BEST TFG or TFM Prize

WINNING WORK

The 7th Edition of the Award for the Best Novel Research Line (TFG or TFM) has granted the award for the best novel research line in Natural Language Processing to the work “Identification of Sexism on TikTok: A Multimodal AI Approach with Text, Audio, and Video” by Iván Arcos Gabaldón from the Polytechnic University of Valencia.

CALL

The Spanish Society for Natural Language Processing (SEPLN) announces the 7th Edition of the Award for the best new research line in Natural Language Processing (NLP). The call aims to reward the best Undergraduate Thesis (TFG) or Master’s Thesis (TFM) developed during the current academic year by undergraduate or master’s students enrolled in any national university.

The purpose of this award is to raise the profile of research related to NLP among undergraduate or master’s students and to encourage the development of works that analyze, use, propose, or develop new methods, techniques, or applications related to language technology, including, but not limited to:

  • Mathematical and psycholinguistic language models.
  • Machine learning in NLP.
  • Computational lexicography and terminology.
  • Corpus linguistics.
  • Development of linguistic resources and tools.
  • Morphological and syntactic analysis.
  • Semantics, pragmatics, and discourse.
  • Lexical-semantic ambiguity resolution.
  • Monolingual and multilingual text generation.
  • Machine translation.
  • Multimodality.
  • Speech processing.
  • Dialogue systems/conversational assistants.
  • Multimedia information indexing and retrieval.
  • Monolingual and multilingual information retrieval and extraction.
  • Question-answering systems.
  • Evaluation of NLP systems.
  • Automatic content analysis.
  • Opinion analysis and argumentation mining.
  • Plagiarism detection.
  • Negation and speculation processing.
  • Text mining in social networks.
  • Automatic text summarization.
  • Text simplification.
  • Knowledge and common sense.
  • NLP in the biomedical field.
  • Generation of educational resources based on NLP.
  • NLP for low-resource languages.
  • Industrial applications of NLP.
  • Ethical aspects of NLP.
  • Interpretability and analysis of models for NLP.
  • Ontology development.

All Undergraduate Thesis Projects and Master’s Thesis Projects defended during the 2023-2024 academic year by students enrolled in undergraduate or master’s programs at any national university or who are in the process of defending them are eligible for these awards.

Interested students must submit proof that the work has been defended or is in the process of being defended during the 2023/24 academic year and a summary in article format describing the developed TFG or TFM. The proof and the article must be submitted via the following form.

The article should include:

  • Title of the TFG or TFM;
  • Motivation and justification of the proposed work;
  • Objectives and contributions of the work;
  • Relationship with the NLP area;
  • Methodology and experimentation;
  • Results and conclusions.

The submitted works must follow the following style:

  • Use PDF format.
  • Be written in Spanish or English.
  • Have a maximum length of 4 pages, plus an extra page for references if necessary.
  • The documents should not include a header, footer, or the author’s name (only one author per TFG or TFM).
  • Follow the SEPLN journal’s style guide using their LaTeX or Word templates.

The application period begins on June 10, 2024, and ends on June 24, 2024.

The award for the best TFG or TFM will consist of a certificate and support for attendance and, if necessary, accommodation to attend the Doctoral Symposium on September 26, 2024, within the framework of the annual SEPLN conference (http://sepln2024.sepln.org/), where the author of the winning work will give a brief presentation of 5-10 minutes to introduce it to the entire NLP research community. Additionally, the winning work will be disseminated through social media and the SEPLN conference website, along with the author’s name and the university where the work was developed.

A panel of experts in the NLP research area, consisting of members of the SEPLN advisory council, will be created to evaluate the submitted works.

The panel of experts will consider the following criteria to award the prize:

  • Originality and novelty of the TFG or TFM
  • Academic quality
  • Degree of difficulty of the topic addressed
  • Rigor in the methodology used for its preparation
  • Results and conclusions obtained

IMPORTANT DATES

  • Application period: June 10, 2024 – June 24, 2024
  • Review period: June 25, 2024 – July 9, 2024
  • Prize notification: July 12, 2024
  • Oral presentation of the work: September 26, 2024 (SEPLN 2024)

The notification of the winning work will be made via email to the person concerned and will also be announced through the SEPLN 2024 conference website.

For any questions or concerns, you can contact the following email addresses: alba.bonet@gcloud.ua.es, david.vilares@udc.es, mdmolina@ujaen.es and sjzafra@ujaen.es 

ORGANIZING COMMITTEE

  • Alba Bonet Jover. University of Alicante (Spain)
  • David Vilares Calvo. University of A Coruña (Spain)
  • M. Dolores Molina González. University of Jaén (Spain)
  • Salud María Jiménez Zafra. University of Jaén (Spain)