Dan Iter
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 5%
- Topic Modeling
- Natural Language Processing Techniques
- Machine Learning in Healthcare
- Speech and dialogue systems
- Advanced Text Analysis Techniques
Papers in ⓘ
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- Topic Modeling 13
- Natural Language Processing Techniques 9
- Text Readability and Simplification 3
- Machine Learning and Data Classification 2
- Semantic Web and Ontologies 1
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- Cloud Computing and Resource Management 2
- Co-authors
- Chenguang Zhu (6 shared papers)Xu Yi‐chong (4 shared papers)Yang Liu (6 shared papers)Ruochen Xu (3 shared papers)Shuohang Wang (3 shared papers)Dan Jurafsky (3 shared papers)Jong‐Woo Yoon (1 shared paper)Kelvin Guu (1 shared paper)
- Journals
- Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (1 paper)Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (1 paper)arXiv (Cornell University) (1 paper)USENIX Annual Technical Conference (1 paper)
- Partner nations
- United StatesFranceGermany
In The Last Decade
Dan Iter
15 papers receiving 453 citations
Hit Papers
Peers
Comparison fields: 5 of 80
- Health Informatics 25
- Artificial Intelligence 294
- Information Systems 102
- Computer Vision and Pattern Recognition 58
- Computer Networks and Communications 60
Countries citing papers authored by Dan Iter
This map shows the geographic impact of Dan Iter'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 Dan Iter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Iter more than expected).
Fields of papers citing papers by Dan Iter
This network shows the impact of papers produced by Dan Iter. 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 Dan Iter. The network helps show where Dan Iter may publish in the future.
Co-authors
The 25 scholars most cited alongside Dan Iter, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | G-Eval: NLG Evaluation using Gpt-4 with Better Human Alignment Hit paper breakdown → | 2023 | 220 |
| 2 | 2018 | 56 | |
| 3 | From laptop to lambda: outsourcing everyday jobs to thousands of transient functional containers | 2019 | 55 |
| 4 | 2023 | 55 | |
| 5 | 2020 | 46 | |
| 6 | 2017 | 11 | |
| 7 | 2022 | 9 | |
| 8 | 2021 | 6 | |
| 9 | 2023 | 5 | |
| 10 | 2023 | 4 | |
| 11 | Socratic Learning: Correcting Misspecified Generative Models using Discriminative Models | 2016 | 3 |
| 12 | 2024 | 2 | |
| 13 | Outsourcing Everyday Jobs to Thousands of Cloud Functions with gg. | 2019 | 1 |
| 14 | 2023 | 1 | |
| 15 | 2023 | 1 | |
| 16 | 2020 | 1 |
About Dan Iter
Dan Iter is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Computer Networks and Communications and Social Psychology, having authored 16 papers that have together received 476 indexed citations. Recurring topics across this work include Topic Modeling (13 papers), Natural Language Processing Techniques (9 papers), Text Readability and Simplification (3 papers), Cloud Computing and Resource Management (2 papers), Multimodal Machine Learning Applications (2 papers), Machine Learning and Data Classification (2 papers), Business Process Modeling and Analysis (1 paper) and Semantic Web and Ontologies (1 paper). The work is most often cited by research in Health Informatics (25 citations), Artificial Intelligence (294 citations), Information Systems (102 citations), Computer Vision and Pattern Recognition (58 citations) and Computer Networks and Communications (60 citations). Dan Iter has collaborated with scholars based in United States, France and Germany. Frequent co-authors include Chenguang Zhu, Xu Yi‐chong, Yang Liu, Ruochen Xu, Shuohang Wang, Dan Jurafsky, Jong‐Woo Yoon, Kelvin Guu, Reid Pryzant and Jerry Li. Their work appears in journals such as Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), arXiv (Cornell University) and USENIX Annual Technical Conference.
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.