Fei Xia

1.9k total citations · 1 hit paper
55 papers, 1.0k citations indexed

About

Fei Xia is a scholar working on Artificial Intelligence, Molecular Biology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Fei Xia has authored 55 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Artificial Intelligence, 8 papers in Molecular Biology and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Fei Xia's work include Topic Modeling (38 papers), Natural Language Processing Techniques (37 papers) and Biomedical Text Mining and Ontologies (8 papers). Fei Xia is often cited by papers focused on Topic Modeling (38 papers), Natural Language Processing Techniques (37 papers) and Biomedical Text Mining and Ontologies (8 papers). Fei Xia collaborates with scholars based in United States, China and United Kingdom. Fei Xia's co-authors include Michael C. McCord, Yan Song, Imre Solti, Eithon Cadag, Özlem Uzuner, William D. Lewis, Meliha Yetisgen-Yildiz, Yuanhe Tian, Martha Palmer and Rajesh Bhatt and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, BMC Bioinformatics and Journal of the American Medical Informatics Association.

In The Last Decade

Fei Xia

54 papers receiving 944 citations

Hit Papers

align trajectories

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.

SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilities

2024 56 citations Brian Ichter, Dorsa Sadigh et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Fei Xia United States	16	820	187	115	71	46	55	1.0k
Zhuosheng Zhang China	20	1.3k 1.6×	59 0.3×	365 3.2×	125 1.8×	29 0.6×	73	1.5k
Elior Sulem Israel	8	611 0.7×	42 0.2×	85 0.7×	120 1.7×	22 0.5×	12	870
Ilana Heintz United States	5	386 0.5×	40 0.2×	54 0.5×	104 1.5×	21 0.5×	9	644
John Hewitt United States	8	771 0.9×	38 0.2×	183 1.6×	86 1.2×	7 0.2×	11	975
Saïd Ouatik El Alaoui Morocco	18	723 0.9×	120 0.6×	102 0.9×	158 2.2×	9 0.2×	81	909
Oscar Sainz Spain	4	432 0.5×	47 0.3×	66 0.6×	114 1.6×	22 0.5×	8	686
Marta R. Costa‐jussà Spain	18	1.6k 1.9×	80 0.4×	347 3.0×	112 1.6×	7 0.2×	149	1.7k
John DeNero United States	18	942 1.1×	61 0.3×	115 1.0×	60 0.8×	6 0.1×	52	1.1k
Hayley Ross United States	2	344 0.4×	41 0.2×	54 0.5×	102 1.4×	21 0.5×	4	587
Chengyu Wang China	15	570 0.7×	76 0.4×	140 1.2×	103 1.5×	7 0.2×	101	771

Countries citing papers authored by Fei Xia

Since Specialization

Citations

This map shows the geographic impact of Fei Xia'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 Fei Xia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fei Xia more than expected).

Fields of papers citing papers by Fei Xia

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fei Xia. 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 Fei Xia. The network helps show where Fei Xia may publish in the future.

Co-authorship network of co-authors of Fei Xia

This figure shows the co-authorship network connecting the top 25 collaborators of Fei Xia. A scholar is included among the top collaborators of Fei Xia 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 Fei Xia. Fei Xia 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

1.

Abacha, Asma Ben, et al.. (2025). MEDEC: A Benchmark for Medical Error Detection and Correction in Clinical Notes. 22539–22550. 2 indexed citations

2.

Tian, Yuanhe, Fei Xia, & Yan Song. (2024). Large Language Models Are No Longer Shallow Parsers. 7131–7142. 3 indexed citations

3.

Tian, Yuanhe, Fei Xia, & Yan Song. (2024). Dialogue Summarization with Mixture of Experts based on Large Language Models. 7143–7155. 5 indexed citations

4.

Cui, Yuchen, et al.. (2024). Distilling and Retrieving Generalizable Knowledge for Robot Manipulation via Language Corrections. 15172–15179. 10 indexed citations

5.

Sathyamoorthy, Adarsh Jagan, Brian Ichter, Fei Xia, et al.. (2024). CoNVOI: Context-aware Navigation using Vision Language Models in Outdoor and Indoor Environments. 13837–13844. 7 indexed citations

6.

Weng, Yixuan, et al.. (2023). Towards better Chinese-centric neural machine translation for low-resource languages. Computer Speech & Language. 84. 101566–101566. 12 indexed citations

7.

Weng, Yixuan, Fei Xia, Bin Li, et al.. (2023). Large Language Models are Better Reasoners with Self-Verification. 2550–2575. 29 indexed citations

8.

Xia, Fei, et al.. (2023). Find Parent then Label Children: A Two-stage Taxonomy Completion Method with Pre-trained Language Model. 1032–1042. 4 indexed citations

9.

Xia, Fei, Bin Li, Yixuan Weng, et al.. (2022). MedConQA: Medical Conversational Question Answering System based on Knowledge Graphs. 148–158. 9 indexed citations

10.

Tian, Yuanhe, Shen Wang, Yan Song, et al.. (2020). Improving biomedical named entity recognition with syntactic information. BMC Bioinformatics. 21(1). 539–539. 34 indexed citations

11.

Tian, Yuanhe, et al.. (2019). ChiMed: A Chinese Medical Corpus for Question Answering. 250–260. 18 indexed citations

12.

Zhang, Wei, et al.. (2018). Localized multi-kernel diagnosis model for avionics based on affinity propagation clustering. Beijing Hangkong Hangtian Daxue xuebao. 44(8). 1693. 1 indexed citations

13.

Antoniak, Maria, Eric B. Bell, & Fei Xia. (2015). Leveraging Paraphrase Labels to Extract Synonyms from Twitter. The Florida AI Research Society. 3–7. 2 indexed citations

14.

Liu, Qun & Fei Xia. (2014). Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Tutorial Abstracts. International Conference on Computational Linguistics. 7 indexed citations

15.

Xia, Fei, et al.. (2014). Enriching ODIN. Language Resources and Evaluation. 3151–3157. 2 indexed citations

16.

Evans, Heather L., et al.. (2013). Modeling annotator rationales with application to pneumonia classification. National Conference on Artificial Intelligence. 6 indexed citations

17.

Xia, Fei, et al.. (2010). Comparing Language Similarity across Genetic and Typologically-Based Groupings. International Conference on Computational Linguistics. 385–393. 21 indexed citations

18.

Yetisgen-Yildiz, Meliha, Imre Solti, Fei Xia, & Scott Halgrim. (2010). Preliminary Experiments with Amazon's Mechanical Turk for Annotating Medical Named Entities. North American Chapter of the Association for Computational Linguistics. 180–183. 22 indexed citations

19.

Xia, Fei & William D. Lewis. (2007). Multilingual Structural Projection across Interlinear Text. North American Chapter of the Association for Computational Linguistics. 452–459. 31 indexed citations

20.

Xia, Fei, et al.. (2006). Features, Bagging, and System Combination for the Chinese POS Tagging Task. Meeting of the Association for Computational Linguistics. 25–32. 1 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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