MRKL Systems: A modular, Neuro-Symbolic Architecture that Combines Large Language models, External Knowledge Sources and Discrete Reasoning
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Arxiv |
2022 |
Reasoning |
- |
Leveraging Large Language Models to Generate Answer Set Programs
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KR |
2023 |
Reasoning |
Github |
Logic-LM: Empowering Large Language Models with Symbolic Solvers for Faithful Logical Reasoning
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EMNLP |
2023 |
Reasoning |
Github |
LOGIC-LM++: Multi-Step Refinement for Symbolic Formulations
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ACL |
2024 |
Reasoning |
- |
LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers
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EMNLP |
2023 |
Reasoning |
Github |
Faithful Chain-of-Thought Reasoning
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IJCNLP-AACL |
2023 |
Reasoning |
Github |
SATLM: Satisfiability-Aided Language Models Using Declarative Prompting
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NeurIPS |
2023 |
Math Reasoning |
Github |
Faithful Logical Reasoning via Symbolic Chain-of-Thought
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ACL |
2023 |
Reasoning |
Github |
Verification and Refinement of Natural Language Explanations through LLM-Symbolic Theorem Proving
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EMNLP |
2024 |
Theorem Proving |
Github |
StackSight: Unveiling WebAssembly through Large Language Models and Neurosymbolic Chain-of-Thought Decompilation
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ICML |
2024 |
Code Generation |
- |
Monitor-Guided Decoding of Code LMs with Static Analysis of Repository Context
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NeurIPS |
2023 |
Code Generation |
Github |
Solving Math Word Problems by Combining Language Models With Symbolic Solvers
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Arxiv |
2023 |
Math Reasoning |
Github |
AutoSAT: Automatically Optimize SAT Solvers via Large Language Models
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Arxiv |
2024 |
SAT Problem |
Github |
Prototype-then-Refine: A Neuro-Symbolic Approach for Improved Logical Reasoning with LLMs
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Arxiv |
2024 |
Reasoning |
- |
Neuro-Symbolic Integration Brings Causal and Reliable Reasoning Proofs
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Arxiv |
2024 |
Reasoning |
Github |
SymBa: Symbolic Backward Chaining for Structured Natural Language Reasoning
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Arxiv |
2025 |
Reasoning |
Github |
Frugal LMs Trained to Invoke Symbolic Solvers Achieve Parameter-Efficient Arithmetic Reasoning
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AAAI |
2024 |
Math Reasoning |
- |
Lemur: Integrating Large Language Models in Automated Program Verification
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ICLR |
2024 |
Code Generation |
- |
Symbol-LLM: Leverage Language Models for Symbolic System in Visual Human Activity Reasoning
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NeurIPS |
2023 |
Robotics |
Github |
Parsel: Algorithmic Reasoning with Language Models by Composing Decompositions
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NeurIPS |
2023 |
Robotics |
Github |
Disentangling Extraction and Reasoning in Multi-hop Spatial Reasoning
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EMNLP |
2024 |
Spatial Reasoning |
- |
Generalized Planning in PDDL Domains with Pretrained Large Language Models
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AAAI |
2024 |
Planning |
Github |
Leveraging Pre-trained Large Language Models to Construct and Utilize World Models for Model-based Task Planning
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NeurIPS |
2023 |
Planning |
Github |
Coupling Large Language Models with Logic Programming for Robust and General Reasoning from Text
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ACL Findings |
2023 |
Planning |
Github |
LLM+P: Empowering Large Language Models with Optimal Planning Proficiency
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Arxiv |
2023 |
Planning/Robotics |
Github |
Dynamic Planning with a LLM
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LanGame Workshop @ NeurIPS |
2023 |
Planning/Robotics |
- |
Neuro-Symbolic Procedural Planning with Commonsense Prompting
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ICLR |
2023 |
Planning/Robotics |
Github |
Leveraging Environment Interaction for Automated PDDL Translation and Planning with Large Language Models
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NeurIPS |
2024 |
Planning |
Github |
A Framework for Neurosymbolic Robot Action Planning using Large Language Models
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Frontiers in Neurorobotics |
2024 |
Robotics |
Github |
ReKep: Spatio-Temporal Reasoning of Relational Keypoint Constraints for Robotic Manipulation
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Arxiv |
2024 |
Robotics |
- |
LeanDojo: Theorem Proving with Retrieval-Augmented Language Models
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NeurIPS D&B |
2023 |
Theorem Proving |
Github |
LEGO-Prover: Neural Theorem Proving with Growing Libraries
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ICLR |
2024 |
Theorem Proving |
Github |
Proving Olympiad Inequalities by Synergizing LLMs and Symbolic Reasoning
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ICLR |
2025 |
Theorem Proving |
Github |
Autoformalization with Large Language Models
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NeurIPS |
2022 |
Theorem Proving |
- |
Autoformalizing Euclidean Geometry
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ICML |
2024 |
Geometry Reasoning |
Github |
Autoformalize Mathematical Statements by Symbolic Equivalence and Semantic Consistency
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NeurIPS |
2024 |
Theorem Proving |
Github |
Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs
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ICLR |
2023 |
Theorem Proving |
Github |
Don't Trust: Verify -- Grounding LLM Quantitative Reasoning with Autoformalization
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ICLR |
2024 |
Theorem Proving |
Github |
Large Language Models as Planning Domain Generators
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ICAPS |
2024 |
Planning |
Github |
Generating Symbolic World Models via Test-time Scaling of Large Language Models
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ICML |
2024 |
Planning |
- |