SAT-RL: Training Language Models for Logical Reasoning with Symbolic Solvers
cs.AI, cs.SC
Submitted: 2026-10-09
Updated: 2026-10-09
Sources
- FullStack Bench: Evaluating LLMs as Full Stack Coders
- Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models
- ReTool: Reinforcement Learning for Strategic Tool Use in LLMs
- DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
- On-Policy RL with Optimal Reward Baseline
- REINFORCE++: Stabilizing Critic-Free Policy Optimization with Global Advantage Normalization
- HardcoreLogic: Challenging Large Reasoning Models with Long-tail Logic Puzzle Games
- FCoReBench: Can Large Language Models Solve Challenging First-Order Combinatorial Reasoning Problems?
- Logic-LM: Empowering Large Language Models with Symbolic Solvers for Faithful Logical Reasoning
- Large Language Models Meet Symbolic Provers for Logical Reasoning Evaluation
- DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition
- Proximal Policy Optimization Algorithms
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
- OpenAI GPT-5 System Card
- MCP-Solver: Integrating Language Models with Constraint Programming Systems
- Qwen3.5-Omni Technical Report
- Self-Consistency Improves Chain of Thought Reasoning in Language Models
- Self-Play Preference Optimization for Language Model Alignment
- DAPO: An Open-Source LLM Reinforcement Learning System at Scale
- AR-LSAT: Investigating Analytical Reasoning of Text
Related papers
- MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
- Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
- Agents' Last Exam
- The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
- MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
- Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems