Ming Zhong

Orcid: 0000-0001-5728-0224

Affiliations:
  • University of Illinois Urbana-Champaign, Department of Computer Science, Urbana, IL, USA
  • Fudan University, School of Computer Science, Shanghai, China


According to our database1, Ming Zhong authored at least 31 papers between 2019 and 2024.

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

Timeline

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Bibliography

2024
Multi-LoRA Composition for Image Generation.
CoRR, 2024

Investigating Data Contamination for Pre-training Language Models.
CoRR, 2024

2023
Seeking Neural Nuggets: Knowledge Transfer in Large Language Models from a Parametric Perspective.
CoRR, 2023

L-Eval: Instituting Standardized Evaluation for Long Context Language Models.
CoRR, 2023

Unsupervised Event Chain Mining from Multiple Documents.
Proceedings of the ACM Web Conference 2023, 2023

Dynosaur: A Dynamic Growth Paradigm for Instruction-Tuning Data Curation.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

The Shifted and The Overlooked: A Task-oriented Investigation of User-GPT Interactions.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Instruct and Extract: Instruction Tuning for On-Demand Information Extraction.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Reaction Miner: An Integrated System for Chemical Reaction Extraction from Textual Data.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

PREME: Preference-based Meeting Exploration through an Interactive Questionnaire.
Proceedings of the Findings of the Association for Computational Linguistics: EACL 2023, 2023

ReactIE: Enhancing Chemical Reaction Extraction with Weak Supervision.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022
Towards a Unified Multi-Dimensional Evaluator for Text Generation.
CoRR, 2022

CiteSum: Citation Text-guided Scientific Extreme Summarization and Low-resource Domain Adaptation.
CoRR, 2022

Unsupervised Summarization with Customized Granularities.
CoRR, 2022

Unsupervised Multi-Granularity Summarization.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Towards a Unified Multi-Dimensional Evaluator for Text Generation.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

CiteSum: Citation Text-guided Scientific Extreme Summarization and Domain Adaptation with Limited Supervision.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Open-Vocabulary Argument Role Prediction For Event Extraction.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Improving Abstractive Dialogue Summarization with Speaker-Aware Supervised Contrastive Learning.
Proceedings of the 29th International Conference on Computational Linguistics, 2022

CoLo: A Contrastive Learning Based Re-ranking Framework for One-Stage Summarization.
Proceedings of the 29th International Conference on Computational Linguistics, 2022

DialogLM: Pre-trained Model for Long Dialogue Understanding and Summarization.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
RetrievalSum: A Retrieval Enhanced Framework for Abstractive Summarization.
CoRR, 2021

QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarization.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Enhancing Scientific Papers Summarization with Citation Graph.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
CDEvalSumm: An Empirical Study of Cross-Dataset Evaluation for Neural Summarization Systems.
CoRR, 2020

An Empirical Study of Cross-Dataset Evaluation for Neural Summarization Systems.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Extractive Summarization as Text Matching.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019
A Closer Look at Data Bias in Neural Extractive Summarization Models.
CoRR, 2019

Exploring Domain Shift in Extractive Text Summarization.
CoRR, 2019

Searching for Effective Neural Extractive Summarization: What Works and What's Next.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019


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