Dan Iter

1.3k total citations · 1 hit paper
16 papers, 476 citations indexed

About

Dan Iter is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Dan Iter has authored 16 papers receiving a total of 476 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 4 papers in Information Systems and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Dan Iter's work include Topic Modeling (13 papers), Natural Language Processing Techniques (9 papers) and Text Readability and Simplification (3 papers). Dan Iter is often cited by papers focused on Topic Modeling (13 papers), Natural Language Processing Techniques (9 papers) and Text Readability and Simplification (3 papers). Dan Iter collaborates with scholars based in United States, France and Germany. Dan Iter's co-authors include Chenguang Zhu, Yang Liu, Xu Yi‐chong, Shuohang Wang, Ruochen Xu, Dan Jurafsky, Jong‐Woo Yoon, Kelvin Guu, Reid Pryzant and Jerry Li and has published in prestigious journals such as USENIX Annual Technical Conference, arXiv (Cornell University) and Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).

In The Last Decade

Dan Iter

15 papers receiving 453 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.

G-Eval: NLG Evaluation using Gpt-4 with Better Human Alignment

2023 220 citations Yang Liu, Dan Iter et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Dan Iter United States	7	294	102	60	58	32	16	476
Kyo-Joong Oh South Korea	9	224 0.8×	70 0.7×	15 0.3×	69 1.2×	12 0.4×	22	386
Yngve Lamo Norway	13	221 0.8×	157 1.5×	51 0.8×	23 0.4×	11 0.3×	57	447
Ilias Tachmazidis United Kingdom	9	111 0.4×	38 0.4×	56 0.9×	15 0.3×	60 1.9×	27	292
Muhammed J. A. Patwary Bangladesh	13	158 0.5×	37 0.4×	17 0.3×	65 1.1×	38 1.2×	43	359
Hrafn Loftsson Iceland	11	497 1.7×	58 0.6×	11 0.2×	35 0.6×	19 0.6×	39	641
Ilia Shumailov United Kingdom	8	188 0.6×	68 0.7×	13 0.2×	38 0.7×	13 0.4×	19	396
Evelyne Viegas United States	10	293 1.0×	90 0.9×	18 0.3×	44 0.8×	18 0.6×	32	450
Izabela Stefaniak Poland	4	136 0.5×	27 0.3×	11 0.2×	34 0.6×	15 0.5×	12	223
Lung‐Hao Lee Taiwan	15	508 1.7×	99 1.0×	15 0.3×	83 1.4×	48 1.5×	55	637
K. M. Azharul Hasan Bangladesh	13	401 1.4×	115 1.1×	78 1.3×	70 1.2×	11 0.3×	109	619

Countries citing papers authored by Dan Iter

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Dan Iter

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

16 of 16 papers shown

1.

Sun, Simeng, Yang Liu, Shuohang Wang, et al.. (2024). PEARL: Prompting Large Language Models to Plan and Execute Actions Over Long Documents. 469–486. 2 indexed citations

2.

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

3.

Zhang, Zhihan, Wenhao Yu, Xu Yi‐chong, et al.. (2023). Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models. 5 indexed citations

4.

Yi‐chong, Xu, Ruochen Xu, Dan Iter, et al.. (2023). InheritSumm: A General, Versatile and Compact Summarizer by Distilling from GPT. 13879–13892. 1 indexed citations

5.

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

6.

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

7.

Liu, Yang, Dan Iter, Xu Yi‐chong, et al.. (2023). G-Eval: NLG Evaluation using Gpt-4 with Better Human Alignment. 2511–2522. 220 indexed citations breakdown →

8.

Grangier, David & Dan Iter. (2022). The Trade-offs of Domain Adaptation for Neural Language Models. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 3802–3813. 9 indexed citations

9.

Iter, Dan, et al.. (2021). Focus on what matters: Applying Discourse Coherence Theory to Cross Document Coreference. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. 1406–1417. 6 indexed citations

10.

Iter, Dan, et al.. (2020). Pretraining with Contrastive Sentence Objectives Improves Discourse Performance of Language Models. 46 indexed citations

11.

Iter, Dan, et al.. (2020). Entity Attribute Relation Extraction with Attribute-Aware Embeddings. 50–55. 1 indexed citations

12.

Fouladi, Sadjad, Francisco Romero, Dan Iter, et al.. (2019). From laptop to lambda: outsourcing everyday jobs to thousands of transient functional containers. USENIX Annual Technical Conference. 475–488. 55 indexed citations

13.

Fouladi, Sadjad, Francisco Romero, Dan Iter, et al.. (2019). Outsourcing Everyday Jobs to Thousands of Cloud Functions with gg.. 44. 1 indexed citations

14.

Iter, Dan, Jong‐Woo Yoon, & Dan Jurafsky. (2018). Automatic Detection of Incoherent Speech for Diagnosing Schizophrenia. 136–146. 56 indexed citations

15.

Varma, Paroma, Dan Iter, Christopher De, & Christopher Ré. (2017). Flipper. 1–5. 11 indexed citations

16.

Varma, Paroma, Bryan He, Dan Iter, et al.. (2016). Socratic Learning: Correcting Misspecified Generative Models using Discriminative Models. arXiv (Cornell University). 3 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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