Lingjing Kong
15 papers · 2020–2026 · 6 conferences · across top CS/AI conferences
Achievements
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πΊοΈ Taxonomy Completionist (30) π Renaissance Researcher (5) π Interdisciplinary Bridge π§ Keyword Pioneer π Conference Polyglot (5)
π
Academic Marathon
(5)
π
Cross-Pollinator
(13)
π
Century Club
(13)
π₯
Unstoppable
(6)
Conferences
NIPS (5)
ICML (4)
ACL (2)
ICLR (2)
CVPR (1)
EMNLP (1)
Top co-authors
Keywords
causal inference
(3)
latent variable model
(3)
hierarchical model
(2)
domain adaptation
(2)
distributed learning
(1)
intent classification
(1)
few-shot learning
(1)
self-supervised learning
(1)
stochastic gradient descent
(1)
knowledge distillation
(1)
causal discovery
(1)
image reconstruction
(1)
model fusion
(1)
deep learning
(1)
neural network optimization
(1)
ensemble learning
(1)
representation learning
(1)
causal structure
(1)
distribution shift
(1)
unsupervised learning
(1)
Papers
Advancing Reasoning in Diffusion Language Models with Denoising Process Rewards
ACL 2026
Mechanistic Interpretability Should Prioritize Feature Consistency in Sparse Autoencoders
ACL 2026
Causal Representation Learning from Multimodal Biomedical Observations
ICLR 2025
Learning Vision and Language Concepts for Controllable Image Generation
ICML 2025
Towards Understanding Extrapolation: a Causal Lens
NIPS 2024
Learning Discrete Concepts in Latent Hierarchical Models
NIPS 2024
Multi-domain image generation and translation with identifiability guarantees
ICLR 2023
Identification of Nonlinear Latent Hierarchical Models
NIPS 2023
Counterfactual Generation with Identifiability Guarantees
NIPS 2023
Understanding Masked Autoencoders via Hierarchical Latent Variable Models
CVPR 2023
Partial disentanglement for domain adaptation
ICML 2022
Consensus Control for Decentralized Deep Learning
ICML 2021
Self-training Improves Pre-training for Few-shot Learning in Task-oriented Dialog Systems
EMNLP 2021
Extrapolation for Large-batch Training in Deep Learning
ICML 2020
Ensemble Distillation for Robust Model Fusion in Federated Learning
NIPS 2020