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Causal Inference

3310 directly classified papers

Papers per year

Papers

Causally Aware Generative Adversarial Networks for Light Pollution Control AAAI 2024

Spatial-Logic-Aware Weakly Supervised Learning for Flood Mapping on Earth Imagery AAAI 2024

JFLD: A Japanese Benchmark for Deductive Reasoning Based on Formal Logic COLING 2024

A Bayesian Spatial Model to Correct Under-Reporting in Urban Crowdsourcing AAAI 2024

Neural Causal Abstractions AAAI 2024

Is Structure Dependence Shaped for Efficient Communication?: A Case Study on Coordination EMNLP 2024

Large Language Model Recall Uncertainty is Modulated by the Fan Effect EMNLP 2024

Identifying General Mechanism Shifts in Linear Causal Representations NIPS 2024

JEMHopQA: Dataset for Japanese Explainable Multi-Hop Question Answering COLING 2024

Multi-LogiEval: Towards Evaluating Multi-Step Logical Reasoning Ability of Large Language Models EMNLP 2024

Exploring the Jungle of Bias: Political Bias Attribution in Language Models via Dependency Analysis EMNLP 2024

Inference Helps PLMs’ Conceptual Understanding: Improving the Abstract Inference Ability with Hierarchical Conceptual Entailment Graphs EMNLP 2024

Root Cause Explanation of Outliers under Noisy Mechanisms AAAI 2024

Uncertainty Quantification in Heterogeneous Treatment Effect Estimation with Gaussian-Process-Based Partially Linear Model AAAI 2024

yangqi at SemEval-2024 Task 9: Simulate Human Thinking by Large Language Model for Lateral Thinking Challenges NAACL 2024

A Hierarchical Network for Multimodal Document-Level Relation Extraction AAAI 2024

Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation AAAI 2024

What Makes Medical Claims (Un)Verifiable? Analyzing Entity and Relation Properties for Fact Verification EACL 2024

Denoising Rationalization for Multi-hop Fact Verification via Multi-granular Explainer EMNLP 2024

Dual-oriented Disentangled Network with Counterfactual Intervention for Multimodal Intent Detection EMNLP 2024

Towards the Disappearing Truth: Fine-Grained Joint Causal Influences Learning with Hidden Variable-Driven Causal Hypergraphs in Time Series AAAI 2024

A Twist for Graph Classification: Optimizing Causal Information Flow in Graph Neural Networks AAAI 2024

Distantly-Supervised Joint Extraction with Noise-Robust Learning ACL 2024

Learning and scoring Gaussian latent variable causal models with unknown additive interventions JMLR 2024

Effective Causal Discovery under Identifiable Heteroscedastic Noise Model AAAI 2024