Hao Fei

3.4k total citations · 1 hit paper
83 papers, 1.3k citations indexed

About

Hao Fei is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Hao Fei has authored 83 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 70 papers in Artificial Intelligence, 20 papers in Computer Vision and Pattern Recognition and 6 papers in Molecular Biology. Recurrent topics in Hao Fei's work include Topic Modeling (58 papers), Natural Language Processing Techniques (36 papers) and Sentiment Analysis and Opinion Mining (24 papers). Hao Fei is often cited by papers focused on Topic Modeling (58 papers), Natural Language Processing Techniques (36 papers) and Sentiment Analysis and Opinion Mining (24 papers). Hao Fei collaborates with scholars based in China, Singapore and United States. Hao Fei's co-authors include Yafeng Ren, Donghong Ji, Donghong Ji, Fei Li, Shengqiong Wu, Meishan Zhang, Jingye Li, Bobo Li, Tat‐Seng Chua and Yue Zhang and has published in prestigious journals such as Bioinformatics, IEEE Transactions on Pattern Analysis and Machine Intelligence and Information Sciences.

In The Last Decade

Hao Fei

78 papers receiving 1.3k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Unified Named Entity Recognition as Word-Word Relation Classification

2022 158 citations Jingye Li, Hao Fei et al. Proceedings of the AAAI Conference on Artificial Intelligence profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Hao Fei	1.1k	194	113	98	93	83	1.3k
Shashi Narayan	1.3k 1.2×	174 0.9×	53 0.5×	86 0.9×	113 1.2×	32	1.5k
Xinyan Xiao	1.1k 0.9×	346 1.8×	89 0.8×	68 0.7×	125 1.3×	46	1.3k
Xingcheng Yao	1.1k 1.0×	322 1.7×	49 0.4×	63 0.6×	223 2.4×	3	1.4k
Zornitsa Kozareva	1.3k 1.2×	155 0.8×	99 0.9×	141 1.4×	225 2.4×	55	1.4k
Cícero dos Santos	1.8k 1.5×	211 1.1×	96 0.8×	138 1.4×	343 3.7×	11	1.9k
Claire Gardent	1.1k 1.0×	139 0.7×	42 0.4×	62 0.6×	108 1.2×	110	1.3k
Zhuosheng Zhang	1.3k 1.2×	365 1.9×	47 0.4×	59 0.6×	125 1.3×	73	1.5k
Antoine Bosselut	1.0k 0.9×	259 1.3×	58 0.5×	55 0.6×	107 1.2×	49	1.1k
Mikel Artetxe	1.4k 1.2×	337 1.7×	44 0.4×	49 0.5×	115 1.2×	35	1.6k
Houfeng Wang	1.9k 1.6×	287 1.5×	57 0.5×	67 0.7×	298 3.2×	99	2.1k

Countries citing papers authored by Hao Fei

Since Specialization

Citations

This map shows the geographic impact of Hao Fei's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hao Fei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hao Fei more than expected).

Fields of papers citing papers by Hao Fei

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hao Fei. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hao Fei. The network helps show where Hao Fei may publish in the future.

Co-authorship network of co-authors of Hao Fei

This figure shows the co-authorship network connecting the top 25 collaborators of Hao Fei. A scholar is included among the top collaborators of Hao Fei based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hao Fei. Hao Fei is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Xiao, Wei, et al.. (2024). Divide and Conquer: Legal Concept-guided Criminal Court View Generation. 3395–3410.

Zhang, Meishan, Hao Fei, Bin Wang, et al.. (2024). Recognizing Everything from All Modalities at Once: Grounded Multimodal Universal Information Extraction. 14498–14511. 3 indexed citations

Xu, Dawei, Chengniu Wang, Wei Liu, et al.. (2024). MiR-184-3p in the paraventricular nucleus participates in the neurobiology of depression via regulation of the hypothalamus-pituitary-adrenal axis. Neuropharmacology. 260. 110129–110129. 3 indexed citations

Zheng, Li, Hao Fei, Fei Li, et al.. (2024). Reverse Multi-Choice Dialogue Commonsense Inference with Graph-of-Thought. Proceedings of the AAAI Conference on Artificial Intelligence. 38(17). 19688–19696. 2 indexed citations

Li, Bobo, Hao Fei, Shengqiong Wu, et al.. (2024). MMLSCU: A Dataset for Multi-modal Multi-domain Live Streaming Comment Understanding. 4395–4406.

