Saksham Singhal

1.4k total citations · 1 hit paper
10 papers, 507 citations indexed

About

Saksham Singhal is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics. According to data from OpenAlex, Saksham Singhal has authored 10 papers receiving a total of 507 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 1 paper in Statistical and Nonlinear Physics. Recurrent topics in Saksham Singhal's work include Topic Modeling (7 papers), Natural Language Processing Techniques (6 papers) and Speech Recognition and Synthesis (4 papers). Saksham Singhal is often cited by papers focused on Topic Modeling (7 papers), Natural Language Processing Techniques (6 papers) and Speech Recognition and Synthesis (4 papers). Saksham Singhal collaborates with scholars based in China, United States and India. Saksham Singhal's co-authors include Furu Wei, Wenhui Wang, Li Dong, Song Xia, Zewen Chi, Hangbo Bao, Dong Li, Zhiliang Peng, Xian-Ling Mao and Kriti Aggarwal and has published in prestigious journals such as Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) and Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.

In The Last Decade

Saksham Singhal

10 papers receiving 490 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.

Image as a Foreign Language: BEIT Pretraining for Vision and Vision-Language Tasks

2023 247 citations Wenhui Wang, Hangbo Bao et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Saksham Singhal China	7	368	289	25	20	15	10	507
Hangbo Bao China	5	279 0.8×	231 0.8×	16 0.6×	23 1.1×	18 1.2×	8	432
Juhua Hu United States	9	246 0.7×	249 0.9×	27 1.1×	10 0.5×	18 1.2×	27	390
Emmanuel Bengio Canada	3	303 0.8×	157 0.5×	17 0.7×	12 0.6×	18 1.2×	4	379
Maxinder S Kanwal Poland	2	292 0.8×	157 0.5×	17 0.7×	10 0.5×	18 1.2×	2	367
Şerafettin Taşcı Türkiye	6	278 0.8×	191 0.7×	16 0.6×	40 2.0×	30 2.0×	7	347
А.В. Куракин United States	6	284 0.8×	151 0.5×	21 0.8×	14 0.7×	23 1.5×	8	361
Jing Yu China	13	443 1.2×	499 1.7×	19 0.8×	44 2.2×	6 0.4×	49	682
Vedanuj Goswami United States	7	410 1.1×	421 1.5×	27 1.1×	15 0.8×	22 1.5×	13	581
Thalaiyasingam Ajanthan Australia	7	226 0.6×	239 0.8×	9 0.4×	9 0.5×	21 1.4×	19	333

Countries citing papers authored by Saksham Singhal

Since Specialization

Citations

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

Fields of papers citing papers by Saksham Singhal

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Saksham Singhal

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

10 of 10 papers shown

1.

Patra, Barun, Saksham Singhal, Shaohan Huang, et al.. (2023). Beyond English-Centric Bitexts for Better Multilingual Language Representation Learning. 15354–15373. 6 indexed citations

2.

Lv, Tengchao, et al.. (2023). Language Is Not All You Need: Aligning Perception with Language Models. 72096–72109. 1 indexed citations

3.

Singhal, Saksham, et al.. (2023). Deepfake Detection: A Multi-Algorithmic and Multi-Modal Approach for Robust Detection and Analysis. 1–8. 1 indexed citations

4.

Wang, Wenhui, Hangbo Bao, Dong Li, et al.. (2023). Image as a Foreign Language: BEIT Pretraining for Vision and Vision-Language Tasks. 19175–19186. 247 indexed citations breakdown →

5.

Chi, Zewen, Shaohan Huang, Li Dong, et al.. (2022). XLM-E: Cross-lingual Language Model Pre-training via ELECTRA. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 6170–6182. 40 indexed citations

6.

Chi, Zewen, Li Dong, Furu Wei, et al.. (2021). InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training. 3576–3588. 143 indexed citations

7.

Chi, Zewen, Li Dong, Shuming Ma, et al.. (2021). mT6: Multilingual Pretrained Text-to-Text Transformer with Translation Pairs. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. 1671–1683. 36 indexed citations

8.

Zheng, Bo, Li Dong, Shaohan Huang, et al.. (2021). Consistency Regularization for Cross-Lingual Fine-Tuning. 3403–3417. 20 indexed citations

9.

Zheng, Bo, Li Dong, Shaohan Huang, et al.. (2021). Allocating Large Vocabulary Capacity for Cross-Lingual Language Model Pre-Training. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. 3203–3215. 12 indexed citations

10.

Singhal, Saksham & Vikram Pudi. (2015). Dispersion Based Similarity for Mining Similar Papers in Citation Network. 524–531. 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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