Linyong Nan

497 total citations
16 papers, 151 citations indexed

About

Linyong Nan is a scholar working on Artificial Intelligence, Information Systems and Communication. According to data from OpenAlex, Linyong Nan has authored 16 papers receiving a total of 151 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 2 papers in Information Systems and 1 paper in Communication. Recurrent topics in Linyong Nan's work include Topic Modeling (11 papers), Natural Language Processing Techniques (10 papers) and Advanced Text Analysis Techniques (4 papers). Linyong Nan is often cited by papers focused on Topic Modeling (11 papers), Natural Language Processing Techniques (10 papers) and Advanced Text Analysis Techniques (4 papers). Linyong Nan collaborates with scholars based in United States, China and United Kingdom. Linyong Nan's co-authors include Dragomir Radev, Yilun Zhao, Caiming Xiong, Yixin Liu, Arman Cohan, Rui Zhang, Pengfei Liu, Shafiq Joty, Wojciech Kryściński and Simeng Han and has published in prestigious journals such as Investigative Ophthalmology & Visual Science and Transactions of the Association for Computational Linguistics.

In The Last Decade

Linyong Nan

16 papers receiving 144 citations

Peers

Linyong Nan

AI

CVPR

MSOR

IS

COMMU

Karl Pichotta United States

Jiaao Chen United States

Yassine Benajiba United States

Petri Leskinen Finland

Aleksandra Piktus Germany

Martin Josifoski Switzerland

Karim Bouzoubaa Morocco

Daniel Gillick United States

Emanuela Boroş France

Or Honovich Israel

Karl Pichotta United States

Linyong Nan

207 ×1.6

AI

27 ×1.2

CVPR

19 ×0.9

MSOR

32 ×1.8

IS

3 ×0.5

COMMU

Citations per year, relative to Linyong Nan Linyong Nan (= 1×) peers Karl Pichotta

Countries citing papers authored by Linyong Nan

Since Specialization

Citations

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

Fields of papers citing papers by Linyong Nan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Linyong Nan

This figure shows the co-authorship network connecting the top 25 collaborators of Linyong Nan. A scholar is included among the top collaborators of Linyong Nan 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 Linyong Nan. Linyong Nan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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16 of 16 papers shown

1.

Nan, Linyong, et al.. (2024). On Evaluating the Integration of Reasoning and Action in LLM Agents with Database Question Answering. 4556–4579. 5 indexed citations

2.

Long, Yi‐Tao, Hongjun Liu, Linyong Nan, et al.. (2024). DocMath-Eval: Evaluating Math Reasoning Capabilities of LLMs in Understanding Long and Specialized Documents. 16103–16120. 2 indexed citations

3.

Zhang, Haowei, Yilun Zhao, Long Xie, et al.. (2024). OpenT2T: An Open-Source Toolkit for Table-to-Text Generation. 259–269. 1 indexed citations

4.

Zhao, Yilun, et al.. (2023). Investigating Table-to-Text Generation Capabilities of Large Language Models in Real-World Information Seeking Scenarios. 160–175. 3 indexed citations

5.

Zhao, Yilun, et al.. (2023). LoFT: Enhancing Faithfulness and Diversity for Table-to-Text Generation via Logic Form Control. 554–561. 5 indexed citations

6.

Zhao, Yilun, et al.. (2023). RobuT: A Systematic Study of Table QA Robustness Against Human-Annotated Adversarial Perturbations. 6064–6081. 3 indexed citations

7.

Zhao, Yilun, et al.. (2023). OpenRT: An Open-source Framework for Reasoning Over Tabular Data. 336–347. 2 indexed citations

8.

Nan, Linyong, et al.. (2023). Enhancing Text-to-SQL Capabilities of Large Language Models: A Study on Prompt Design Strategies. 14935–14956. 13 indexed citations

9.

Zhao, Yilun, Linyong Nan, Yixin Liu, et al.. (2023). QTSumm: Query-Focused Summarization over Tabular Data. 1157–1172. 1 indexed citations

10.

Liu, Yixin, Pengfei Liu, Yilun Zhao, et al.. (2023). Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human Evaluation. 4140–4170. 32 indexed citations

11.

Nan, Linyong, et al.. (2022). R2D2: Robust Data-to-Text with Replacement Detection. 6903–6917. 7 indexed citations

12.

Liu, Yixin, Ansong Ni, Linyong Nan, et al.. (2022). Leveraging Locality in Abstractive Text Summarization. 6081–6093. 13 indexed citations

13.

Zhao, Yilun, et al.. (2022). ReasTAP: Injecting Table Reasoning Skills During Pre-training via Synthetic Reasoning Examples. 9006–9018. 6 indexed citations

14.

Nan, Linyong, Ziming Mao, Xi Lin, et al.. (2022). FeTaQA: Free-form Table Question Answering. Transactions of the Association for Computational Linguistics. 10. 35–49. 48 indexed citations

15.

Nan, Linyong, et al.. (2020). Detecting Urgency Status of Crisis Tweets: A Transfer Learning Approach for Low Resource Languages. 4693–4703. 9 indexed citations

16.

Thakoor, Kaveri A., Qian Zheng, Linyong Nan, et al.. (2019). Assessing the Ability of Convolutional Neural Networks to Detect Glaucoma from OCT Probability Maps. Investigative Ophthalmology & Visual Science. 60(9). 1464–1464. 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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