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EMNLP 2021 : Conference on Empirical Methods in Natural Language Processing (EMNLP)

EMNLP 2021 : Conference on Empirical Methods in Natural Language Processing (EMNLP)

Punta Cana , Dominican Republic

Submission Deadline: Monday 10 May 2021

Conference Dates: Nov 07, 2021 - Nov 07, 2021

Research
Impact Score 23.10

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Ranking & Metrics Impact Score is a novel metric devised to rank conferences based on the number of contributing the best scientists in addition to the h-index estimated from the scientific papers published by the best scientists. See more details on our methodology page.

Research Impact Score: 23.10
Contributing Best Scientists: 498
H5-index:
Papers published by Best Scientists 1118
Research Ranking (Computer Science) 9

Conference Call for Papers

EMNLP 2021 has the goal of a broad technical program. Relevant topics for the conference include, but are not limited to, the following areas (in alphabetical order):

Computational Social Science and Social Media
Dialogue and Interactive Systems
Discourse and Pragmatics
Ethics and NLP
Generation
Green NLP
Information Extraction
Information Retrieval and Text Mining
Interpretability and Analysis of Models for NLP
Linguistic Theories, Cognitive Modeling and Psycholinguistics
Machine Learning for NLP
Machine Translation and Multilinguality
NLP Applications
Phonology, Morphology and Word Segmentation
Question Answering
Resources and Evaluation
Semantics: Lexical, Sentence level, Textual Inference and Other areas
Sentiment Analysis, Stylistic Analysis, and Argument Mining
Speech, Vision, Robotics, Multimodal Grounding
Summarization
Syntax: Tagging, Chunking and Parsing

Overview

Top Research Topics at Empirical Methods in Natural Language Processing?

  • Artificial intelligence (73.92%)
  • Natural language processing (54.35%)
  • Task (project management) (19.33%)

The scientific interests tackled in the conference are Artificial intelligence, Natural language processing, Task (project management), Machine learning and Machine translation. Most of the Artificial intelligence studies addressed also intersect with Context (language use). The work on Natural language processing tackled in it brings together disciplines like Domain (software engineering) and Speech recognition.

The work on Task (project management) addressed in the event expands to the thematically related Information retrieval. Machine learning research presented in the conference encompasses a variety of subjects, including Training set and Inference. Empirical Methods in Natural Language Processing facilitates discussions on Machine translation that incorporate concepts from other fields like Translation (geometry) and Rule-based machine translation.

The majority of Parsing studies presented zero in on Dependency grammar.

What are the most cited papers published at the conference?

  • Glove: Global Vectors for Word Representation (19607 citations)
  • Learning Phrase Representations using RNN Encoder--Decoder for Statistical Machine Translation (9549 citations)
  • Convolutional Neural Networks for Sentence Classification (6459 citations)

Research areas of the most cited articles at Empirical Methods in Natural Language Processing:

The published papers focus largely on the fields of Artificial intelligence, Natural language processing, Machine learning, Task (project management) and Sentence. Issues in Artificial intelligence were discussed in the conference papers, taking into consideration concepts from other disciplines like Speech recognition and Pattern recognition. The published articles focus on Natural language processing but the discussions also offer insight into other areas such as Context (language use) and Information retrieval.

What topics the last edition of the conference is best known for?

  • Artificial intelligence
  • Law
  • Programming language

The previous edition focused in particular on these issues:

The conference facilitates discussions on Artificial intelligence, Natural language processing, Language model, Embedding and Code (cryptography). Empirical Methods in Natural Language Processing connects the study in Artificial intelligence with the closely related area of Machine learning. Empirical Methods in Natural Language Processing explores topics in Natural language processing which can be helpful for research in disciplines like Matching (statistics), Salient and Decoding methods.

The presented research on Language model deals specifically with Representation (mathematics) but it also addresses topics in Unsupervised learning. The event focuses on Embedding but also tackles concerns of closely connected disciplines like

  • Autoencoder together with Range (mathematics), Sequence and Question answering,
  • Simple (abstract algebra), which have a strong connection to Effective method, Matrix decomposition, Identity (object-oriented programming) and Orthographic projection,
  • Encoder that intertwine with fields like Zero (linguistics) and Translation (geometry).. Empirical Methods in Natural Language Processing deals with Code (cryptography) in conjunction with Theoretical computer science and similar fields in Abstract syntax and Source code.

The most cited articles from the last conference are:

  • Finetuning Pretrained Transformers into RNNs (3 citations)
  • An Exploratory Study on Long Dialogue Summarization: What Works and What’s Next (2 citations)
  • Sentence-Permuted Paragraph Generation (1 citations)

Papers citation over time

A key indicator for each conference is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

Research.com

The top authors publishing at Empirical Methods in Natural Language Processing (based on the number of publications) are:

  • Noah A. Smith (61 papers) published 1 paper at the last edition, 11 less than at the previous edition,
  • Dan Roth (52 papers) absent at the last edition,
  • Christopher D. Manning (50 papers) absent at the last edition,
  • Mirella Lapata (49 papers) absent at the last edition,
  • Eduard Hovy (44 papers) absent at the last edition.

The overall trend for top authors publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top authors.

Research.com

Only papers with recognized affiliations are considered

The top affiliations publishing at Empirical Methods in Natural Language Processing (based on the number of publications) are:

  • Microsoft (360 papers) published 20 papers at the last edition, 72 less than at the previous edition,
  • Carnegie Mellon University (341 papers) absent at the last edition,
  • Google (267 papers) published 4 papers at the last edition, 86 less than at the previous edition,
  • University of Washington (204 papers) published 2 papers at the last edition, 49 less than at the previous edition,
  • IBM (201 papers) absent at the last edition.

The overall trend for top affiliations publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top affiliations.

Research.com

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions at the conference edition to all articles published within that conference. The best research institutions were selected based on the largest number of articles published during all editions of the conference.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

Research.com

During the most recent 2021 edition, 6.06% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 83.87% were posted by at least one author from the top 10 institutions publishing at the conference. Another 6.45% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 0.00% of all publications and 9.68% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of conferences they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same conference from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the conference in relation to all participants in a given year.

Research.com

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

Research.com

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing at a conference. The index includes the authors publishing at the last edition of a conference, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

Research.com

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Research.com

Previous Editions

EMNLP 2021 : Conference on Empirical Methods in Natural Language Processing (EMNLP)

Nov 07, 2021 - Nov 07, 2021

Punta Cana , Dominican Republic, Dominican Republic

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