Hao Peng

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


According to our database1, Hao Peng authored at least 15 papers between 2020 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Event-level Knowledge Editing.
CoRR, 2024

2023
Pre-training language model incorporating domain-specific heterogeneous knowledge into a unified representation.
Expert Syst. Appl., April, 2023

MAVEN-Arg: Completing the Puzzle of All-in-One Event Understanding Dataset with Event Argument Annotation.
CoRR, 2023

When does In-context Learning Fall Short and Why? A Study on Specification-Heavy Tasks.
CoRR, 2023

OmniEvent: A Comprehensive, Fair, and Easy-to-Use Toolkit for Event Understanding.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

The Devil is in the Details: On the Pitfalls of Event Extraction Evaluation.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022
COPEN: Probing Conceptual Knowledge in Pre-trained Language Models.
CoRR, 2022

Information Extraction and Human-Robot Dialogue towards Real-life Tasks: A Baseline Study with the MobileCS Dataset.
CoRR, 2022

A Challenge on Semi-Supervised and Reinforced Task-Oriented Dialog Systems.
CoRR, 2022

Multimodal Entity Tagging with Multimodal Knowledge Base.
CoRR, 2022

MAVEN-ERE: A Unified Large-scale Dataset for Event Coreference, Temporal, Causal, and Subevent Relation Extraction.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

COPEN: Probing Conceptual Knowledge in Pre-trained Language Models.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2021
TravelBERT: Pre-training Language Model Incorporating Domain-specific Heterogeneous Knowledge into A Unified Representation.
CoRR, 2021

2020
More Data, More Relations, More Context and More Openness: A Review and Outlook for Relation Extraction.
Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing, 2020

Learning from Context or Names? An Empirical Study on Neural Relation Extraction.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020


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