In the ever-evolving world of search engine optimization (SEO), staying updated with the latest trends is crucial to maintaining a competitive edge. One trend that has gained significant momentum in recent years is voice search.
With the rise of virtual assistants and smart devices, more users rely on voice commands to search for information, make inquiries, and perform various online tasks. As voice search continues to reshape the digital landscape, optimizing your website for this trend has become a must-have SEO strategy in 2023.
ChatGPT-4, powered by OpenAI, is the ultimate game-changer in conversational AI. It is advanced NLP and machine learning capabilities offer next-gen virtual assistant and chatbot solutions.
The paper discusses the capabilities of large pre-trained language models and their limitations in accessing and manipulating knowledge. The authors introduce retrieval-augmented generation (RAG) models that combine pre-trained parametric and non-parametric memory for language generation. The study explores the effectiveness of RAG models in various NLP tasks and compares them with other architectures.
odyCy is a state of the art NLP library for Ancient Greek, capable of part-of-speech tagging, morphological analysis, dependency parsing, lemmatization and more.
The string2string library is an open-source tool that offers a comprehensive suite of efficient algorithms for a broad range of string-to-string problems. It includes both traditional algorithmic solutions and recent advanced neural approaches to address various problems in pairwise string alignment, distance measurement, lexical and semantic search, and similarity analysis. Additionally, the library provides several helpful visualization tools and metrics to facilitate the interpretation and analysis of these methods.
H. Chang, Z. Yao, A. Gon, H. Yu, and A. McCallum. Findings of the Association for Computational Linguistics: ACL 2023, page 12707--12730. Toronto, Canada, Association for Computational Linguistics, (July 2023)
H. Chang, and A. McCallum. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), page 8048--8073. Dublin, Ireland, Association for Computational Linguistics, (May 2022)
T. Ziegenbein, S. Syed, F. Lange, M. Potthast, and H. Wachsmuth. Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, page 4344--4363. Association for Computational Linguistics (ACL), (July 2023)Funding Information: This project has been partially funded by the German Research Foundation (DFG) within the project OASiS, project number 455913891, as part of the Priority Program “Robust Argumentation Machines (RATIO)” (SPP-1999). We would like to thank the participants of our study and the anonymous reviewers for the feedback and their time.; 61st Annual Meeting of the Association for Computational Linguistics, ACL 2023 ; Conference date: 09-07-2023 Through 14-07-2023.
S. Syed, T. Ziegenbein, P. Heinisch, H. Wachsmuth, and M. Potthast. Proceedings of the 24th Annual Meeting of the Special Interest Group on Discourse and Dialogue, page 114--129. Prague, Czechia, Association for Computational Linguistics, (September 2023)
M. Stahl, and H. Wachsmuth. Proceedings of the 16th International Natural Language Generation Conference: Generation Challenges, page 31--36. (September 2023)
G. Skitalinskaya, and H. Wachsmuth. Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), page 15799–15816. Association for Computational Linguistics (ACL), (July 2023)Funding Information: We thank Andreas Breiter for his valuable feedback on early drafts, and the anonymous reviewers for their helpful comments. This work was partially funded by the Deutsche Forschungsgemeinschaft(DFG, German Research Foundation) under project number 374666841, SFB 1342.; 61st Annual Meeting of the Association for Computational Linguistics, ACL 2023 ; Conference date: 09-07-2023 Through 14-07-2023.
G. Skitalinskaya, M. Spliethöver, and H. Wachsmuth. Proceedings of the 16th International Natural Language Generation Conference, page 134--152. (2023)DBLP's bibliographic metadata records provided through http://dblp.org/search/publ/api are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions..
M. Sengupta. Findings of the Association for Computational Linguistics: EMNLP 2023, page 4636–4659. Association for Computational Linguistics (ACL), (December 2023)