transfer: Component Roles in Grokking Transfer and Stability
Sep 16, 2026Zeyu JiaTransfer Learning Algorithmic Reasoning
Tianjin Medical University
GTA: Graph Theory Agent and Benchmark for Algorithmic Graph Reasoning with LLMs
Sep 14, 2026Zixiang Xu, Yanbo Wang, Chenxi Wang +6LLM Reasoning with Graphs LLM Agents
University of Southern California · University of California, Los Angeles · Mohamed bin Zayed University of Artificial Intelligence +2
Diffusion as a Training Curriculum for Timestep-Free Iterative Reasoning
Sep 1, 2026Mariia Drozdova, Aidan Sirbu, Pietro Miotti +4Constraint Satisfaction Algorithmic Reasoning
1Google, Paradigms of Intelligence Team · School of Computer Science, McGill University · 4Mila - Quebec AI Institute +3
Beyond Uncertainty: Multi-Solver Disagreement Rewards for Self-Evolving Reasoning Curricula
Aug 30, 2026Vinoth Selvendran, Zhanming ZhangReward Modeling RL for Language Model Reasoning
Independent Researcher · Palo Alto, CA, USA · New York, NY, USA
Thought-Level Beam Search for Reasoning
Aug 8, 2026Lijie Yang, Hongyin Luo, Jiawei Zhao +2Inference-Time Search Efficient Language Model Reasoning
Princeton University · MIT CSAIL · Meta AI
CoBa: Cost-Effective Test-Time Scaling via Compute-Balanced Routing
Aug 7, 2026Yan Zhou, Yue Ouyang, Kaiyang Zheng +1Cost-Aware Inference Test-Time Scaling
School of Mathematics and Statistics, Changsha University of Science and Technology, Changsha, China · School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Graph Machine: Exploring Edge Mechanisms as an Inductive Bias
Aug 7, 2026Lintai HouGraph Structure Learning Neural Algorithmic Reasoning
Iter Labs
Measuring in-context algorithmic reasoning in language models against an exact Bayes-optimal standard
Aug 3, 2026Hector Zenil, Luan OzelimLLM Evaluation Bayesian Inference
Oxford Immune Algorithmics, Oxford University Innovation & London Institute for Healthcare Engineering, U.K · Department of Biomedical Computing, School of Biomedical Engineering and Imaging Sciences & King’s Institute for AI, King’s College London, U.K
Recursive Vision Language Models for General Symbolic Reasoning
Aug 2, 2026Omid Nejati Manzari, Guillaume Lajoie, Hassan RivazSymbolic Reasoning Implicit Reasoning in Language Models
Concordia University, Montreal, Canada · Mila — Quebec AI Institute · Université de Montréal
LeAct: Learning to Reason from Expert Actions
Jul 23, 2026Ziran Yang, Chengshuai Shi, Raj Ghugare +3Imitation Learning Algorithmic Reasoning
Princeton University
When Does Recurrence Become an Algorithm? Convergence Selection in Weight-Tied Looped Transformers
Jul 22, 2026Tong Zhang, Junhao Hu, Yun Peng +1Inference-Time Scaling Length Generalization
Fudan University · Peking University
How to Build Marcus's Algebraic Mind: From Thagard's Brain--Mind Viewpoint
Jul 18, 2026Hiroyuki Chuma, Kanji Otsuka, Yoichi SatoComputational Cognitive Modeling Hyperdimensional Computing
Institute of Innovation Research, Hitotsubashi University (Professor Emeritus) · Meisei University (Professor Emeritus) · Shuhari System
Think Through a Bottleneck: Hourglass Reasoning for Rigorous Induction
Jul 13, 2026Huan ZhuLLM Self-Refinement LLM-Based Program Synthesis
Peking University
Energy-guided Recursive Model
Jul 11, 2026Yifei Zhao, Ying TangInference-Time Search Energy-Based Models
Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China · School of Physics, University of Electronic Science and Technology of China, Chengdu 611731, China
A Symbolic Neural CPU for Quantization-Simulated Writeback and Interpretable Program Execution
Jul 10, 2026Jose Luis Lima de Jesus SilvaNeural Algorithmic Reasoning Neural Network Interpretability
Federal University of Bahia, Department of Geophysics, Salvador, BA 40170-115, Brazil · Grupo de Estudos e Aplicação de Inteligência Artificial em Geofísica (GAIA), Federal University of Bahia, Salvador, BA 40170-115, Brazil
Search, Fail, Recover: A Training Framework for Correction-Aware Reasoning
Jul 8, 2026Dmitry Beresnev, Vladimir Makharev, Roman Khalikov +2LLM Self-Correction Inference-Time Search
Innopolis University, Innopolis, Russia · AXXX, Moscow, Russia · Lomonosov Moscow State University, Moscow, Russia
ClassicLogic: A Knowledge-Driven Benchmark of Classic Puzzle Games for Evaluating Compositional Generalization
Jul 6, 2026Mahnoor Shahid, Hannes RotheLogical Reasoning Benchmark Design
Universität Duisburg-Essen Germany
AlgoBench: Benchmarking Algorithmic Adaptation in Code Generation
Jun 30, 2026Xinyuan Song, Zekun Cai, Liang ZhaoSynthetic Benchmark Generation Code Generation Evaluation
Emory University, Atlanta, GA, USA · The University of Tokyo, Tokyo, Japan · LocationMind, Tokyo, Japan
AlgoSkill: Learning to Design Algorithms by Scheduling Human-Like Skills
Jun 29, 2026Xinyuan Song, Zekun Cai, Liang ZhaoAutomated Algorithm Discovery LLM-Based Program Synthesis
Emory University, Atlanta, GA, USA · The University of Tokyo, Tokyo, Japan · LocationMind, Tokyo, Japan
Flow Reasoning Models: Turning Flows Into Efficient Recurrent Reasoners
Jun 28, 2026Alec Helbling, Andrey Bryutkin, Mauro Martino +3Structured Reasoning Flow-Based Generative Modeling
1Georgia Tech · 3MIT-IBM Computing Research Lab · 4IBM Research +1
Closed-Loop Graph Algorithm Execution with Small Language Models: Step Accuracy and Rollout Reliability
Jun 23, 2026Michal PodstawskiAlgorithmic Reasoning
NASK National Research Institute, Warsaw, Poland

