Yujia Zheng
26 papers · 2021–2026 · 10 conferences · across top CS/AI conferences
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ICML (6)
NIPS (6)
ICLR (5)
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ACL (1)
CVPR (1)
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Keywords
independent component analysis
(3)
latent variable model
(3)
source separation
(3)
causal discovery
(3)
representation learning
(3)
causal inference
(2)
structural sparsity
(2)
unsupervised learning
(2)
few-shot learning
(1)
matrix factorization
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adversarial robustness
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structure learning
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distribution shift
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domain adaptation
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multimodal learning
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imitation learning
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temporal sequence
(1)
second-order statistics
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sparse representation
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temporal modeling
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Papers
Mechanistic Interpretability Should Prioritize Feature Consistency in Sparse Autoencoders
ACL 2026
Are All Prompt Components Value-Neutral? Understanding the Heterogeneous Adversarial Robustness of Dissected Prompt in LLMs
EACL 2026
Causal Representation Learning from Multimodal Biomedical Observations
ICLR 2025
Synergy Between Sufficient Changes and Sparse Mixing Procedure for Disentangled Representation Learning
ICLR 2025
Learning Vision and Language Concepts for Controllable Image Generation
ICML 2025
Nonparametric Identification of Latent Concepts
ICML 2025
Nonparametric Factor Analysis and Beyond
AISTATS 2025
Type Information-Assisted Self-Supervised Knowledge Graph Denoising
AISTATS 2025
SmartCLIP: Modular Vision-language Alignment with Identification Guarantees
CVPR 2025
A General Representation-Based Approach to Multi-Source Domain Adaptation
ICML 2025
Butterfly Effects in Toolchains: A Comprehensive Analysis of Failed Parameter Filling in LLM Tool-Agent Systems
EMNLP 2025
Identification of Intermittent Temporal Latent Process
ICLR 2025
A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables
ICLR 2024
Identifying Selections for Unsupervised Subtask Discovery
NIPS 2024
Causal Temporal Representation Learning with Nonstationary Sparse Transition
NIPS 2024
Local Causal Discovery with Linear non-Gaussian Cyclic Models
AISTATS 2024
Causal Representation Learning from Multiple Distributions: A General Setting
ICML 2024
Detecting and Identifying Selection Structure in Sequential Data
ICML 2024
Causal-learn: Causal Discovery in Python
JMLR 2024
On the Identifiability of Sparse ICA without Assuming Non-Gaussianity
NIPS 2023
Generalized Precision Matrix for Scalable Estimation of Nonparametric Markov Networks
ICLR 2023
Generalizing Nonlinear ICA Beyond Structural Sparsity
NIPS 2023
On the Identifiability of Nonlinear ICA: Sparsity and Beyond
NIPS 2022
Partial disentanglement for domain adaptation
ICML 2022
Reliable Causal Discovery with Improved Exact Search and Weaker Assumptions
NIPS 2021
Cold-start Sequential Recommendation via Meta Learner
AAAI 2021