Reid Pryzant

1.0k total citations · 1 hit paper
15 papers, 448 citations indexed

About

Reid Pryzant is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Reid Pryzant has authored 15 papers receiving a total of 448 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 2 papers in Information Systems. Recurrent topics in Reid Pryzant's work include Topic Modeling (9 papers), Natural Language Processing Techniques (8 papers) and Multimodal Machine Learning Applications (3 papers). Reid Pryzant is often cited by papers focused on Topic Modeling (9 papers), Natural Language Processing Techniques (8 papers) and Multimodal Machine Learning Applications (3 papers). Reid Pryzant collaborates with scholars based in United States, Germany and Japan. Reid Pryzant's co-authors include Dan Jurafsky, Diyi Yang, Quoc V. Le, Denny Britz, Sadao Kurohashi, Chenguang Zhu, Dan Iter, Michael Zeng, Emaad Manzoor and Amir Feder and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Transactions of the Association for Computational Linguistics and Proceedings of the AAAI Conference on Artificial Intelligence.

In The Last Decade

Reid Pryzant

15 papers receiving 428 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.

Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond

2022 120 citations Amir Feder, Katherine A. Keith 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
Reid Pryzant United States	11	324	76	53	44	18	15	448
Marina Litvak Israel	11	418 1.3×	32 0.4×	97 1.8×	39 0.9×	22 1.2×	52	493
David Lillis Ireland	9	142 0.4×	46 0.6×	109 2.1×	9 0.2×	9 0.5×	33	266
Ilia Shumailov United Kingdom	8	188 0.6×	38 0.5×	68 1.3×	53 1.2×	9 0.5×	19	396
Baoxun Wang China	13	497 1.5×	54 0.7×	149 2.8×	20 0.5×	13 0.7×	33	578
K. Kavitha India	5	126 0.4×	36 0.5×	60 1.1×	23 0.5×	14 0.8×	14	290
Johann Petrak United Kingdom	8	311 1.0×	27 0.4×	92 1.7×	67 1.5×	28 1.6×	15	395
Gustavo Hernández Ábrego United States	6	473 1.5×	129 1.7×	68 1.3×	33 0.8×	13 0.7×	8	572
Mandy Guo United States	10	486 1.5×	125 1.6×	57 1.1×	28 0.6×	12 0.7×	11	566
Nelson F. Liu United States	5	294 0.9×	61 0.8×	64 1.2×	13 0.3×	32 1.8×	7	445

Countries citing papers authored by Reid Pryzant

Since Specialization

Citations

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

Fields of papers citing papers by Reid Pryzant

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Reid Pryzant

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

15 of 15 papers shown

1.

Yang, Ziyi, Mahmoud Khademi, Xu Yi‐chong, et al.. (2024). i-Code V2: An Autoregressive Generation Framework over Vision, Language, and Speech Data. 1615–1627. 2 indexed citations

2.

Pryzant, Reid, et al.. (2024). Prompt Engineering a Prompt Engineer. 355–385. 24 indexed citations

3.

Rho, Eugenia Ha Rim, et al.. (2023). Escalated police stops of Black men are linguistically and psychologically distinct in their earliest moments. Proceedings of the National Academy of Sciences. 120(23). e2216162120–e2216162120. 13 indexed citations

4.

Iter, Dan, Reid Pryzant, Ruochen Xu, et al.. (2023). In-Context Demonstration Selection with Cross Entropy Difference. 1150–1162. 1 indexed citations

5.

Sanyal, Soumya, Xu Yi‐chong, Ziyi Yang, et al.. (2023). APOLLO: A Simple Approach for Adaptive Pretraining of Language Models for Logical Reasoning. 3 indexed citations

6.

Yang, Ziyi, Yuwei Fang, Chenguang Zhu, et al.. (2023). i-Code: An Integrative and Composable Multimodal Learning Framework. Proceedings of the AAAI Conference on Artificial Intelligence. 37(9). 10880–10890. 20 indexed citations

7.

Liu, Yang, Ming Zhong, Yizhu Jiao, et al.. (2023). The Shifted and The Overlooked: A Task-oriented Investigation of User-GPT Interactions. 2375–2393. 4 indexed citations

8.

Pryzant, Reid, et al.. (2023). Automatic Prompt Optimization with “Gradient Descent” and Beam Search. 7957–7968. 55 indexed citations

9.

Feder, Amir, Katherine A. Keith, Emaad Manzoor, et al.. (2022). Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond. Transactions of the Association for Computational Linguistics. 10. 1138–1158. 120 indexed citations breakdown →

10.

Pryzant, Reid, et al.. (2020). Automatically Neutralizing Subjective Bias in Text. Proceedings of the AAAI Conference on Artificial Intelligence. 34(1). 480–489. 69 indexed citations

11.

Pryzant, Reid, Kelly Shen, Dan Jurafsky, & Stefan Wagner. (2018). Deconfounded Lexicon Induction for Interpretable Social Science. 1615–1625. 28 indexed citations

12.

Pryzant, Reid, et al.. (2018). Interpretable Neural Architectures for Attributing an Ad’s Performance to its Writing Style. 125–135. 11 indexed citations

13.

Pryzant, Reid, Youngjoo Chung, & Dan Jurafsky. (2017). Predicting Sales from the Language of Product Descriptions.. International ACM SIGIR Conference on Research and Development in Information Retrieval. 19 indexed citations

14.

Britz, Denny, Quoc V. Le, & Reid Pryzant. (2017). Effective Domain Mixing for Neural Machine Translation. 118–126. 55 indexed citations

15.

Pryzant, Reid, Stefano Ermon, & David B. Lobell. (2017). Monitoring Ethiopian Wheat Fungus with Satellite Imagery and Deep Feature Learning. 1524–1532. 24 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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