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Efficient Reasoning with Flow Language Models

Hanru Bai, Faissal Izermine, Oscar Davis, T. Konstantin Rusch

Max Planck Institute for Intelligent Systems · ETH Zurich · ELLIS Institute Tübingen+3

Efficient Language Model Reasoning Language Modeling Continuous Latent Reasoning Continuous Diffusion Language Models Algorithmic Reasoning

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Flow Language Models (FLMs) have emerged as a continuous-state alternative to discrete diffusion language models, yet the role of their continuous representations in reasoning remains unclear. We investigate this question by comparing the reasoning efficiency of FLMs and discrete diffusion models, measured by solution accuracy under matched denoising steps. Unlike discrete diffusion, which passes categorical states between denoising steps, FLMs evolve a continuous sequence representation throughout denoising and decodes it into discrete tokens only at the end. Our theoretical analysis shows, from a superposition perspective, how information retained in these continuous states can benefit reasoning. Intermediate-state interventions provide further empirical support for this theoretical account, showing that removing information about alternative candidates reduces subsequent solution recovery. Together, these findings show that FLMs allow evidence for multiple candidates to persist and inform subsequent reasoning before a discrete answer is produced. Furthermore, our experiments on maze planning and Sudoku tasks show that FLMs achieve greater reasoning efficiency in the few-step regime: FLMs achieves higher sequence accuracy than discrete diffusion baselines at matched model sizes and small denoising steps. On maze planning tasks, FLMs can also achieve comparable accuracy with smaller models. For example, on Maze15, FLM reaches the 95% accuracy target at 64 denoising steps with 36.5% fewer parameters than MDLM. These findings point to continuous state spaces as a promising foundation for reasoning models that require fewer refinement steps.

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