Cover Image

ChaosBench-Logic v2: Evaluating LLM Logical Reasoning over Dynamical Systems at Scale

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Thomas, Noel
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

ChaosBench-Logic: A Benchmark for Logical and Symbolic Reasoning on Chaotic Dynamical Systems
by: Thomas, Noel
Published: (2026)

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

Reasoning-as-Logic-Units: Scaling Test-Time Reasoning in Large Language Models Through Logic Unit Alignment
by: Li, Cheryl, et al.
Published: (2025)

Temporal Inductive Logic Reasoning over Hypergraphs
by: Yang, Yuan, et al.
Published: (2022)

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

Temporalizing Confidence: Evaluation of Chain-of-Thought Reasoning with Signal Temporal Logic
by: Mao, Zhenjiang, et al.
Published: (2025)

DivLogicEval: A Framework for Benchmarking Logical Reasoning Evaluation in Large Language Models
by: Chung, Tsz Ting, et al.
Published: (2025)

ActivationReasoning: Logical Reasoning in Latent Activation Spaces
by: Helff, Lukas, et al.
Published: (2025)

LogicVista: Multimodal LLM Logical Reasoning Benchmark in Visual Contexts
by: Xiao, Yijia, et al.
Published: (2024)

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

LLM-Assisted Logic Rule Learning: Scaling Human Expertise for Time Series Anomaly Detection
by: Zhang, Haoting, et al.
Published: (2026)

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

Efficient Learning of Fuzzy Logic Systems for Large-Scale Data Using Deep Learning
by: Koklu, Ata, et al.
Published: (2024)

LGMT: Logic-Grounded Metamorphic Testing for Evaluating the Reasoning Reliability of LLMs
by: Zhou, Zenghui, et al.
Published: (2026)

The Tsetlin Machine Goes Deep: Logical Learning and Reasoning With Graphs
by: Granmo, Ole-Christoffer, et al.
Published: (2025)

A Foundation Model for Zero-shot Logical Query Reasoning
by: Galkin, Mikhail, et al.
Published: (2024)

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

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

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

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

SLR: Automated Synthesis for Scalable Logical Reasoning
by: Helff, Lukas, et al.
Published: (2025)

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

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

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

SATQuest: A Verifier for Logical Reasoning Evaluation and Reinforcement Fine-Tuning of LLMs
by: Zhao, Yanxiao, et al.
Published: (2025)

Modeling Relational Patterns for Logical Query Answering over Knowledge Graphs
by: He, Yunjie, et al.
Published: (2023)

Zadeh's Type-2 Fuzzy Logic Systems: Precision and High-Quality Prediction Intervals
by: Guven, Yusuf, et al.
Published: (2024)

Enhancing Interval Type-2 Fuzzy Logic Systems: Learning for Precision and Prediction Intervals
by: Koklu, Ata, et al.
Published: (2024)

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

FormInv: A Measurement Protocol for Semantic Invariance in Mathematical Reasoning Benchmarks
by: Thomas, Nishal, et al.
Published: (2026)

LogicGuard: Improving Embodied LLM agents through Temporal Logic based Critics
by: Gokhale, Anand, 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)

Learning to Generate Formally Verifiable Step-by-Step Logic Reasoning via Structured Formal Intermediaries
by: Chen, Luoxin, et al.
Published: (2026)

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

LLM Assertiveness can be Mechanistically Decomposed into Emotional and Logical Components
by: Tsujimura, Hikaru, et al.
Published: (2025)

ChaosNetBench: Benchmarking Spatio-Temporal Graph Neural Networks on Chaotic Lattice Dynamics
by: Moges, Henok Tenaw, et al.
Published: (2026)

Logical Specifications-guided Dynamic Task Sampling for Reinforcement Learning Agents
by: Shukla, Yash, et al.
Published: (2024)

A Implies B: Circuit Analysis in LLMs for Propositional Logical Reasoning
by: Hong, Guan Zhe, et al.
Published: (2024)

Disentangling Logic: The Role of Context in Large Language Model Reasoning Capabilities
by: Hua, Wenyue, et al.
Published: (2024)

Program Synthesis using Inductive Logic Programming for the Abstraction and Reasoning Corpus
by: Rocha, Filipe Marinho, et al.
Published: (2024)