Inference-Time Search

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10 papers in the last four weeks, up 11% on the four weeks before. 0.1% of all new papers.

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LPDP: Inference-Time Reward Control for Variable-Length DNA Generation with Edit Flows
May 12, 2026Jeongchan Kim, Yunkyung Ko, Jong Chul YeInference-Time Search Generative Modeling
KAIST AI
Breaking the Reward Barrier: Accelerating Tree-of-Thought Reasoning via Speculative Exploration
May 11, 2026Shuzhang Zhong, Haochen Huang, Shengxuan Qiu +3Inference-Time Search Tree of Thoughts
Institute for Artificial Intelligence, Peking University · School of Integrated Circuits, Peking University · 3ByteDance Seed
CA-SQL: Complexity-Aware Inference Time Reasoning for Text-to-SQL via Exploration and Compute Budget Allocation
May 8, 2026James Petullo, Nianwen XueInference-Time Search Inference-Time Scaling
Brandeis University / Waltham, MA
Inference-Time Budget Control for LLM Search Agents
May 7, 2026Zhengru Fang, Senkang Forest Hu, Zhonghao Chang +6Multi-Hop QA Inference-Time Search
City University of Hong Kong · Tsinghua University · Alibaba Ant Group
Where Reasoning Breaks: Logic-Aware Path Selection by Controlling Logical Connectives in LLMs Reasoning Chains
Apr 22, 2026Seunghyun Park, Yuanyuan LeiInference-Time Search RL for Language Model Reasoning
Independent Researcher · University of Florida Gainesville, FL, United States
Efficient Test-Time Inference via Deterministic Exploration of Truncated Decoding Trees
Apr 22, 2026Xueyan Li, Johannes Zenn, Ekaterina Fadeeva +3Language Model Decoding Inference-Time Search
Max Planck Institute for Intelligent Systems · ETH Zurich · AI Center Tübingen +3
RosettaSearch: Multi-Objective Inference-Time Search for Protein Sequence Design
Apr 19, 2026Meghana Kshirsagar, Allen Nie, Ching-An Cheng +5Inference-Time Search Large Language Model-Guided Optimization
AI for Good, Microsoft Redmond · Google DeepMind · Google Research +3
NCO4CVRP: Neural Combinatorial Optimization for the Capacitated Vehicle Routing Problem
Apr 17, 2026Mahir Labib Dihan, Md. Ashrafur Rahman Khan, Wasif Jalal +2Inference-Time Search Metaheuristic Optimization
Department of Computer Science and Engineering Bangladesh University of Engineering and Technology
PAC-CF: Calibrating Irreversible Frontier Pruning in LLM-Guided Search
Apr 15, 2026Tianhao Qian, Jiayu Chen, Zhenyu Sun +1LLM Inference Efficiency Inference-Time Search
FormalEvolve: Neuro-Symbolic Evolutionary Search for Diverse Autoformalization
Mar 20, 2026Haijian Lu, Wei Wang, Jing LiuAutoformalization Inference-Time Search
School of Artificial Intelligence, Xidian University, Xi’an, China · Beijing Institute for General Artificial Intelligence, Beijing, China
Efficient K-generalizable Learned Search
Mar 6, 2026Yifan Peng, Jiafei Fan, Xingda Wei +7Inference-Time Search Graph-Based Retrieval
Shanghai Jiao Tong University · Boston University · Alibaba Group
What If We Allocate Test-Time Compute Adaptively?
Feb 1, 2026Ahsan Bilal, Ahmed Mohsin, Muhammad Umer +4Inference-Time Search Test-Time Scaling
University of Oklahoma, OK, USA · Stanford University, CA, USA · Universitat Pompeu Fabra, Barcelona, Spain +2
Inference-Time Diversity in RL-Trained Lean Theorem Provers: A Diagnostic Study
Jan 22, 2026Zachary BurtonInference-Time Search RL for Language Model Reasoning
Massachusetts Institute of Technology, Cambridge, MA, USA.
Scalable Decision Making for Games of Imperfect Information
Nov 10, 2025Samuel Sokota, Eugene Vinitsky, Hengyuan Hu +3Game-Playing Agents Inference-Time Search
Carnegie Mellon University · NYU Tandon School of Engineering · Stanford University +1
MASPRM: Multi-Agent System Process Reward Model
Oct 28, 2025Milad Yazdani, Mahdi Mostajabdaveh, Zirui Zhou +1Multi-Agent LLM Systems Inference-Time Search
Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC V6T1Z4, Canada · Huawei Technologies Canada, Burnaby, BC V5C6S7, Canada

May 12, 2026, cs.LGJ/K move · Enter open · S save

LPDP: Inference-Time Reward Control for Variable-Length DNA Generation with Edit Flows

Jeongchan Kim, Yunkyung Ko, Jong Chul Ye

KAIST AI

Inference-Time Search Generative Modeling Molecular Generation Genomics Inference-Time Guidance

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We study the application of recent Edit Flows for inference-time reward control for DNA sequence generation. Unlike most reward-guided DNA generation frameworks, which operate on fixed-length sequence spaces, Edit Flows have a potential to generate variable-length DNA through biologically plausible insertion, deletion, and substitution operations. In particular, we propose Local Perturbation Discrete Programming (LPDP), a training-free, intermediate-state and action-aware local re-solving operator for variable-length DNA edit-action generators at inference time. More specifically, at each guided rollout step, LPDP scores one-step root edits, retains a near-best root band, and re-ranks each retained root by solving a bounded local discrete program around its child sequence. This local program uses the typed geometry of edit actions to focus on coherent substitution, insertion, or deletion subgraphs, and aggregates local continuations with either a hard Max backup or a soft log-sum-exponential (LSE) backup. We instantiate LPDP in two regimes: front-loaded reward tilting for enhancer optimization, where early edits are critical for establishing global regulatory sequence structure, and back-loaded reward tilting for exon-intron-exon inpainting, where late edits fine-tune splice-boundary contexts.

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