:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Peng, Mengmeng, Fang, Zhenyu, Sun, He
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2601.10810
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

Neural Probabilistic Logic Learning for Knowledge Graph Reasoning
by: Sun, Fengsong, et al.
Published: (2024)

Logical Distillation of Graph Neural Networks
by: Pluska, Alexander, et al.
Published: (2024)

eXpLogic: Explaining Logic Types and Patterns in DiffLogic Networks
by: Wormald, Stephen, et al.
Published: (2025)

Propositional Logic for Probing Generalization in Neural Networks
by: Langedijk, Anna, et al.
Published: (2025)

From Arithmetic to Logic: The Resilience of Logic and Lookup-Based Neural Networks Under Parameter Bit-Flips
by: Bacellar, Alan T. L., et al.
Published: (2026)

Neuro-Logic Lifelong Learning
by: He, Bowen, et al.
Published: (2025)

Standard Neural Computation Alone Is Insufficient for Logical Intelligence
by: Kim, Youngsung
Published: (2025)

LogicTree: Structured Proof Exploration for Coherent and Rigorous Logical Reasoning with Large Language Models
by: He, Kang, et al.
Published: (2025)

Review of Digital Asset Development with Graph Neural Network Unlearning
by: Lisbon, Zara
Published: (2024)

CKnowEdit: A New Chinese Knowledge Editing Dataset for Linguistics, Facts, and Logic Error Correction in LLMs
by: Fang, Jizhan, et al.
Published: (2024)

Towards Probabilistic Inductive Logic Programming with Neurosymbolic Inference and Relaxation
by: Hillerstrom, Fieke, et al.
Published: (2024)

Variable Assignment Invariant Neural Networks for Learning Logic Programs
by: Phua, Yin Jun, et al.
Published: (2024)

EXPLAIN, AGREE, LEARN: Scaling Learning for Neural Probabilistic Logic
by: Verreet, Victor, et al.
Published: (2024)

Towards Aligned Data Removal via Twin Machine Unlearning
by: Ji, Haoxuan, et al.
Published: (2024)

Towards a Mechanistic Understanding of Propositional Logical Reasoning in Large Language Models
by: Chen, Danchun, et al.
Published: (2026)

Neural Logic Networks for Interpretable Classification
by: Perreault, Vincent, et al.
Published: (2025)

Subjective Logic Encodings
by: Vasilakes, Jake, et al.
Published: (2025)

Towards Explainable Indoor Localization: Interpreting Neural Network Learning on Wi-Fi Fingerprints Using Logic Gates
by: Gufran, Danish, et al.
Published: (2025)

How Explanations Leak the Decision Logic: Stealing Graph Neural Networks via Explanation Alignment
by: Ma, Bin, et al.
Published: (2025)

The Logical Expressiveness of Temporal GNNs via Two-Dimensional Product Logics
by: Sälzer, Marco, et al.
Published: (2025)

Logic-Guided Multistage Inference for Explainable Multidefendant Judgment Prediction
by: Zhang, Xu, et al.
Published: (2026)

LLM Unlearning via Neural Activation Redirection
by: Shen, William F., et al.
Published: (2025)

ZebraLogic: On the Scaling Limits of LLMs for Logical Reasoning
by: Lin, Bill Yuchen, et al.
Published: (2025)

Federated Knowledge Graph Unlearning via Diffusion Model
by: Liu, Bingchen, et al.
Published: (2024)

Interpretable Classification via a Rule Network with Selective Logical Operators
by: Wei, Bowen, et al.
Published: (2024)

Logical Structure as Knowledge: Enhancing LLM Reasoning via Structured Logical Knowledge Density Estimation
by: Bi, Zhen, et al.
Published: (2025)

Improving Neural-based Classification with Logical Background Knowledge
by: Ledaguenel, Arthur, et al.
Published: (2024)

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

Enhancing Time Series Forecasting via Logic-Inspired Regularization
by: Zhang, Jianqi, et al.
Published: (2025)

Neural Probabilistic Circuits: Enabling Compositional and Interpretable Predictions through Logical Reasoning
by: Chen, Weixin, et al.
Published: (2025)

Explaining Neural Networks in Preference Learning: a Post-hoc Inductive Logic Programming Approach
by: Fossemò, Daniele, et al.
Published: (2026)

Label Distribution Learning from Logical Label
by: Jia, Yuheng, et al.
Published: (2023)

ChaosBench-Logic v2: Evaluating LLM Logical Reasoning over Dynamical Systems at Scale
by: Thomas, Noel
Published: (2026)

Towards Symbolic XAI -- Explanation Through Human Understandable Logical Relationships Between Features
by: Schnake, Thomas, et al.
Published: (2024)

Poisoning the Inner Prediction Logic of Graph Neural Networks for Clean-Label Backdoor Attacks
by: Zhang, Yuxiang, et al.
Published: (2026)

Self-Supervised Inductive Logic Programming
by: Patsantzis, Stassa
Published: (2025)

Improving Chain-of-Thought for Logical Reasoning via Attention-Aware Intervention
by: Phuong, Nguyen Minh, et al.
Published: (2026)

Logic Synthesis Optimization with Predictive Self-Supervision via Causal Transformers
by: Karimi, Raika, et al.
Published: (2024)

Comparing Neural Network Encodings for Logic-based Explainability
by: Carvalho, Levi Cordeiro, et al.
Published: (2025)