CLEAR: Can Language Models Really Understand Causal Graphs?
Fuente:
arXiv
Saved in:
| Main Authors: | Chen, Sirui, Xu, Mengying, Wang, Kun, Zeng, Xingyu, Zhao, Rui, Zhao, Shengjie, Lu, Chaochao |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Causal Evaluation of Language Models
by: Chen, Sirui, et al.
Published: (2024)
by: Chen, Sirui, et al.
Published: (2024)
Enhancing Causal Reasoning in Large Language Models: A Causal Attribution Model for Precision Fine-Tuning
by: Cai, Hengrui, et al.
Published: (2023)
by: Cai, Hengrui, et al.
Published: (2023)
Can Post-Training Transform LLMs into Causal Reasoners?
by: Chen, Junqi, et al.
Published: (2026)
by: Chen, Junqi, et al.
Published: (2026)
CauScientist: Teaching LLMs to Respect Data for Causal Discovery
by: Peng, Bo, et al.
Published: (2026)
by: Peng, Bo, et al.
Published: (2026)
Can Large Language Models Help Experimental Design for Causal Discovery?
by: Li, Junyi, et al.
Published: (2025)
by: Li, Junyi, et al.
Published: (2025)
Language Models as Causal Effect Generators
by: Bynum, Lucius E. J., et al.
Published: (2024)
by: Bynum, Lucius E. J., et al.
Published: (2024)
Efficient Causal Graph Discovery Using Large Language Models
by: Jiralerspong, Thomas, et al.
Published: (2024)
by: Jiralerspong, Thomas, et al.
Published: (2024)
Discovering and Reasoning of Causality in the Hidden World with Large Language Models
by: Liu, Chenxi, et al.
Published: (2024)
by: Liu, Chenxi, et al.
Published: (2024)
Industrial-Grade Smart Troubleshooting through Causal Technical Language Processing: a Proof of Concept
by: Trilla, Alexandre, et al.
Published: (2024)
by: Trilla, Alexandre, et al.
Published: (2024)
From Imitation to Introspection: Probing Self-Consciousness in Language Models
by: Chen, Sirui, et al.
Published: (2024)
by: Chen, Sirui, et al.
Published: (2024)
Causal Diffusion Autoencoders: Toward Counterfactual Generation via Diffusion Probabilistic Models
by: Komanduri, Aneesh, et al.
Published: (2024)
by: Komanduri, Aneesh, et al.
Published: (2024)
Text Rationalization for Robust Causal Effect Estimation
by: Zhang, Lijinghua, et al.
Published: (2025)
by: Zhang, Lijinghua, et al.
Published: (2025)
A Causal Lens for Evaluating Faithfulness Metrics
by: Zaman, Kerem, et al.
Published: (2025)
by: Zaman, Kerem, et al.
Published: (2025)
RCT Rejection Sampling for Causal Estimation Evaluation
by: Keith, Katherine A., et al.
Published: (2023)
by: Keith, Katherine A., et al.
Published: (2023)
DEPO: Dual-Efficiency Preference Optimization for LLM Agents
by: Chen, Sirui, et al.
Published: (2025)
by: Chen, Sirui, et al.
Published: (2025)
ALCM: Autonomous LLM-Augmented Causal Discovery Framework
by: Khatibi, Elahe, et al.
Published: (2024)
by: Khatibi, Elahe, et al.
Published: (2024)
Language Agents Meet Causality -- Bridging LLMs and Causal World Models
by: Gkountouras, John, et al.
Published: (2024)
by: Gkountouras, John, et al.
Published: (2024)
Beyond Surface Structure: A Causal Assessment of LLMs' Comprehension Ability
by: Han, Yujin, et al.
Published: (2024)
by: Han, Yujin, et al.
Published: (2024)
Evaluating Interventional Reasoning Capabilities of Large Language Models
by: Kasetty, Tejas, et al.
Published: (2024)
by: Kasetty, Tejas, et al.
Published: (2024)
Causal Preference Elicitation
by: Bonilla, Edwin V., et al.
Published: (2026)
by: Bonilla, Edwin V., et al.
Published: (2026)
Integrating Large Language Models in Causal Discovery: A Statistical Causal Approach
by: Takayama, Masayuki, et al.
Published: (2024)
by: Takayama, Masayuki, et al.
