Margaret Mitchell

14.8k total citations · 5 hit papers
64 papers, 6.7k citations indexed

About

Margaret Mitchell is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Safety Research. According to data from OpenAlex, Margaret Mitchell has authored 64 papers receiving a total of 6.7k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Artificial Intelligence, 23 papers in Computer Vision and Pattern Recognition and 8 papers in Safety Research. Recurrent topics in Margaret Mitchell's work include Topic Modeling (22 papers), Multimodal Machine Learning Applications (16 papers) and Natural Language Processing Techniques (16 papers). Margaret Mitchell is often cited by papers focused on Topic Modeling (22 papers), Multimodal Machine Learning Applications (16 papers) and Natural Language Processing Techniques (16 papers). Margaret Mitchell collaborates with scholars based in United States, United Kingdom and Australia. Margaret Mitchell's co-authors include C. Lawrence Zitnick, Aishwarya Agrawal, Dhruv Batra, Devi Parikh, Jiasen Lu, Stanislaw Antol, Kristy Hollingshead, Ben Hutchinson, Xiaodong He and Saurabh Gupta and has published in prestigious journals such as Journal of Consulting and Clinical Psychology, International Journal of Computer Vision and Cognitive Science.

In The Last Decade

Margaret Mitchell

63 papers receiving 6.4k citations

Hit Papers

5 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.

VQA: Visual Question Answering

2015 2.3k citations Aishwarya Agrawal, Margaret Mitchell et al. profile →
From captions to visual concepts and back

2015 774 citations Xiaodong He, Margaret Mitchell et al. profile →
A Neural Network Approach to Context-Sensitive Generation of Conversational Responses

2015 432 citations Alessandro Sordoni, Michel Galley et al. profile →
Closing the AI accountability gap

2020 407 citations Margaret Mitchell et al. profile →
VQA: Visual Question Answering

2016 345 citations Aishwarya Agrawal, Margaret Mitchell et al. profile →

Peers

Countries citing papers authored by Margaret Mitchell

Since Specialization

Citations

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

Fields of papers citing papers by Margaret Mitchell

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Margaret Mitchell

This figure shows the co-authorship network connecting the top 25 collaborators of Margaret Mitchell. A scholar is included among the top collaborators of Margaret 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 Margaret Mitchell. Margaret Mitchell 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

#	Work	Indexed citations
1	CIVICS: Building a Dataset for Examining Culturally-Informed Values in Large Language Models 2024 ·Proceedings of the AAAI/ACM Conference on AI Ethics and Society ·(unknown), (unknown), Yacine Jernite, Atoosa Kasirzadeh, Alexandra Sasha Luccioni, Margaret Mitchell	3
2	Stronger Together: on the Articulation of Ethical Charters, Legal Tools, and Technical Documentation in ML 2023 ·arXiv (Cornell University) ·(unknown), (unknown), Yacine Jernite, Margaret Mitchell	7
3	Detecting Personal Information in Training Corpora: an Analysis 2023 ·Nishant Subramani, Alexandra Sasha Luccioni, Jesse Dodge, Margaret Mitchell	8
4	SEAL: Interactive Tool for Systematic Error Analysis and Labeling 2022 ·Nazneen Fatema Rajani, Weixin Liang, Lingjiao Chen, Margaret Mitchell, James Zou	7
5	Algorithmic fairness in pandemic forecasting: lessons from COVID-19 2022 ·npj Digital Medicine ·Thomas C. Tsai, Sercan Ö. Arık, (unknown), Jinsung Yoon, Nathanael C. Yoder, (unknown), Margaret Mitchell, Garth Graham, Tomas Pfister	6
6	Visual Storytelling 2016 ·Ting-Hao Huang, Francis Ferraro, Nasrin Mostafazadeh, Ishan Misra, Aishwarya Agrawal, Jacob Devlin, Ross Girshick, Xiaodong He, Pushmeet Kohli, Dhruv Batra, C. Lawrence Zitnick, Devi Parikh, Lucy Vanderwende, Michel Galley, Margaret Mitchell	138
7	On Available Corpora for Empirical Methods in Vision & Language. 2015 ·arXiv (Cornell University) ·Francis Ferraro, Nasrin Mostafazadeh, Ting-Hao Huang, Lucy Vanderwende, Jacob Devlin, Michel Galley, Margaret Mitchell	1
8	Learning Visual Classifiers using Human-centric Annotations. 2015 ·arXiv (Cornell University) ·Ishan Misra, C. Lawrence Zitnick, Margaret Mitchell, Ross Girshick	2
9	CLPsych 2015 Shared Task: Depression and PTSD on Twitter 2015 ·Glen Coppersmith, Mark Dredze, Craig Harman, Kristy Hollingshead, Margaret Mitchell	202
10	A Neural Network Approach to Context-Sensitive Generation of Conversational Responses breakdown → 2015 ·Alessandro Sordoni, Michel Galley, Michael Auli, Chris Brockett, Yangfeng Ji, Margaret Mitchell, Jian‐Yun Nie, Jianfeng Gao, Bill Dolan	432
11	Crowdsourcing Language Generation Templates for Dialogue Systems 2014 ·Margaret Mitchell, Dan Bohus, Ece Kamar	13
12	Overview of the TAC2013 Knowledge Base Population Evaluation: English Sentiment Slot Filling. 2013 ·Theory and applications of categories ·Margaret Mitchell	8
13	Graphs and Spatial Relations in the Generation of Referring Expressions 2013 ·Jette Viethen, Margaret Mitchell, Emiel Krahmer	8
14	Understanding and predicting importance in images 2012 ·Alexander C. Berg, Torres Berg, Hal Daumé, Jennifer L. Dodge, Amit Goyal, Xufeng Han, Alexander Mensch, Margaret Mitchell, Arun Sood, Karl Stratos, Kota Yamaguchi	94
15	Midge: Generating Image Descriptions From Computer Vision Detections 2012 ·Conference of the European Chapter of the Association for Computational Linguistics ·Margaret Mitchell, Jesse Dodge, Amit Goyal, Kota Yamaguchi, Karl Stratos, Xufeng Han, Alyssa Mensch, (unknown), Tamara L. Berg, Hal Daumé	251
16	On the Use of Size Modifiers When Referring to Visible Objects 2011 ·Cognitive Science ·Margaret Mitchell, Kees van Deemter, Ehud Reiter	5
17	Semi-Supervised Modeling for Prenominal Modifier Ordering 2011 ·Meeting of the Association for Computational Linguistics ·Margaret Mitchell, (unknown), Brian Roark	6
18	Two Approaches for Generating Size Modifiers 2011 ·Margaret Mitchell, Kees van Deemter, Ehud Reiter	6
19	Prenominal Modifier Ordering via Multiple Sequence Alignment 2010 ·North American Chapter of the Association for Computational Linguistics ·(unknown), Margaret Mitchell, Brian Roark	3
20	Autant en emporte le vent 2003 ·Gallimard eBooks ·Margaret Mitchell, (unknown)	1

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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