Cheng Tan

Orcid: 0000-0002-8639-923X

Affiliations:
  • Westlake University, AI Lab, School of Engineering, Hangzhou, China
  • Northwest A&F University, College of Information Engineering, Xianyang, China (former)


According to our database1, Cheng Tan authored at least 85 papers between 2020 and 2024.

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Bibliography

2024
Enhancing human-like multimodal reasoning: a new challenging dataset and comprehensive framework.
Neural Comput. Appl., November, 2024

A Survey on Generative Diffusion Models.
IEEE Trans. Knowl. Data Eng., July, 2024

Beyond Homophily and Homogeneity Assumption: Relation-Based Frequency Adaptive Graph Neural Networks.
IEEE Trans. Neural Networks Learn. Syst., June, 2024

GNN Cleaner: Label Cleaner for Graph Structured Data.
IEEE Trans. Knowl. Data Eng., February, 2024

Learning to Model Graph Structural Information on MLPs via Graph Structure Self-Contrasting.
CoRR, 2024

FoldToken2: Learning compact, invariant and generative protein structure language.
CoRR, 2024

CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graph.
CoRR, 2024

Peer Review as A Multi-Turn and Long-Context Dialogue with Role-Based Interactions.
CoRR, 2024

GenBench: A Benchmarking Suite for Systematic Evaluation of Genomic Foundation Models.
CoRR, 2024

Retrieval Meets Reasoning: Even High-school Textbook Knowledge Benefits Multimodal Reasoning.
CoRR, 2024

UniIF: Unified Molecule Inverse Folding.
CoRR, 2024

FoldToken: Learning Protein Language via Vector Quantization and Beyond.
CoRR, 2024

Switch EMA: A Free Lunch for Better Flatness and Sharpness.
CoRR, 2024

DCS-Net: Pioneering Leakage-Free Point Cloud Pretraining Framework with Global Insights.
CoRR, 2024

Masked Modeling for Self-supervised Representation Learning on Vision and Beyond.
CoRR, 2024

Interpretable and Generalizable Spatiotemporal Predictive Learning with Disentangled Consistency.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

VQDNA: Unleashing the Power of Vector Quantization for Multi-Species Genomic Sequence Modeling.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

A Graph is Worth K Words: Euclideanizing Graph using Pure Transformer.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Deciphering RNA Secondary Structure Prediction: A Probabilistic K-Rook Matching Perspective.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Re-Dock: Towards Flexible and Realistic Molecular Docking with Diffusion Bridge.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

MogaNet: Multi-order Gated Aggregation Network.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

SemiReward: A General Reward Model for Semi-supervised Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

KW-Design: Pushing the Limit of Protein Design via Knowledge Refinement.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

RDesign: Hierarchical Data-efficient Representation Learning for Tertiary Structure-based RNA Design.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Deep Manifold Transformation for Protein Representation Learning.
Proceedings of the IEEE International Conference on Acoustics, 2024

MLIP: Enhancing Medical Visual Representation with Divergence Encoder and Knowledge-guided Contrastive Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

General Point Model Pretraining with Autoencoding and Autoregressive.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

PSC-CPI: Multi-Scale Protein Sequence-Structure Contrasting for Efficient and Generalizable Compound-Protein Interaction Prediction.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Wavelet-Driven Spatiotemporal Predictive Learning: Bridging Frequency and Time Variations.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Cross-Gate MLP with Protein Complex Invariant Embedding Is a One-Shot Antibody Designer.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Self-Supervised Learning on Graphs: Contrastive, Generative, or Predictive.
IEEE Trans. Knowl. Data Eng., April, 2023

MMDesign: Multi-Modality Transfer Learning for Generative Protein Design.
CoRR, 2023

Efficiently Predicting Protein Stability Changes Upon Single-point Mutation with Large Language Models.
CoRR, 2023

Boosting the Power of Small Multimodal Reasoning Models to Match Larger Models with Self-Consistency Training.
CoRR, 2023

Segment Anything in Defect Detection.
CoRR, 2023

General Point Model with Autoencoding and Autoregressive.
CoRR, 2023

Revisiting the Temporal Modeling in Spatio-Temporal Predictive Learning under A Unified View.
CoRR, 2023

VQPL: Vector Quantized Protein Language.
CoRR, 2023

Enhancing Human-like Multi-Modal Reasoning: A New Challenging Dataset and Comprehensive Framework.
CoRR, 2023

