Constraint-Guided Reasoning in Language Models

Latest papers

15 papers1 paper in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

Repairing LLM-Generated Specifications with Deterministic Diagnosis
Oct 15, 2026Giovanni Vaccarino, Emanuele La Malfa, Dehai Min +6Autoformalization LLM Self-Correction
Department of Computer Science, University of Oxford, Oxford, UK · Department of Computer Science, University of Illinois Chicago, Chicago, IL, USA · Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy +2
MolDesignBench: Evaluating LLM-based Agent for Scenario-grounded Molecular Design
Sep 23, 2026Yongjun Jeong, Hanbum Ko, Ye Rin Kim +6Molecular Optimization LLM Agent Evaluation
Department of Artificial Intelligence, Korea University · LG AI Research · Department of Statistics, Korea University
From Token Probabilities to Semantic Constraints: Towards Declarative Probabilistic Evaluation of Language Models
Sep 11, 2026Kyle Richardson, Cullen Anderson, Pranav Balakrishnan +4Constraint-Guided Reasoning in Language Models LLM Evaluation
Allen Institute for AI · University of Massachusetts Amherst
Linear Temporal Logic Translation via Human-Inspired Self-Constrained Reasoning for Robot Task Specification
Aug 28, 2026Haofei Hou, Fanxu Meng, Shunyi Zhao +4Constraint-Guided Reasoning in Language Models Linear Temporal Logic
School of Advanced Manufacturing and Robotics, Peking University, Beijing 100871, China. · School of Integrated Circuits, Peking University, Beijing 100871, China.
Solver-Guided Reasoning for Mixed-Equilibrium Strategies
Aug 7, 2026Han Wang, Philippe Beardsell, Boning Li +4Nash Equilibrium Game-Playing Agents
Shanghai Jiao Tong University · GTO Wizard · Tsinghua University +2
Constrained Path Reasoning: Measuring When Committed Stages Earn Their Cost
Jul 19, 2026Honglin LiLLM Inference Efficiency Inference-Time Search
ShanghaiTech University
Where Larger Models Excel: The Primacy of Constraint-Guided Reasoning
May 9, 2026Guan-Yi Lin, Hen-Hsen HuangLanguage Model Scaling Laws LLM Reasoning
National Chengchi University Taipei, Taiwan · Academia Sinica Taipei, Taiwan
Heuristic Classification of Thoughts Prompting (HCoT): Integrating Expert System Heuristics for Structured Reasoning into Large Language Models
Apr 14, 2026Lei Lin, Jizhao Zhu, Yong Liu +3Structured Reasoning in Language Models Constraint-Guided Reasoning in Language Models
Computer Network Information Center, Chinese Academy of Sciences, Beijing, China · Shenyang Aerospace University · ZGC LAB, Beijing,China +1
The Model Says Walk: Measuring whether LLMs Condition on Hidden Constraints
Mar 30, 2026Yubo Li, Lu Zhang, Tianchong Jiang +2Constraint-Guided Reasoning in Language Models Implicit Reasoning in Language Models
Carnegie Mellon University · Independent Researcher
Can Large Language Models Reason and Optimize Under Constraints?
Mar 24, 2026Fabien Bernier, Salah Ghamizi, Pantelis Dogoulis +1Constraint-Guided Reasoning in Language Models LLM Evaluation
SnT – University of Luxembourg, Luxembourg · Luxembourg Institute of Health (LIH), Luxembourg
TopoBench: Benchmarking LLMs on Hard Topological Reasoning
Mar 12, 2026Mayug Maniparambil, Nils Hoehing, Janak Kapuriya +5Constraint-Guided Reasoning in Language Models Spatial Reasoning Benchmarks
Intercom Research · University College Dublin · University of Galway +3
ConstraintBench: Benchmarking LLM Constraint Reasoning on Direct Optimization
Feb 25, 2026Joseph Tso, Preston Schmittou, Quan Huynh +1Constraint-Guided Reasoning in Language Models Constrained Optimization
Haladir Research Team
Prompt Architecture Determines Reasoning Quality: A Variable Isolation Study on the Car Wash Problem
Feb 25, 2026Heejin JoStructured Reasoning in Language Models Prompt Engineering
Independent Researcher
Neurosymbolic Language Reasoning as Satisfiability Modulo Theory
Feb 20, 2026Hyunseok Oh, Sam Stern, Youngki Lee +1Constraint-Guided Reasoning in Language Models Neuro-Symbolic Reasoning
Seoul National University · U. Mass. Amherst · Microsoft
Broken Chains: The Cost of Incomplete Reasoning in LLMs
Feb 16, 2026Ian Su, Gaurav Purushothaman, Jey Narayan +5LLM Reasoning CoT Reasoning

Oct 15, 2026J/K move · Enter open · S save

Repairing LLM-Generated Specifications with Deterministic Diagnosis

Giovanni Vaccarino, Emanuele La Malfa, Dehai Min, Hanrong Zhang+5

Department of Computer Science, University of Oxford, Oxford, UK · Department of Computer Science, University of Illinois Chicago, Chicago, IL, USA · Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy+2

Autoformalization LLM Self-Correction Constraint-Guided Reasoning in Language Models

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Large language models (LLMs) are increasingly used as formalizers: given a reasoning problem expressed in natural language, they produce a formal specification that a symbolic solver can then solve, with guarantees relative to that specification. Many specifications are runnable yet semantically wrong, encoding incorrect constraints, domains, objectives, predicates, or goals, and solver-error feedback dries up once execution succeeds. Purely LLM-based diagnosis, lacking a formal ground truth, often fails to spot these errors, and its ungrounded critiques cause regressions in 11.8% of initially correct specifications in our experiments. We propose DRAGO, a repair framework that replaces this ungrounded critique with deterministic, formalism-specific diagnosis, and retains a rewrite only when the diagnosed error weight strictly decreases under a reference-free acceptance predicate. Across five benchmarks spanning logical reasoning (SMT-LIB2), constraint programming (MiniZinc), and planning (PDDL), DRAGO cuts regressions by nearly an order of magnitude, to 1.3%, while improving answer accuracy by 12.9 percentage points over zero-shot formalization and 8.7 percentage points over LLM-diagnostic repair, averaged across benchmarks. We also uncover two rendering defects in Planetarium that cause 50% (3,086 instances) of its floor-tile split to be inconsistent with the reference formalizations, and release a corrected split.