Jin Ma
Orcid: 0009-0005-5837-6144Affiliations:
- Tencent, Beijing, China
According to our database1,
Jin Ma
authored at least 16 papers
between 2022 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
CBVS: A Large-Scale Chinese Image-Text Benchmark for Real-World Short Video Search Scenarios.
CoRR, 2024
2023
A Confidence-based Partial Label Learning Model for Crowd-Annotated Named Entity Recognition.
CoRR, 2023
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023
Proceedings of the 31st ACM International Conference on Multimedia, 2023
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023
Proceedings of the The 61st Annual Meeting of the Association for Computational Linguistics: Industry Track, 2023
A Confidence-based Partial Label Learning Model for Crowd-Annotated Named Entity Recognition.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023
Knowledge Transfer in Incremental Learning for Multilingual Neural Machine Translation.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023
On the Universal Adversarial Perturbations for Efficient Data-free Adversarial Detection.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
ChiQA: A Large Scale Image-based Real-World Question Answering Dataset for Multi-Modal Understanding.
CoRR, 2022
Title2Event: Benchmarking Open Event Extraction with a Large-scale Chinese Title Dataset.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022
ChiQA: A Large Scale Image-based Real-World Question Answering Dataset for Multi-Modal Understanding.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022