Ming Ding

Orcid: 0000-0001-5152-7011

Affiliations:
  • Zhipu AI
  • Tsinghua University, Department of Computer Science and Technology, Beijing, China


According to our database1, Ming Ding authored at least 42 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2024
Inf-DiT: Upsampling Any-Resolution Image with Memory-Efficient Diffusion Transformer.
CoRR, 2024

CogView3: Finer and Faster Text-to-Image Generation via Relay Diffusion.
CoRR, 2024

Does Negative Sampling Matter? A Review with Insights into its Theory and Applications.
CoRR, 2024

CogCoM: Train Large Vision-Language Models Diving into Details through Chain of Manipulations.
CoRR, 2024

2023
Region or Global? A Principle for Negative Sampling in Graph-Based Recommendation.
IEEE Trans. Knowl. Data Eng., June, 2023

MRT: Tracing the Evolution of Scientific Publications.
IEEE Trans. Knowl. Data Eng., 2023

CogAgent: A Visual Language Model for GUI Agents.
CoRR, 2023

CogVLM: Visual Expert for Pretrained Language Models.
CoRR, 2023

Relay Diffusion: Unifying diffusion process across resolutions for image synthesis.
CoRR, 2023

GPT Can Solve Mathematical Problems Without a Calculator.
CoRR, 2023

ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation.
CoRR, 2023

ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

BatchSampler: Sampling Mini-Batches for Contrastive Learning in Vision, Language, and Graphs.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

GLM-130B: An Open Bilingual Pre-trained Model.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
GLM-130B: An Open Bilingual Pre-trained Model.
CoRR, 2022

STAM: A Spatiotemporal Aggregation Method for Graph Neural Network-based Recommendation.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

CogView2: Faster and Better Text-to-Image Generation via Hierarchical Transformers.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Rethinking the Setting of Semi-supervised Learning on Graphs.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Parameter-Efficient Tuning Makes a Good Classification Head.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

GLM: General Language Model Pretraining with Autoregressive Blank Infilling.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021
FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding.
CoRR, 2021

GPT Understands, Too.
CoRR, 2021

All NLP Tasks Are Generation Tasks: A General Pretraining Framework.
CoRR, 2021

M6: A Chinese Multimodal Pretrainer.
CoRR, 2021

WuDaoCorpora: A super large-scale Chinese corpora for pre-training language models.
AI Open, 2021

Adaptive Diffusion in Graph Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

UFC-BERT: Unifying Multi-Modal Controls for Conditional Image Synthesis.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

CogView: Mastering Text-to-Image Generation via Transformers.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Are we really making much progress?: Revisiting, benchmarking and refining heterogeneous graph neural networks.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

MixGCF: An Improved Training Method for Graph Neural Network-based Recommender Systems.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

The International Workshop on Pretraining: Algorithms, Architectures, and Applications ([email protected] 2021).
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2020
CogLTX: Applying BERT to Long Texts.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Understanding Negative Sampling in Graph Representation Learning.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2019
Cognitive Knowledge Graph Reasoning for One-shot Relational Learning.
CoRR, 2019

ProNE: Fast and Scalable Network Representation Learning.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Towards Knowledge-Based Recommender Dialog System.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Cognitive Graph for Multi-Hop Reading Comprehension at Scale.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018
Spectral Network Embedding: A Fast and Scalable Method via Sparsity.
CoRR, 2018

Semi-supervised Learning on Graphs with Generative Adversarial Nets.
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018


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