Eric Mitchell

4.5k total citations
11 papers, 77 citations indexed

About

Eric Mitchell is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Eric Mitchell has authored 11 papers receiving a total of 77 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 1 paper in Molecular Biology. Recurrent topics in Eric Mitchell's work include Topic Modeling (4 papers), Natural Language Processing Techniques (3 papers) and Multimodal Machine Learning Applications (2 papers). Eric Mitchell is often cited by papers focused on Topic Modeling (4 papers), Natural Language Processing Techniques (3 papers) and Multimodal Machine Learning Applications (2 papers). Eric Mitchell collaborates with scholars based in United States and South Korea. Eric Mitchell's co-authors include Chelsea Finn, Christopher D. Manning, Rafael Rafailov, Archit Sharma, Huaxiu Yao, Joseph J. Noh, Patrick Liu, Will J. Armstrong, Ananth Agarwal and Sergiy Popovych and has published in prestigious journals such as Nature Communications, Transportation Research Record Journal of the Transportation Research Board and arXiv (Cornell University).

In The Last Decade

Eric Mitchell

9 papers receiving 74 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Eric Mitchell United States	5	49	11	7	7	6	11	77
Prashant Shah United States	3	58 1.2×	6 0.5×	7 1.0×	9 1.3×	3 0.5×	5	79
Rafael Rafailov United States	3	37 0.8×	13 1.2×	5 0.7×	5 0.7×	4 0.7×	4	62
Ayesha Bajwa Hong Kong	3	48 1.0×	7 0.6×	5 0.7×	7 1.0×	6 1.0×	4	65
Maximin Coavoux France	4	85 1.7×	9 0.8×	11 1.6×	6 0.9×	4 0.7×	11	98
Ninareh Mehrabi United States	5	65 1.3×	7 0.6×	6 0.9×	6 0.9×	5 0.8×	14	83
Tosin Adewumi Sweden	7	73 1.5×	16 1.5×	8 1.1×	5 0.7×	3 0.5×	18	101
Nishant Subramani United States	5	40 0.8×	16 1.5×	7 1.0×	8 1.1×	3 0.5×	6	67
Sarah Tan United States	7	84 1.7×	6 0.5×	3 0.4×	18 2.6×	6 1.0×	11	120
Rajiv Mathews United States	7	90 1.8×	6 0.5×	11 1.6×	8 1.1×	2 0.3×	13	103
Nora Kassner Germany	3	116 2.4×	39 3.5×	7 1.0×	5 0.7×	5 0.8×	10	132

Countries citing papers authored by Eric Mitchell

Since Specialization

Citations

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

Fields of papers citing papers by Eric Mitchell

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eric Mitchell

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

All Works

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11 of 11 papers shown

1.

Lee, Yoonho, et al.. (2024). Calibrating Language Models with Adaptive Temperature Scaling. 18128–18138. 3 indexed citations

2.

Popovych, Sergiy, Thomas Macrina, Nico Kemnitz, et al.. (2024). Petascale pipeline for precise alignment of images from serial section electron microscopy. Nature Communications. 15(1). 289–289. 8 indexed citations

3.

Finn, Chelsea, et al.. (2024). A Critical Evaluation of AI Feedback for Aligning Large Language Models. 29166–29190.

4.

Mitchell, Eric, Archit Sharma, Rafael Rafailov, et al.. (2023). Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback. 5433–5442. 37 indexed citations

5.

Henderson, Peter, Eric Mitchell, Christopher D. Manning, Dan Jurafsky, & Chelsea Finn. (2023). Self-Destructing Models: Increasing the Costs of Harmful Dual Uses of Foundation Models. 287–296. 6 indexed citations

6.

Mitchell, Eric, et al.. (2023). Meta-Learning Online Adaptation of Language Models. 4 indexed citations

7.

Mitchell, Eric, Joseph J. Noh, Will J. Armstrong, et al.. (2022). Enhancing Self-Consistency and Performance of Pre-Trained Language Models through Natural Language Inference. 1754–1768. 13 indexed citations

8.

Mitchell, Eric, Chelsea Finn, & Christopher D. Manning. (2021). Challenges of Acquiring Compositional Inductive Biases via Meta-Learning. National Conference on Artificial Intelligence. 138–148.

9.

Mitchell, Eric, et al.. (2020). Higher-Order Function Networks for Learning Composable 3D Object Representations. arXiv (Cornell University). 2 indexed citations

10.

Eisner, Ben, et al.. (2019). QXplore: Q-Learning Exploration by Maximizing Temporal Difference Error. arXiv (Cornell University). 2 indexed citations

11.

Mitchell, Eric, et al.. (1996). Management Framework for Transit Pricing. Transportation Research Record Journal of the Transportation Research Board. 1521. 77–83. 2 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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