Koustuv Sinha

784 total citations
20 papers, 203 citations indexed

About

Koustuv Sinha is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Koustuv Sinha has authored 20 papers receiving a total of 203 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 1 paper in Computer Networks and Communications. Recurrent topics in Koustuv Sinha's work include Topic Modeling (12 papers), Natural Language Processing Techniques (10 papers) and Multimodal Machine Learning Applications (3 papers). Koustuv Sinha is often cited by papers focused on Topic Modeling (12 papers), Natural Language Processing Techniques (10 papers) and Multimodal Machine Learning Applications (3 papers). Koustuv Sinha collaborates with scholars based in Canada, United States and Israel. Koustuv Sinha's co-authors include Joëlle Pineau, Dieuwke Hupkes, Adina Williams, Robin Jia, Douwe Kiela, Derek Ruths, Jackie Chi Kit Cheung, Yue Dong, Jessica Zosa Forde and Hugo Larochelle and has published in prestigious journals such as Nature Machine Intelligence, Empirical Methods in Natural Language Processing and Repository for Publications and Research Data (ETH Zurich).

In The Last Decade

Koustuv Sinha

19 papers receiving 192 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Koustuv Sinha Canada	6	174	39	16	6	6	20	203
Dmitry Ustalov Russia	7	111 0.6×	40 1.0×	19 1.2×	9 1.5×	5 0.8×	32	174
Christopher Akiki Germany	4	133 0.8×	21 0.5×	14 0.9×	4 0.7×	6 1.0×	10	201
Alex Marin United States	9	184 1.1×	19 0.5×	24 1.5×	2 0.3×	3 0.5×	20	208
Arianna Ciula United Kingdom	8	68 0.4×	53 1.4×	29 1.8×	5 0.8×	2 0.3×	38	179
John Niekrasz United States	9	178 1.0×	17 0.4×	14 0.9×	12 2.0×	11 1.8×	21	214
Jasmijn Bastings United States	5	164 0.9×	37 0.9×	15 0.9×	8 1.3×	2 0.3×	8	195
Arjun Akula United States	8	121 0.7×	48 1.2×	5 0.3×	5 0.8×	5 0.8×	14	159
Junji Tomita Japan	9	137 0.8×	25 0.6×	22 1.4×	2 0.3×	14 2.3×	29	172
Liunian Harold Li United States	8	181 1.0×	112 2.9×	8 0.5×	2 0.3×	4 0.7×	11	229
Daniel Hesslow France	2	139 0.8×	24 0.6×	13 0.8×	4 0.7×	3 0.5×	4	194

Countries citing papers authored by Koustuv Sinha

Since Specialization

Citations

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

Fields of papers citing papers by Koustuv Sinha

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Koustuv Sinha

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

All Works

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20 of 20 papers shown

Shridhar, Kumar, Koustuv Sinha, Andrew Cohen, et al.. (2024). The ART of LLM Refinement: Ask, Refine, and Trust. Repository for Publications and Research Data (ETH Zurich). 5872–5883. 2 indexed citations

Wan, David, et al.. (2024). ACUEval: Fine-grained Hallucination Evaluation and Correction for Abstractive Summarization. 10036–10056.

Hupkes, Dieuwke, Mario Giulianelli, Verna Dankers, et al.. (2023). A taxonomy and review of generalization research in NLP. Nature Machine Intelligence. 5(10). 1161–1174. 29 indexed citations

Sinha, Koustuv, Jon Gauthier, Aaron Mueller, et al.. (2023). Language model acceptability judgements are not always robust to context. 6043–6063. 6 indexed citations

Dessì, Roberto, et al.. (2023). Robustness of Named-Entity Replacements for In-Context Learning. 10914–10931. 2 indexed citations

Sinha, Koustuv, et al.. (2023). ML Reproducibility Challenge 2022. Zenodo (CERN European Organization for Nuclear Research). 7 indexed citations

Sharma, Shanya, Manan Dey, & Koustuv Sinha. (2022). How sensitive are translation systems to extra contexts? Mitigating gender bias in Neural Machine Translation models through relevant contexts.. 1968–1984. 3 indexed citations

Sinha, Koustuv, et al.. (2022). The Curious Case of Absolute Position Embeddings. 4449–4472. 3 indexed citations

Lučić, Ana, et al.. (2022). Towards Reproducible Machine Learning Research in Natural Language Processing. UvA-DARE (University of Amsterdam). 7–11. 1 indexed citations

10.

Lučić, Ana, et al.. (2022). Towards Reproducible Machine Learning Research in Information Retrieval. Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. 3459–3461. 1 indexed citations

11.

Sinha, Koustuv, et al.. (2021). Sometimes We Want Ungrammatical Translations. Empirical Methods in Natural Language Processing. 3205–3227. 1 indexed citations

12.

Sinha, Koustuv, Robin Jia, Dieuwke Hupkes, et al.. (2021). Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. 2888–2913. 88 indexed citations

13.

Sinha, Koustuv, et al.. (2021). ML Reproducibility Challenge 2020. Zenodo (CERN European Organization for Nuclear Research). 3 indexed citations

14.

Sinha, Koustuv, Robin Jia, Dieuwke Hupkes, et al.. (2021). Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little. arXiv (Cornell University). 2888–2913. 1 indexed citations

15.

Sinha, Koustuv, Shagun Sodhani, Joëlle Pineau, & William L. Hamilton. (2021). GraphLog: A Benchmark for Measuring Logical Generalization in Graph Neural Networks. 1 indexed citations

16.

Sinha, Koustuv, et al.. (2020). Measuring Systematic Generalization in Neural Proof Generation with Transformers. Neural Information Processing Systems. 33. 22231–22242. 4 indexed citations

17.

Sinha, Koustuv, et al.. (2020). NeurIPS 2019 Reproducibility Challenge. Zenodo (CERN European Organization for Nuclear Research). 5 indexed citations

18.

Pineau, Joëlle, et al.. (2019). ICLR Reproducibility Challenge 2019. Zenodo (CERN European Organization for Nuclear Research). 3 indexed citations

19.

Sinha, Koustuv, Yue Dong, Jackie Chi Kit Cheung, & Derek Ruths. (2018). A Hierarchical Neural Attention-based Text Classifier. 817–823. 37 indexed citations

20.

Piper, Andrew, et al.. (2017). Studying Literary Characters and Character Networks.. DH. 6 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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