Eric Wallace

3.8k total citations · 1 hit paper
20 papers, 1.1k citations indexed

About

Eric Wallace is a scholar working on Artificial Intelligence, Signal Processing and General Health Professions. According to data from OpenAlex, Eric Wallace has authored 20 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 3 papers in Signal Processing and 2 papers in General Health Professions. Recurrent topics in Eric Wallace's work include Topic Modeling (7 papers), Adversarial Robustness in Machine Learning (7 papers) and Natural Language Processing Techniques (6 papers). Eric Wallace is often cited by papers focused on Topic Modeling (7 papers), Adversarial Robustness in Machine Learning (7 papers) and Natural Language Processing Techniques (6 papers). Eric Wallace collaborates with scholars based in United States, Israel and United Kingdom. Eric Wallace's co-authors include Sameer Singh, Robert L. Logan, Taylor Shin, Junlin Wang, Matt Gardner, Sebastian Riedel, Ivana Balažević, Fabio Petroni, Mitchell Stern and Dawn Song and has published in prestigious journals such as Radiology, Journal of Science Education and Technology and Youth & Society.

In The Last Decade

Eric Wallace

20 papers receiving 1.0k 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.

AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts

2020 674 citations Taylor Shin, Robert L. Logan et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Eric Wallace United States	12	857	287	94	47	36	20	1.1k
Jason Wei United States	11	1.1k 1.3×	203 0.7×	173 1.8×	72 1.5×	11 0.3×	16	1.4k
Josua Krause United States	5	335 0.4×	241 0.8×	31 0.3×	58 1.2×	34 0.9×	7	494
Anagha Kulkarni United States	14	331 0.4×	111 0.4×	180 1.9×	81 1.7×	41 1.1×	54	627
James Wexler United States	7	409 0.5×	211 0.7×	60 0.6×	28 0.6×	87 2.4×	13	641
Nazik Alturki Saudi Arabia	16	594 0.7×	135 0.5×	113 1.2×	52 1.1×	19 0.5×	50	1.1k
Tong Yu United States	11	228 0.3×	188 0.7×	92 1.0×	34 0.7×	22 0.6×	61	618
Saad Amin United Kingdom	10	304 0.4×	387 1.3×	83 0.9×	43 0.9×	31 0.9×	68	745
Faisal Ahmed Bangladesh	10	386 0.5×	367 1.3×	73 0.8×	31 0.7×	5 0.1×	32	739
Henry R. Ehrenberg United States	5	499 0.6×	98 0.3×	107 1.1×	47 1.0×	14 0.4×	7	670
Hadi Veisi Iran	15	522 0.6×	81 0.3×	113 1.2×	195 4.1×	33 0.9×	94	838

Countries citing papers authored by Eric Wallace

Since Specialization

Citations

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

Fields of papers citing papers by Eric Wallace

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eric Wallace

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

20 of 20 papers shown

1.

Guan, Melody Y., Manas Joglekar, Eric Wallace, et al.. (2025). Deliberative Alignment: Reasoning Enables Safer Language Models. 2(3). 4 indexed citations

2.

Logan, Robert, Ivana Balažević, Eric Wallace, et al.. (2022). Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models. Findings of the Association for Computational Linguistics: ACL 2022. 2824–2835. 84 indexed citations

3.

Wallace, Eric, et al.. (2022). Prioritizing Radiological Threats: Frameworks for Assessing Risks to Radioactive Materials.. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1 indexed citations

4.

Wallace, Eric, et al.. (2022). Automated Crossword Solving. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 3 indexed citations

5.

Wallace, Eric, Adina Williams, Robin Jia, & Douwe Kiela. (2022). Analyzing Dynamic Adversarial Training Data in the Limit. Findings of the Association for Computational Linguistics: ACL 2022. 202–217. 5 indexed citations

6.

Xu, Albert, et al.. (2021). Detoxifying Language Models Risks Marginalizing Minority Voices. 2390–2397. 35 indexed citations

7.

Li, Zhuohan, Eric Wallace, Sheng Shen, et al.. (2020). Train Big, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers. International Conference on Machine Learning. 1. 5958–5968. 39 indexed citations

8.

Wang, Junlin, et al.. (2020). Gradient-based Analysis of NLP Models is Manipulable. 247–258. 26 indexed citations

9.

Wallace, Eric, Mitchell Stern, & Dawn Song. (2020). Imitation Attacks and Defenses for Black-box Machine Translation Systems. 5531–5546. 43 indexed citations

10.

Shin, Taylor, et al.. (2020). AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts. 4222–4235. 674 indexed citations breakdown →

11.

Wallace, Eric, Matt Gardner, & Sameer Singh. (2020). Interpreting Predictions of NLP Models. 20–23. 14 indexed citations

12.

Wallace, Eric, et al.. (2019). Universal Adversarial Triggers for NLP.. arXiv (Cornell University). 7 indexed citations

13.

Wallace, Eric, et al.. (2019). AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models. 62 indexed citations

14.

Wallace, Eric. (2019). A Discussion of 'Adversarial Examples Are Not Bugs, They Are Features': Learning from Incorrectly Labeled Data. 4(8). 1 indexed citations

15.

Engstrom, Logan, Justin Gilmer, Gabriel Goh, et al.. (2019). A Discussion of 'Adversarial Examples Are Not Bugs, They Are Features'. 4(8). 12 indexed citations

16.

Perry, Justin C., Eric Wallace, & Meghan P. McCormick. (2016). Making My Future Work: Evaluation of a New College and Career Readiness Curriculum. Youth & Society. 50(6). 841–866. 11 indexed citations

17.

Wallace, Eric, et al.. (2014). The Careers in Health and Medical Professions Program (CHAMPS): An Impact Study of a University-Based STEM+H Outreach Program. Journal of Science Education and Technology. 24(4). 484–495. 17 indexed citations

18.

Perry, Justin C. & Eric Wallace. (2013). Career Issues and Social Class. Oxford University Press eBooks. 2 indexed citations

19.

Perry, Justin C. & Eric Wallace. (2012). What schools are doing around career development: Implications for policy and practice. New Directions for Youth Development. 2012(134). 33–44. 3 indexed citations

20.

Wallace, Eric. (2004). The Dural Tail Sign. Radiology. 233(1). 56–57. 31 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.

Explore authors with similar magnitude of impact