:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Lee, Jeyoung, Kang, Hochul
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence Logic in Computer Science
Online Access:	https://arxiv.org/abs/2507.14516
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

SYNAPSE: Synergizing an Adapter and Finetuning for High-Fidelity EEG Synthesis from a CLIP-Aligned Encoder
by: Lee, Jeyoung, et al.
Published: (2025)

Learning Explainable and Better Performing Representations of POMDP Strategies
by: Bork, Alexander, et al.
Published: (2024)

Transfer Learning from Foundational Optimization Embeddings to Unsupervised SAT Representations
by: Pal, Koyena, et al.
Published: (2026)

Regional, Lattice and Logical Representations of Neural Networks
by: Preto, Sandro, et al.
Published: (2025)

Circuit Representations of Random Forests with Applications to XAI
by: Ji, Chunxi, et al.
Published: (2026)

Conflict-Aware Fusion: Mitigating Logic Inertia in Large Language Models via Structured Cognitive Priors
by: Bao, Qiming, et al.
Published: (2025)

Diverse Controllable Diffusion Policy with Signal Temporal Logic
by: Meng, Yue, et al.
Published: (2025)

Model Predictive Robustness of Signal Temporal Logic Predicates
by: Lin, Yuanfei, et al.
Published: (2022)

TGPO: Temporal Grounded Policy Optimization for Signal Temporal Logic Tasks
by: Meng, Yue, et al.
Published: (2025)

Can Transformers Reason Logically? A Study in SAT Solving
by: Pan, Leyan, et al.
Published: (2024)

Structured Abductive-Deductive-Inductive Reasoning for LLMs via Algebraic Invariants
by: Gilda, Sankalp, et al.
Published: (2026)

PiShield: A PyTorch Package for Learning with Requirements
by: Stoian, Mihaela Cătălina, et al.
Published: (2024)

The Geometry of Reasoning: Flowing Logics in Representation Space
by: Zhou, Yufa, et al.
Published: (2025)

A Reinforcement Learning based Reset Policy for CDCL SAT Solvers
by: Li, Chunxiao, et al.
Published: (2024)

Neural DNF-MT: A Neuro-symbolic Approach for Learning Interpretable and Editable Policies
by: Baugh, Kexin Gu, et al.
Published: (2025)

Learning to Solve and Optimize by Evolving Code
by: Semmelrock, Veronika, et al.
Published: (2026)

Robust Shielding for Safe Reinforcement Learning
by: Court, Edwin Hamel-De le, et al.
Published: (2026)

Machine Learning for Quantifier Selection in cvc5
by: Jakubův, Jan, et al.
Published: (2024)

Inductive Generalization in Reinforcement Learning from Specifications
by: Subramanian, Vignesh, et al.
Published: (2024)

SATformer: Transformer-Based UNSAT Core Learning
by: Shi, Zhengyuan, et al.
Published: (2022)

Learning big logical rules by joining small rules
by: Hocquette, Céline, et al.
Published: (2024)

Can Transformers Learn to Verify During Backtracking Search?
by: Phua, Yin Jun, et al.
Published: (2026)

Learning Concepts Definable in First-Order Logic with Counting
by: van Bergerem, Steffen
Published: (2019)

Inference of Abstraction for a Unified Account of Reasoning and Learning
by: Kido, Hiroyuki
Published: (2024)

Compositional Shielding and Reinforcement Learning for Multi-Agent Systems
by: Brorholt, Asger Horn, et al.
Published: (2024)

LeanAgent: Lifelong Learning for Formal Theorem Proving
by: Kumarappan, Adarsh, et al.
Published: (2024)

Compact Rule-Based Classifier Learning via Gradient Descent
by: Fumanal-Idocin, Javier, et al.
Published: (2025)

Learning Brave Assumption-Based Argumentation Frameworks via ASP
by: De Angelis, Emanuele, et al.
Published: (2024)

Reduced Implication-bias Logic Loss for Neuro-Symbolic Learning
by: He, Haoyuan, et al.
Published: (2022)

Learning Temporal Logic Predicates from Data with Statistical Guarantees
by: Soroka, Emi, et al.
Published: (2024)

Multitask Kernel-based Learning with First-Order Logic Constraints
by: Diligenti, Michelangelo, et al.
Published: (2023)

Constraint-aware Learning of Probabilistic Sequential Models for Multi-Label Classification
by: Buleshnyi, Mykhailo, et al.
Published: (2025)

Discovering New Theorems via LLMs with In-Context Proof Learning in Lean
by: Kasaura, Kazumi, et al.
Published: (2025)

Locally Pareto-Optimal Interpretations for Black-Box Machine Learning Models
by: Joshi, Aniruddha, et al.
Published: (2025)

Dualformer: Controllable Fast and Slow Thinking by Learning with Randomized Reasoning Traces
by: Su, DiJia, et al.
Published: (2024)

Machine Learning Model Integration with Open World Temporal Logic for Process Automation
by: Aditya, Dyuman, et al.
Published: (2025)

Value Function Initialization for Knowledge Transfer and Jump-start in Deep Reinforcement Learning
by: Mehimeh, Soumia
Published: (2025)

Learning Logic Specifications for Policy Guidance in POMDPs: an Inductive Logic Programming Approach
by: Meli, Daniele, et al.
Published: (2024)

Do It for HER: First-Order Temporal Logic Reward Specification in Reinforcement Learning (Extended Version)
by: Olivieri, Pierriccardo, et al.
Published: (2026)

THEIA: Learning Complete Kleene Three-Valued Logic in a Pure-Neural Modular Architecture
by: Li, Augustus Haoyang
Published: (2026)