MotifRetro: Exploring the Combinability-Consistency Trade-offs in retrosynthesis via Dynamic Motif Editing.
CoRR, 2023

Knowledge-Design: Pushing the Limit of Protein Design via Knowledge Refinement.
CoRR, 2023

Cross-Gate MLP with Protein Complex Invariant Embedding is A One-Shot Antibody Designer.
CoRR, 2023

Lightweight Contrastive Protein Structure-Sequence Transformation.
CoRR, 2023

PrefixMol: Target- and Chemistry-aware Molecule Design via Prefix Embedding.
CoRR, 2023

Generative Tertiary Structure-based RNA Design.
CoRR, 2023

DiffSDS: A language diffusion model for protein backbone inpainting under geometric conditions and constraints.
CoRR, 2023

Learning to Augment Graph Structure for both Homophily and Heterophily Graphs.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Target-Aware Molecular Graph Generation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track, 2023

Co-supervised Pre-training of Pocket and Ligand.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Understanding the Limitations of Deep Models for Molecular property prediction: Insights and Solutions.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

ProteinInvBench: Benchmarking Protein Inverse Folding on Diverse Tasks, Models, and Metrics.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Harnessing Hard Mixed Samples with Decoupled Regularizer.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

CONVERT: Contrastive Graph Clustering with Reliable Augmentation.
Proceedings of the 31st ACM International Conference on Multimedia, 2023

Mole-BERT: Rethinking Pre-training Graph Neural Networks for Molecules.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

PiFold: Toward effective and efficient protein inverse folding.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Wordreg: Mitigating the Gap between Training and Inference with Worst-Case Drop Regularization.
Proceedings of the IEEE International Conference on Acoustics, 2023

Global-Context Aware Generative Protein Design.
Proceedings of the IEEE International Conference on Acoustics, 2023

Deep Manifold Graph Auto-Encoder For Attributed Graph Embedding.
Proceedings of the IEEE International Conference on Acoustics, 2023

CVT-SLR: Contrastive Visual-Textual Transformation for Sign Language Recognition with Variational Alignment.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Temporal Attention Unit: Towards Efficient Spatiotemporal Predictive Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Multi-level disentanglement graph neural network.
Neural Comput. Appl., 2022

RFold: Towards Simple yet Effective RNA Secondary Structure Prediction.
CoRR, 2022

Protein Language Models and Structure Prediction: Connection and Progression.
CoRR, 2022

SimVP: Towards Simple yet Powerful Spatiotemporal Predictive Learning.
CoRR, 2022

Efficient Multi-order Gated Aggregation Network.
CoRR, 2022

Leveraging Graph-based Cross-modal Information Fusion for Neural Sign Language Translation.
CoRR, 2022

A Survey on Generative Diffusion Model.
CoRR, 2022

CoSP: Co-supervised pretraining of pocket and ligand.
CoRR, 2022

Temporal Attention Unit: Towards Efficient Spatiotemporal Predictive Learning.
CoRR, 2022

Generative De Novo Protein Design with Global Context.
CoRR, 2022

Decoupled Mixup for Data-efficient Learning.
CoRR, 2022

SemiRetro: Semi-template framework boosts deep retrosynthesis prediction.
CoRR, 2022

AlphaDesign: A graph protein design method and benchmark on AlphaFoldDB.
CoRR, 2022

GraphMixup: Improving Class-Imbalanced Node Classification by Reinforcement Mixup and Self-supervised Context Prediction.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

OT Cleaner: Label Correction as Optimal Transport.
Proceedings of the IEEE International Conference on Acoustics, 2022

SimVP: Simpler yet Better Video Prediction.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Hyperspherical Consistency Regularization.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Extensive Deep Temporal Point Process.
CoRR, 2021

Git: Clustering Based on Graph of Intensity Topology.
CoRR, 2021

GraphMixup: Improving Class-Imbalanced Node Classification on Graphs by Self-supervised Context Prediction.
CoRR, 2021

Self-supervised on Graphs: Contrastive, Generative, or Predictive.
CoRR, 2021

Co-learning: Learning from Noisy Labels with Self-supervision.
Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

2020
A Data Augmentation Method Based on Generative Adversarial Networks for Grape Leaf Disease Identification.
IEEE Access, 2020


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