Kaize Ding
33 papers · 2019–2026 · 9 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+9 more ↓ Show less ↑
π Cross-Pollinator (14) π Academic Marathon (6) π Interdisciplinary Bridge π Conference Polyglot (9) π Renaissance Researcher (7)
π
Conference Polyglot
(9)
π
Academic Marathon
(6)
π
Renaissance Researcher
(7)
π€
Dynamic Duo
(10)
π₯
Unstoppable
(7)
π
Century Club
(28)
β‘
Prolific Year
(9)
ποΈ
Keyword Collector
(121)
β
The Questioner
Conferences
EMNLP (7)
AAAI (6)
ACL (6)
NIPS (4)
IJCAI (3)
NAACL (3)
ICLR (2)
COLING (1)
WACV (1)
Top co-authors
Research topics
Keywords
large language model
(13)
graph neural network
(12)
self-supervised learning
(5)
few-shot learning
(4)
anomaly detection
(4)
contrastive learning
(3)
zero-shot learning
(2)
out-of-distribution detection
(2)
fake news detection
(2)
semi-supervised learning
(2)
mutual information
(2)
node representation
(2)
text classification
(2)
data augmentation
(2)
weakly-supervised learning
(2)
representation learning
(2)
unsupervised learning
(2)
graph representation
(2)
node classification
(2)
preference evaluation
(2)
Papers
Explainable and Fine-Grained Safeguarding of LLM Multi-Agent Systems via Bi-Level Graph Anomaly Detection
ACL 2026
CoAct: Co-Active LLM Preference Learning with Human-AI Synergy
ACL 2026
Towards Acyclic Preference Evaluation of Language Models via Multiple Evaluators
AAAI 2026
MolMem: Memory-Augmented Agentic Reinforcement Learning for Sample-Efficient Molecular Optimization
ACL 2026
A Survey of Large Language Models for Text-Guided Molecular Discovery: From Molecule Generation to Optimization
ACL 2026
AD-LLM: Benchmarking Large Language Models for Anomaly Detection
ACL 2025
Exploring Concept Depth: How Large Language Models Acquire Knowledge and Concept at Different Layers?
COLING 2025
Large Language Models for Anomaly and Out-of-Distribution Detection: A Survey
NAACL 2025
ALERT: An LLM-powered Benchmark for Automatic Evaluation of Recommendation Explanations
NAACL 2025
Avoiding Copyright Infringement via Large Language Model Unlearning
NAACL 2025
Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark
ICLR 2025
Explaining Length Bias in LLM-Based Preference Evaluations
EMNLP 2025
AMANDA: Agentic Medical Knowledge Augmentation for Data-Efficient Medical Visual Question Answering
EMNLP 2025
On Large Language Model Continual Unlearning
ICLR 2025
Letβs Ask GNN: Empowering Large Language Model for Graph In-Context Learning
EMNLP 2024
Revisiting Score Propagation in Graph Out-of-Distribution Detection
NIPS 2024
Sterling: Synergistic Representation Learning on Bipartite Graphs
AAAI 2024
Data-Efficient Graph Learning
AAAI 2024
Empowering Large Language Models for Textual Data Augmentation
ACL 2024
On Fake News Detection with LLM Enhanced Semantics Mining
EMNLP 2024
MGM-AE: Self-Supervised Learning on 3D Shape Using Mesh Graph Masked Autoencoders
WACV 2024
Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning
AAAI 2023
Towards Self-Interpretable Graph-Level Anomaly Detection
NIPS 2023
Keypoint-Augmented Self-Supervised Learning for Medical Image Segmentation with Limited Annotation
NIPS 2023
GRENADE: Graph-Centric Language Model for Self-Supervised Representation Learning on Text-Attributed Graphs
EMNLP 2023
BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs
NIPS 2022
Few-Shot Learning on Graphs
IJCAI 2022
Meta Propagation Networks for Graph Few-shot Semi-supervised Learning
AAAI 2022
Learning to Selectively Learn for Weakly-supervised Paraphrase Generation
EMNLP 2021
Fact-Enhanced Synthetic News Generation
AAAI 2021
Inductive Anomaly Detection on Attributed Networks
IJCAI 2020
Be More with Less: Hypergraph Attention Networks for Inductive Text Classification
EMNLP 2020
InterSpot: Interactive Spammer Detection in Social Media
IJCAI 2019