Ashwin Paranjape

1.1k total citations · 1 hit paper
7 papers, 325 citations indexed

About

Ashwin Paranjape is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Ashwin Paranjape has authored 7 papers receiving a total of 325 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 1 paper in Information Systems and 1 paper in Computer Vision and Pattern Recognition. Recurrent topics in Ashwin Paranjape's work include Topic Modeling (7 papers), Natural Language Processing Techniques (5 papers) and Speech and dialogue systems (3 papers). Ashwin Paranjape is often cited by papers focused on Topic Modeling (7 papers), Natural Language Processing Techniques (5 papers) and Speech and dialogue systems (3 papers). Ashwin Paranjape collaborates with scholars based in United States, India and South Korea. Ashwin Paranjape's co-authors include Percy Liang, Kevin Lin, John Hewitt, Nelson F. Liu, Fabio Petroni, Michele Bevilacqua, Devendra Singh Chaplot, Pushpak Bhattacharyya, Christopher D. Manning and Arun Tejasvi Chaganty and has published in prestigious journals such as Transactions of the Association for Computational Linguistics, Theory and applications of categories and Proceedings of the AAAI Conference on Artificial Intelligence.

In The Last Decade

Ashwin Paranjape

7 papers receiving 304 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.

Lost in the Middle: How Language Models Use Long Contexts

2024 285 citations Nelson F. Liu, Kevin Lin et al. Transactions of the Association for Computational Linguistics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ashwin Paranjape United States	4	195	54	39	26	25	7	325
Stefano Teso Italy	10	207 1.1×	29 0.5×	43 1.1×	57 2.2×	19 0.8×	34	308
Qingxiu Dong China	7	199 1.0×	39 0.7×	50 1.3×	18 0.7×	10 0.4×	11	297
Lukas Gianinazzi Switzerland	6	139 0.7×	28 0.5×	51 1.3×	30 1.2×	10 0.4×	14	225
Xinxi Lyu United States	4	370 1.9×	60 1.1×	107 2.7×	25 1.0×	23 0.9×	4	490
Wanjun Zhong China	11	411 2.1×	155 2.9×	65 1.7×	12 0.5×	13 0.5×	36	543
Jungo Kasai United States	13	415 2.1×	55 1.0×	139 3.6×	11 0.4×	8 0.3×	39	538
Zhijing Jin United States	12	807 4.1×	91 1.7×	116 3.0×	35 1.3×	25 1.0×	34	900
Mohamed Yehia Dahab Saudi Arabia	7	190 1.0×	81 1.5×	18 0.5×	34 1.3×	4 0.2×	25	264
Ruotian Ma China	7	584 3.0×	65 1.2×	59 1.5×	27 1.0×	7 0.3×	14	630
Walaa Gad Egypt	9	125 0.6×	95 1.8×	32 0.8×	27 1.0×	3 0.1×	42	264

Countries citing papers authored by Ashwin Paranjape

Since Specialization

Citations

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

Fields of papers citing papers by Ashwin Paranjape

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ashwin Paranjape

This figure shows the co-authorship network connecting the top 25 collaborators of Ashwin Paranjape. A scholar is included among the top collaborators of Ashwin Paranjape 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 Ashwin Paranjape. Ashwin Paranjape 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:

7 of 7 papers shown

1.

Liu, Nelson F., Kevin Lin, John Hewitt, et al.. (2024). Lost in the Middle: How Language Models Use Long Contexts. Transactions of the Association for Computational Linguistics. 12. 157–173. 285 indexed citations breakdown →

2.

Paranjape, Ashwin, et al.. (2022). When can I Speak? Predicting initiation points for spoken dialogue agents. 217–224. 1 indexed citations

3.

Paranjape, Ashwin, et al.. (2021). Effective Social Chatbot Strategies for Increasing User Initiative. 99–110. 2 indexed citations

4.

Chaganty, Arun Tejasvi, Ashwin Paranjape, Jason Bolton, et al.. (2017). Stanford at TAC KBP 2017: Building a Trilingual Relational Knowledge Graph.. Theory and applications of categories. 2 indexed citations

5.

Chaganty, Arun Tejasvi, Ashwin Paranjape, Percy Liang, & Christopher D. Manning. (2017). Importance sampling for unbiased on-demand evaluation of knowledge base population. 1038–1048. 9 indexed citations

6.

Zhang, Yuhao, Arun Tejasvi Chaganty, Ashwin Paranjape, et al.. (2016). Stanford at TAC KBP 2016: Sealing Pipeline Leaks and Understanding Chinese.. Theory and applications of categories. 3 indexed citations

7.

Chaplot, Devendra Singh, Pushpak Bhattacharyya, & Ashwin Paranjape. (2015). Unsupervised Word Sense Disambiguation Using Markov Random Field and Dependency Parser. Proceedings of the AAAI Conference on Artificial Intelligence. 29(1). 23 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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