Ruichu Cai
56 papers · 2013–2026 · 11 conferences · across top CS/AI conferences
Achievements
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(210)
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(54)
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Conferences
AAAI (15)
IJCAI (12)
ICML (8)
NIPS (8)
NAACL (3)
ACL (2)
COLING (2)
ICLR (2)
JMLR (2)
EMNLP (1)
INTERSPEECH (1)
Top co-authors
Research topics
Keywords
causal discovery
(17)
causal inference
(10)
causal structure
(8)
latent variable
(5)
causal direction
(5)
structural equation model
(4)
large language model
(4)
higher-order cumulant
(3)
structural causal model
(3)
representation learning
(3)
graphical model
(3)
graph neural network
(3)
domain adaptation
(3)
transfer learning
(3)
optimal transport
(3)
neural network
(3)
variational inference
(2)
variational autoencoder
(2)
cross-domain generalization
(2)
latent variable model
(2)
Papers
Horizontal and Vertical Federated Causal Structure Learning via Higher-order Cumulants
AAAI 2026
CAMA: Enhancing Mathematical Reasoning in Large Language Models with Causal Knowledge
AAAI 2026
Handling Missing Entities in Zero-Shot Named Entity Recognition: Integrated Recall and Retrieval Augmentation
NAACL 2025
Causal-aware Large Language Models: Enhancing Decision-Making Through Learning, Adapting and Acting
IJCAI 2025
𝒮2IT: Stepwise Syntax Integration Tuning for Large Language Models in Aspect Sentiment Quad Prediction
NAACL 2025
Track-SQL: Enhancing Generative Language Models with Dual-Extractive Modules for Schema and Context Tracking in Multi-turn Text-to-SQL
NAACL 2025
Disentangling Long-Short Term State Under Unknown Interventions for Online Time Series Forecasting
AAAI 2025
Hypergraph Learning for Unsupervised Graph Alignment via Optimal Transport
AAAI 2025
Long-Term Individual Causal Effect Estimation via Identifiable Latent Representation Learning
IJCAI 2025
Dr.ECI: Infusing Large Language Models with Causal Knowledge for Decomposed Reasoning in Event Causality Identification
COLING 2025
CACA: Context-Aware Cross-Attention Network for Extractive Aspect Sentiment Quad Prediction
COLING 2025
GenLink: Generation-Driven Schema-Linking via Multi-Model Learning for Text-to-SQL
EMNLP 2025
On the Identification of Temporal Causal Representation with Instantaneous Dependence
ICLR 2025
Synergy Between Sufficient Changes and Sparse Mixing Procedure for Disentangled Representation Learning
ICLR 2025
Causal View of Time Series Imputation: Some Identification Results on Missing Mechanism
IJCAI 2025
Identification of Latent Confounders via Investigating the Tensor Ranks of the Nonlinear Observations
ICML 2025
Reducing Confounding Bias without Data Splitting for Causal Inference via Optimal Transport
ICML 2025
Identification of Causal Structure in the Presence of Missing Data with Additive Noise Model
AAAI 2024
Causal Discovery from Poisson Branching Structural Causal Model Using High-Order Cumulant with Path Analysis
AAAI 2024
Doubly Robust Causal Effect Estimation under Networked Interference via Targeted Learning
ICML 2024
Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal Explanation
ICML 2024
Automating the Selection of Proxy Variables of Unmeasured Confounders
ICML 2024
S2GSL: Incorporating Segment to Syntactic Enhanced Graph Structure Learning for Aspect-based Sentiment Analysis
ACL 2024
Reducing Balancing Error for Causal Inference via Optimal Transport
ICML 2024
Combinatorial Routing for Neural Trees
IJCAI 2024
On the Identifiability of Poisson Branching Structural Causal Model Using Probability Generating Function
NIPS 2024
Learning Discrete Latent Variable Structures with Tensor Rank Conditions
NIPS 2024
Individual Causal Structure Learning from Population Data
IJCAI 2024
Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables
JMLR 2024
Causal-learn: Causal Discovery in Python
JMLR 2024
Hypergraph Joint Representation Learning for Hypervertices and Hyperedges via Cross Expansion
AAAI 2024
Where and How to Attack? A Causality-Inspired Recipe for Generating Counterfactual Adversarial Examples
AAAI 2024
An Optimal Transport View for Subspace Clustering and Spectral Clustering
AAAI 2024
Exploiting Geometry for Treatment Effect Estimation via Optimal Transport
AAAI 2024
Identification of Causal Structure with Latent Variables Based on Higher Order Cumulants
AAAI 2024
TNPAR: Topological Neural Poisson Auto-Regressive Model for Learning Granger Causal Structure from Event Sequences
AAAI 2024
Some General Identification Results for Linear Latent Hierarchical Causal Structure
IJCAI 2023
Subspace Identification for Multi-Source Domain Adaptation
NIPS 2023
Causal Discovery with Latent Confounders Based on Higher-Order Cumulants
ICML 2023
Structural Hawkes Processes for Learning Causal Structure from Discrete-Time Event Sequences
IJCAI 2023
Identification of Linear Latent Variable Model with Arbitrary Distribution
AAAI 2022
Causal Discovery with Multi-Domain LiNGAM for Latent Factors
IJCAI 2021
SADGA: Structure-Aware Dual Graph Aggregation Network for Text-to-SQL
NIPS 2021
Domain Adaptation with Invariant Representation Learning: What Transformations to Learn?
NIPS 2021
Appearance-Motion Memory Consistency Network for Video Anomaly Detection
AAAI 2021
Time Series Domain Adaptation via Sparse Associative Structure Alignment
AAAI 2021
Meta Multi-Task Learning for Speech Emotion Recognition
INTERSPEECH 2020
TAG : Type Auxiliary Guiding for Code Comment Generation
ACL 2020
Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs
NIPS 2020
Triad Constraints for Learning Causal Structure of Latent Variables
NIPS 2019
Causal Discovery with Cascade Nonlinear Additive Noise Model
IJCAI 2019
Learning Disentangled Semantic Representation for Domain Adaptation
IJCAI 2019
Causal Discovery from Discrete Data using Hidden Compact Representation
NIPS 2018
An Encoder-Decoder Framework Translating Natural Language to Database Queries
IJCAI 2018
A Robust Noise Resistant Algorithm for POI Identification from Flickr Data
IJCAI 2017
SADA: A General Framework to Support Robust Causation Discovery
ICML 2013