5th Workshop on Data Science with Human-in-the-loop (DaSH)
co-located with NAACL 2024, Mexico City
June 21-22, 2024
The 5th Workshop on Data Science with Human-in-the-loop (DaSH) will have an emphasis on language advances and will be co-located with the NAACL 2024 conference. The aim of this workshop is to stimulate research on cooperation between humans and computers within the broad area of natural language processing, including but not limited to information extraction, information retrieval and text mining, machine translation, dialog systems, question answering, language generation, summarization, model interpretability, evaluation, fairness, and ethics. We invite researchers and practitioners interested in understanding how to optimize human-computer cooperation and how to minimize human effort along an NLP pipeline in a wide range of tasks and applications.
Submissions:
We invite submissions describing innovations and implementations that focus on understanding how to optimize human-computer cooperation and minimize human effort along the NLP pipeline in a wide range of NLP tasks and real-world applications.
Topics of interest:
Topics of interest to this workshop include, but are not limited to:
- Supervised, self-supervised, transfer, and unsupervised learning with human-in-the-loop
- Human intervention and consequences on model bias, overfitting, and fairness
- Human and computer cooperation in data cleaning, preparation, representation for NLP tasks
- Optimizing human effort in data labeling
- Crowdsourcing in NLP
- Human-in-the-loop during model evaluation and model improvement
- Multi-modal human-in-the-loop issues in NLP in conjunction with data from other modalities such as social media, knowledge graphs, speech, image, video
- Enabling non-experts to build advanced NLP models
- Formal and higher abstractions for human-machine interaction in NLP tasks
- User interfaces for data preprocessing, labeling, and NLP model building, evaluation, and interpretation
- Human-in-the-loop issues in implementing, using, evaluating, and deploying NLP models in specific applications (e.g., medical, scientific, legal, business, digital humanities, creative).
Additional Information:
Authors are invited to submit either of the following:
- Original, unpublished research papers that are not being considered for publication in any other forum. Research papers are limited to six pages in length, excluding references.
- Short papers of late-breaking work and work in progress. Abstracts are limited to two pages.
Authors of both types of papers will need to present these papers at the DaSH workshop.
Submissions to the workshop must be in PDF and should follow the NAACL paper formatting. All submissions should be anonymized to facilitate double blind reviewing.
One Best Paper Award and One Best Student Paper Award will be selected.
Workshop co-chairs
Eduard Dragut, Temple University
Yunyao Li, Adobe
Lucian Popa, IBM Research - Almaden
Shashank Srivastava, University of North Carolina at Chapel Hill
Slobodan Vucetic, Temple University