Kun Kuang
Associate Professor
Studies causal inference and its integration with machine learning, including causal AI for smart justice and domain-specific large models.
Kun Kuang's lab at Zhejiang works on probabilistic & causal inference, efficient training & inference and large language models. 143 papers since 2023, 115 at top venues, mostly ICML and EMNLP. Applications close .
At a glance
- papers, 2023–2026
- 37/ year
- at T1 venues
- 80%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 34 papers2026 · T1 31 · collecting
- 39 papers2025 · T1 32
- 42 papers2024 · T1 32
- 28 papers2023 · T1 20
T1 venuesOtherVenues: ICML, EMNLP, AAAI, KDD, ACL
Research focuspaper titles that use each topic's words
- Large language models38 papers
- Probabilistic & causal inference26 papers
- causal20 papers
- Efficient training & inference18 papers
- studies causal0 papers
Paper list
From the lab homepage.
202634 papers
- ACL (T1)"I Don’t Know What to Say": A Fact-Filling Questionnaire Method to Help Non-Experts Talk to LegalAI Assistant (opens in a new tab)
- Information Processing and ManagementA multi-agent framework with legal event logic graph for multi-defendant legal judgment prediction (opens in a new tab)
- ICLR (T1)Asynchronous Denoising Diffusion Models for Aligning Text-to-Image Generation (opens in a new tab)
- ACL (T1)C^{2}DLM: Causal Concept-Guided Diffusion Large Language Models (opens in a new tab)
- ICLR (T1)Can LLMs Reason Soundly in Law? Auditing Inference Patterns for Legal Judgment (opens in a new tab)
- ICML (T1)Causal Discovery for Irregularly Time Series with Consistency Guarantees (opens in a new tab)
- KDD (T1)Causal Effect Estimation under Informative Censoring: A Multiple-Imputation Approach with Shadow Calibration (opens in a new tab)
- ACM Computing SurveysCausal Inference with Complex Treatments: A Survey (opens in a new tab)
- EMNLP (T1)ChJGBench: A Comprehensive Benchmark for Chinese Legal Judgment Generation with Diagnostic Evaluation (opens in a new tab)
- KDD (T1)Continuous-Time Counterfactual Quantile Learning for Risk-Sensitive Policy Optimization (opens in a new tab)
- AAAI (T1)Detecting Unobserved Confounders: A Kernelized Regression Approach (opens in a new tab)
- KDD (T1)Each Rank Could be an Expert: Single-Ranked Mixture of Experts LoRA for Multi-task Learning (opens in a new tab)
202539 papers
- ICML (T1)Advancing Personalized Learning with Neural Collapse for Long-Tail Challenge (opens in a new tab)
- ICML (T1)Arrow: Accelerator for Time Series Causal Discovery with Time Weaving (opens in a new tab)
- CIKM (T1)Augmenting Limited and Biased RCTs through Pseudo-Sample Matching-Based Observational Data Fusion Method (opens in a new tab)
- EMNLP (T1)CAT: Causal Attention Tuning For Injecting Fine-grained Causal Knowledge into Large Language Models (opens in a new tab)
- —Classifying Treatment Responders: Bounds and Algorithms, KDD, 2025
- EMNLP (T1)CoEvo: Coevolution of LLM and Retrieval Model for Domain-Specific Information Retrieval (opens in a new tab)
- KDD (T1)Collaboration of Large Language Models and Small Recommendation Models for Device-Cloud Recommendation (opens in a new tab)
- TCSVTCross-Modality Image Interpretation via Concept Decomposition Vector of Visual-Language Models (opens in a new tab)
- ICML (T1)D-Fusion: Direct preference optimization for aligning diffusion models with visually consistent samples (opens in a new tab)
- ICCV (T1)Decoding Correlation-Induced Misalignment in the Stable Diffusion Workflow for Text-to-Image Generation (opens in a new tab)
- ACL (T1)Embracing Imperfection: Simulating Students with Diverse Cognitive Levels Using LLM-based Agents (opens in a new tab)
- ICML (T1)ERICT: Enhancing Robustness by Identifying Concept Tokens in Zero-Shot Vision Language Models (opens in a new tab)
202442 papers
- ICML (T1)A Generative Approach for Treatment Effect Estimation under Collider Bias: From an Out-of-Distribution Perspective (opens in a new tab)
- ICLR (T1)AuG-KD: Anchor-Based Mixup Generation for Out-of-Domain Knowledge Distillation (opens in a new tab)
- TKDE (T1)Causal Distillation for Alleviating Performance Heterogeneity in Recommender Systems (opens in a new tab)
- TGRSCausality-Guided Stepwise Intervention and Reweighting for Remote Sensing Image Semantic Segmentation (opens in a new tab)
- AAAI (T1)CGMGM: A Cross Gaussian Mixture Generative Model for Few-shot Semantic Segmentation (opens in a new tab)
- ACL (T1)Chain-of-Quizzes: Pedagogy-inspired Example Selection in In-Context-Learning (opens in a new tab)
- ICMRCLAP: Contrastive Language-Audio Pre-training Model for Multi-modal Sentiment Analysis (opens in a new tab)
- AAAI (T1)Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation (opens in a new tab)
- AAAI (T1)CoreRec: A Counterfactual Correlation Inference for Next Set Recommendation (opens in a new tab)
- AAAI (T1)De-biased Attention Supervision for Text Classification with Causality (opens in a new tab)
- CVIUDeconfounded Hierarchical Multi-Granularity Classification (opens in a new tab)
- CVPR (T1)Distributionally Generative Augmentation for Fair Facial Attribute Classification (opens in a new tab)
202328 papers
- ICML (T1)Causal Structure Learning for Latent Intervened Non-stationary Data (opens in a new tab)
- TKDE (T1)Collaborative Semantic Aggregation and Calibration for Federated Domain Generalization (opens in a new tab)
- EngineeringData-Driven Learning for Data Rights, Data Pricing, and Privacy Computing (opens in a new tab)
- The WebConfDUET: A Tuning-Free Device-Cloud Collaborative Parameters Generation Framework for Efficient Device Model Generalization (opens in a new tab)
- EMNLP (T1)Exploiting Contrastive Learning and Numerical Evidence for Confusing Legal Judgment Prediction (opens in a new tab)
- ICLR (T1)Fairness-aware Contrastive Learning with Partially Annotated Sensitive Attributes (opens in a new tab)
- FITEEFederated Mutual Learning: A Collaborative Machine Learning Method for Heterogeneous Data,Models, and Objectives (opens in a new tab)
- ACL (T1)Focus-aware Response Generation in Inquiry Conversation (opens in a new tab)
- ACM MMGeneralized Universal Domain Adaptation with Generative Flow Networks (opens in a new tab)
- The WebConfGraph Neural Network with Two Uplift Estimators for Label-Scarcity Individual Uplift Modeling (opens in a new tab)
- NeurIPS (T1)HAP: Structure-Aware Masked Image Modeling for Human-Centric Perception (opens in a new tab)
- TKDDInstrumental Variable-Driven Domain Generalization with Unobserved Confounders (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to ZhejiangFall 2027
Computer Science PhD (international applicants)
- Round
- Self-funded
- Opens
- —
- GRE
- See program page
- English
- Per ZJU language requirements
- Fee
- RMB 800
Not yet confirmed for this intake.
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