Published: (2024)
Causal Reasoning and Large Language Models: Opening a New Frontier for Causality
by: Kıcıman, Emre, et al.
Published: (2023)
by: Kıcıman, Emre, et al.
Published: (2023)
Causal State Distillation for Explainable Reinforcement Learning
by: Lu, Wenhao, et al.
Published: (2023)
by: Lu, Wenhao, et al.
Published: (2023)
A Recipe for Causal Graph Regression: Confounding Effects Revisited
by: Yin, Yujia, et al.
Published: (2025)
by: Yin, Yujia, et al.
Published: (2025)
A General Causal Inference Framework for Cross-Sectional Observational Data
by: Zhao, Yonghe, et al.
Published: (2024)
by: Zhao, Yonghe, et al.
Published: (2024)
CausalGuard: Conformal Inference under Graph Uncertainty
by: Singh, Vikash, et al.
Published: (2026)
by: Singh, Vikash, et al.
Published: (2026)
Metacognition as Reward: Reinforcing LLM Reasoning via Knowledge and Regulation Signals
by: Chen, Sirui, et al.
Published: (2026)
by: Chen, Sirui, et al.
Published: (2026)
Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables
by: Xie, Feng, et al.
Published: (2023)
by: Xie, Feng, et al.
Published: (2023)
Learning Causal Abstractions of Linear Structural Causal Models
by: Massidda, Riccardo, et al.
Published: (2024)
by: Massidda, Riccardo, et al.
Published: (2024)
Multi-Domain Causal Discovery in Bijective Causal Models
by: Jalaldoust, Kasra, et al.
Published: (2025)
by: Jalaldoust, Kasra, et al.
Published: (2025)
Causal Concept Graphs in LLM Latent Space for Stepwise Reasoning
by: Meherab, Md Muntaqim, et al.
Published: (2026)
by: Meherab, Md Muntaqim, et al.
Published: (2026)
RealTCD: Temporal Causal Discovery from Interventional Data with Large Language Model
by: Li, Peiwen, et al.
Published: (2024)
by: Li, Peiwen, et al.
Published: (2024)
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook
by: Jiang, Wenzhao, et al.
Published: (2023)
by: Jiang, Wenzhao, et al.
Published: (2023)
Towards Causal Foundation Model: on Duality between Causal Inference and Attention
by: Zhang, Jiaqi, et al.
Published: (2023)
by: Zhang, Jiaqi, et al.
Published: (2023)
Enhancing Maritime Trajectory Forecasting via H3 Index and Causal Language Modelling (CLM)
by: Drapier, Nicolas, et al.
Published: (2024)
by: Drapier, Nicolas, et al.
Published: (2024)
HOLOGRAPH: Active Causal Discovery via Sheaf-Theoretic Alignment of Large Language Model Priors
by: Kim, Hyunjun
Published: (2025)
by: Kim, Hyunjun
Published: (2025)
Rating Multi-Modal Time-Series Forecasting Models (MM-TSFM) for Robustness Through a Causal Lens
by: Lakkaraju, Kausik, et al.
Published: (2024)
by: Lakkaraju, Kausik, et al.
Published: (2024)
Synthesis by Design: Controlled Data Generation via Structural Guidance
by: Xu, Lei, et al.
Published: (2025)
by: Xu, Lei, et al.
Published: (2025)
On the Granularity of Causal Effect Identifiability
by: Chen, Yizuo, et al.
Published: (2025)
by: Chen, Yizuo, et al.
Published: (2025)
AutoEval Done Right: Using Synthetic Data for Model Evaluation
by: Boyeau, Pierre, et al.
Published: (2024)
by: Boyeau, Pierre, et al.
Published: (2024)
Similar Items
-
Causal Evaluation of Language Models
by: Chen, Sirui, et al.
Published: (2024) -
Enhancing Causal Reasoning in Large Language Models: A Causal Attribution Model for Precision Fine-Tuning
by: Cai, Hengrui, et al.
Published: (2023) -
Can Post-Training Transform LLMs into Causal Reasoners?
by: Chen, Junqi, et al.
Published: (2026) -
CauScientist: Teaching LLMs to Respect Data for Causal Discovery
by: Peng, Bo, et al.
Published: (2026) -
Can Large Language Models Help Experimental Design for Causal Discovery?
by: Li, Junyi, et al.
Published: (2025)