Cover Image

Correlation or Causation: Analyzing the Causal Structures of LLM and LRM Reasoning Process

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	FU, Zhizhang, Bao, Guangsheng, Zhang, Hongbo, Hu, Chenkai, Zhang, Yue
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

ReEfBench: Quantifying the Reasoning Efficiency of LLMs
by: Fu, Zhizhang, et al.
Published: (2026)

Detecting RLVR Training Data via Structural Convergence of Reasoning
by: Zhang, Hongbo, et al.
Published: (2026)

How Likely Do LLMs with CoT Mimic Human Reasoning?
by: Bao, Guangsheng, et al.
Published: (2024)

Direct Value Optimization: Improving Chain-of-Thought Reasoning in LLMs with Refined Values
by: Zhang, Hongbo, et al.
Published: (2025)

Glimpse: Enabling White-Box Methods to Use Proprietary Models for Zero-Shot LLM-Generated Text Detection
by: Bao, Guangsheng, et al.
Published: (2024)

CoT-Kinetics: A Theoretical Modeling Assessing LRM Reasoning Process
by: Bi, Jinhe, et al.
Published: (2025)

Evaluating the Logical Reasoning Abilities of Large Reasoning Models
by: Liu, Hanmeng, et al.
Published: (2025)

JudgeLRM: Large Reasoning Models as a Judge
by: Chen, Nuo, et al.
Published: (2025)

Actual Causation and Nondeterministic Causal Models
by: Beckers, Sander
Published: (2025)

QuantLRM: Quantization of Large Reasoning Models via Fine-Tuning Signals
by: Zhang, Nan, et al.
Published: (2026)

Bounding Probabilities of Causation with Partial Causal Diagrams
by: Xie, Yuxuan, et al.
Published: (2026)

Correlation to Causation: A Causal Deep Learning Framework for Arctic Sea Ice Prediction
by: Hossain, Emam, et al.
Published: (2025)

CycleResearcher: Improving Automated Research via Automated Review
by: Weng, Yixuan, et al.
Published: (2024)

Break the Chain: Large Language Models Can be Shortcut Reasoners
by: Ding, Mengru, et al.
Published: (2024)

Logical Reasoning in Large Language Models: A Survey
by: Liu, Hanmeng, et al.
Published: (2025)

Trustworthy Reasoning: Evaluating and Enhancing Factual Accuracy in LLM Intermediate Thought Processes
by: Jiao, Rui, et al.
Published: (2025)

UDA: Unsupervised Debiasing Alignment for Pair-wise LLM-as-a-Judge
by: Zhang, Yang, et al.
Published: (2025)

CSCE: Boosting LLM Reasoning by Simultaneous Enhancing of Causal Significance and Consistency
by: Wang, Kangsheng, et al.
Published: (2024)

Knows: Agent-Native Structured Research Representations
by: Yu, Guangsheng, et al.
Published: (2026)

Decoupling Content and Expression: Two-Dimensional Detection of AI-Generated Text
by: Bao, Guangsheng, et al.
Published: (2025)

Can Large Language Models Infer Causation from Correlation?
by: Jin, Zhijing, et al.
Published: (2023)

Mediation Analysis for Probabilities of Causation
by: Kawakami, Yuta, et al.
Published: (2024)

Beyond Reactive Safety: Risk-Aware LLM Alignment via Long-Horizon Simulation
by: Sun, Chenkai, et al.
Published: (2025)

Probabilities of Causation for Continuous and Vector Variables
by: Kawakami, Yuta, et al.
Published: (2024)

Control Synthesis of Cyber-Physical Systems for Real-Time Specifications through Causation-Guided Reinforcement Learning
by: Tang, Xiaochen, et al.
Published: (2025)

Prompting Strategies for Enabling Large Language Models to Infer Causation from Correlation
by: Sgouritsa, Eleni, et al.
Published: (2024)

Planning in Strawberry Fields: Evaluating and Improving the Planning and Scheduling Capabilities of LRM o1
by: Valmeekam, Karthik, et al.
Published: (2024)

Grounding Multi-Hop Reasoning in Structural Causal Models via Group Relative Policy Optimization
by: Bu, Yunhan, et al.
Published: (2026)

Estimating Probabilities of Causation with Machine Learning Models
by: Wang, Shuai, et al.
Published: (2025)

Towards a Benchmark for Causal Business Process Reasoning with LLMs
by: Fournier, Fabiana, et al.
Published: (2024)

Decomposition of Probabilities of Causation with Two Mediators
by: Kawakami, Yuta, et al.
Published: (2025)

Causal Temporal Reasoning for Markov Decision Processes
by: Kazemi, Milad, et al.
Published: (2022)

Causal Strengths and Leaky Beliefs: Interpreting LLM Reasoning via Noisy-OR Causal Bayes Nets
by: Dettki, Hanna
Published: (2025)

To Analyze and Regulate Human-in-the-loop Learning for Congestion Games
by: Li, Hongbo, et al.
Published: (2025)

LRM: Large Reconstruction Model for Single Image to 3D
by: Hong, Yicong, et al.
Published: (2023)

Causality-informed Anomaly Detection in Partially Observable Sensor Networks: Moving beyond Correlations
by: Xiao, Xiaofeng, et al.
Published: (2025)

Graph of Verification: Structured Verification of LLM Reasoning with Directed Acyclic Graphs
by: Fang, Jiwei, et al.
Published: (2025)

CausalStep: A Benchmark for Explicit Stepwise Causal Reasoning in Videos
by: Li, Xuchen, et al.
Published: (2025)

Time Series Reasoning via Process-Verifiable Thinking Data Synthesis and Scheduling for Tailored LLM Reasoning
by: Zhou, Jiahui, et al.
Published: (2026)

ARGORA: Orchestrated Argumentation for Causally Grounded LLM Reasoning and Decision Making
by: Jin, Youngjin, et al.
Published: (2026)