Scholar

Fei Zhao

Google Scholar ID: V01xzWQAAAAJ

Nanjing University

Natural Language ProcessingLarge Language ModelMulti-modal LLM

Citations & Impact

All-time

Citations

740

H-index

i10-index

Publications

Co-authors

list available

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Publications

20 items

Browse publications on Google Scholar (top-right) ↗

Resume (English only)

Academic Achievements

2025-08-20: One paper on Chinese Multi-image Benchmark is accepted by Findings of EMNLP 2025.
2025-02-22: One paper on Efficient Multimodal Large Language Models is accepted by ICLR 2025.
2024-09-20: One paper on Multimodal Hallucination Mitigation is accepted by EMNLP 2024.
2024-05-24: Release a paper on Multi-modal Large Language Models to Arxiv.
2024-05-16: Two papers are accepted by Findings of ACL 2024.
2024-02-16: Release a paper on Multimodal Hallucination Mitigation to Arxiv.
2023-10-08: One paper on multimodal ABSA is accepted by EMNLP 2023.
2023-10-03: Release a paper on in-context learning to Arxiv.
2023-07-26: One paper on multimodal entity linking is accepted by ACM Multimedia 2023.
2023-05-11: One paper is accepted by TASLP 2023.
2023-05-02: One paper is accepted by Findings of ACL 2023.
2022-10-06: One paper on few-shot aspect category detection is accepted by Findings of EMNLP 2022.
2022-08-17: One paper on multimodal ABSA is accepted by COLING 2022.
2022-06-30: One paper on multimodal NER is accepted by ACM Multimedia 2022.
2020-10-01: One paper on ABSA is accepted by COLING 2020.
2020-09-14: One paper on aspect triplet extraction is accepted by Findings of EMNLP 2020.
2019-11-11: One paper on TOWE is accepted by AAAI 2020.

Research Experience

Involved in multiple research projects, including multi-modal information extraction and multi-modal large language models.

Education

PhD candidate at the School of Artificial Intelligence, Nanjing University, advisor: to be supplemented

Background

Currently a final-year PhD candidate at the School of Artificial Intelligence, Nanjing University (NJU), and a member of the NJU-NLP Research Group. Recent works mainly focus on in-context learning, multi-modal information extraction, multi-modal large language models, and NLP applications.

Miscellany