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Proceedings of the Conference on Empirical Methods in Natural Language Processing - EMNLP '08

·2008

Abstract

Welcome to the 2008 Conference on Empirical Methods in Natural Language Processing! The conference is organized under the auspices of SIGDAT, the ACL Special Interest Group for linguistic data and corpus-based approaches to natural language processing. It is co-located this year with AMTA 2008 and the International Workshop on Spoken Language Translation, in Honolulu, Hawaii. EMNLP received 385 submissions. We were able to accept 116 papers in total (an acceptance rate of 30%). 81 of the papers (21%) were accepted for oral presentation, and 35 (9%) for poster presentation. Two poster papers were subsequently withdrawn after acceptance. The papers were selected by a program committee of 15 area chairs, from Asia, Europe, and North America, assisted by a panel of 339 reviewers. This year EMNLP introduced an author response period. Authors were able to read and respond to the reviews of their paper before the program committee made a final decision. They were asked to correct factual errors in the reviews and answer questions raised in the reviewer comments. The intention was to help produce more accurate reviews. In some cases, reviewers changed their scores in view of the authors' response and the area chairs read all responses carefully prior to making recommendations for acceptance.

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Metadata

Published
2008
OpenAlex
W2930957955
Cited by
2,157
References
0
Type
paratext
Language
en
Open access
closed

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CoChat. (2026). Citation check: Proceedings of the Conference on Empirical Methods in Natural Language Processing - EMNLP '08. https://app.cochat.ai/papers/10.3115/1613715
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Proceedings of the Conference on Empirical Methods in Natural Language Processing - EMNLP '08. (2008). https://doi.org/10.3115/1613715

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.