Fei, Hao, et al.. (2024). Fine-grained Structural Hallucination Detection for Unified Visual Comprehension and Generation in Multimodal LLM. 13–22. 5 indexed citations

Fei, Hao, et al.. (2024). S ³ Agent: Unlocking the Power of VLLM for Zero-Shot Multi-Modal Sarcasm Detection. ACM Transactions on Multimedia Computing Communications and Applications. 21(11). 1–16. 2 indexed citations

Fei, Hao, Bobo Li, Shengqiong Wu, et al.. (2024). PanoSent: A Panoptic Sextuple Extraction Benchmark for Multimodal Conversational Aspect-based Sentiment Analysis. ResearchSpace (University of Auckland). 7667–7676. 6 indexed citations

Chen, Boyu, Hao Fei, Shengqiong Wu, et al.. (2024). Self-Adaptive Fine-grained Multi-modal Data Augmentation for Semi-supervised Muti-modal Coreference Resolution. 8576–8585. 1 indexed citations

10.

Liu, Jiang, Hao Fei, Fei Li, et al.. (2024). TKDP: Threefold Knowledge-Enriched Deep Prompt Tuning for Few-Shot Named Entity Recognition. IEEE Transactions on Knowledge and Data Engineering. 36(11). 6397–6409. 8 indexed citations

11.

Zhou, Chengjie, Bobo Li, Hao Fei, et al.. (2024). Revisiting Structured Sentiment Analysis as Latent Dependency Graph Parsing. 10178–10191.

12.

Li, Bobo, Hao Fei, Fei Li, Tat‐Seng Chua, & Donghong Ji. (2024). Multimodal Emotion-Cause Pair Extraction with Holistic Interaction and Label Constraint. ACM Transactions on Multimedia Computing Communications and Applications. 21(11). 1–19. 2 indexed citations

13.

Xiao, Wei, et al.. (2024). Guided Knowledge Generation with Language Models for Commonsense Reasoning. 1103–1136. 1 indexed citations

14.

Fei, Hao, Bobo Li, Qian Liu, et al.. (2023). Reasoning Implicit Sentiment with Chain-of-Thought Prompting. 1171–1182. 45 indexed citations

15.

Fei, Hao, et al.. (2023). Syntax-based dynamic latent graph for event relation extraction. Information Processing & Management. 60(5). 103469–103469. 15 indexed citations

16.

Wu, Shengqiong, Hao Fei, Wei Ji, & Tat‐Seng Chua. (2023). Cross2StrA: Unpaired Cross-lingual Image Captioning with Cross-lingual Cross-modal Structure-pivoted Alignment. 8 indexed citations

17.

Fei, Hao, Qian Liu, Meishan Zhang, Min Zhang, & Tat‐Seng Chua. (2023). Scene Graph as Pivoting: Inference-time Image-free Unsupervised Multimodal Machine Translation with Visual Scene Hallucination. 5980–5994. 13 indexed citations

18.

Huang, Chenyu, Zheng Zhang, Hao Fei, & Lizi Liao. (2022). Conversation Disentanglement with Bi-Level Contrastive Learning. 2985–2996. 4 indexed citations

19.

Xu, Han, et al.. (2022). Cross-Lingual Contrastive Learning for Fine-Grained Entity Typing for Low-Resource Languages. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2241–2250. 12 indexed citations

20.

Wang, Fengqi, Fei Li, Hao Fei, et al.. (2022). Entity-centered Cross-document Relation Extraction. 9871–9881. 7 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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