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 # Data Science & Artificial Intelligence Lab
 
@@ -15,72 +15,3 @@ Welcome to the DSAI Lab at the HKUST(GZ), our research focuses on a variety of t
 * Data Mining
 * AI for Science
 * Large Language Model
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-## Publication
-
-(Under Adding Constructions)
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-### KDD 2024
-
-GraphWiz: An Instruction-Following Language Model for Graph Problems [[github](https://github.com/nuochenpku/Graph-Reasoning-LLM)]
-
-ZeroG: Investigating Cross-dataset Zero-shot Transferability in Graphs [[github](https://github.com/NineAbyss/ZeroG)]
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-All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining [[github](https://github.com/cshhzhao/GCOPE)]
-
-Relaxing Continuous Constraints of Equivariant Graph Neural Networks for Physical Dynamics Learning [[github](https://github.com/compasszzn/DEGNN)]
-
-### ICML 2024
-Parameter Efficient Fine-Tuning with Discrete Fourier Transform [[github](https://github.com/Chaos96/fourierft)]
-
-### IJCAI 2024
-A Survey of Graph Meets Large Language Model: Progress and Future Directions [[github](https://github.com/yhLeeee/Awesome-LLMs-in-Graph-tasks)]
-
-### WWW 2024
-Weakly Supervised Anomaly Detection via Knowledge-Data Alignment [[github](https://github.com/cshhzhao/KDAlign)]
-
-### ICLR 2024
-Protein Multimer Structure Prediction via Prompt Learning [[github](https://github.com/zqgao22/PromptMSP)]
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-Deep Reinforcement Learning for Modelling Protein Complexes
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-SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases
-
-### NIPS 2023
-GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection [[github](https://github.com/squareRoot3/GADBench)]
-
-Deep Insights into Noisy Pseudo Labeling on Graph Data [[github](https://github.com/AcEbt/CPL)]
-
-### EMNLP 2023
-Large Language Models Meet Harry Potter: A Bilingual Dataset for Aligning Dialogue Agents with Characters [[github](https://github.com/nuochenpku/Harry-Potter-Dialogue-Dataset)]
-
-Orca: A Few-shot Benchmark for Chinese Conversational Machine Reading Comprehension [[github](https://github.com/nuochenpku/Orca)]
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-Nature Response Generation for Chinese Reading Comprehension [[github](https://github.com/nuochenpku/Penguin)]
-
-### CIKM 2023
-A Co-training Approach for Noisy Time Series Learning [[github](https://github.com/Vicky-51/TS-CoT/tree/master)]
-
-### KDD 2023
-Warpformer: A Multi-scale Modeling Approach for Irregular Clinical Time Series [[github](https://github.com/imJiawen/Warpformer)]
-
-### ACL 2023
-Alleviating Over-smoothing for Unsupervised Sentence Representation [[github](https://github.com/nuochenpku/SSCL)]
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-Structural Contrastive Pretraining for Cross-Lingual Comprehension [[github](https://github.com/nuochenpku/SCP)]
-
-A Fused Gromov-Wasserstein Framework for Unsupervised Knowledge Graph Entity Alignment [[github](https://github.com/squareRoot3/FusedGW-Entity-Alignment)]
-
-### Nature Communications 2023
-Hierarchical Graph Learning for Protein-Protein Interaction [[github](https://github.com/zqgao22/HIGH-PPI)]
-
-### AAAI 2023
-Handling Missing Data via Max-Entropy Regularized Graph Autoencoder
-Human Mobility Modeling During the COVID-19 Pandemic via Deep Graph Diffusion Infomax
-Wiener Graph Deconvolutional Network Improves Graph Self-Supervised Learning
-
-### ICDE 2023
-Robust Attributed Graph Alignment via Joint Structure Learning and Optimal Transport [[github](https://github.com/squareRoot3/SLOTAlign)]
-
-### ICML 2022
-Rethinking Graph Neural Networks for Anomaly Detection [[github](https://github.com/squareRoot3/Rethinking-Anomaly-Detection)]