Table Representation Learning workshop
NeurIPS 2022, Room 398, Friday 2 December, New Orleans, USA
About
We develop large models to “understand” images, videos and natural language that fuel many intelligent applications from text completion to self-driving cars. But tabular data has long been overlooked despite its dominant presence in data-intensive systems. By learning latent representations from (semi-)structured tabular data, pretrained table models have shown preliminary but impressive performance for semantic parsing, question answering, table understanding, and data preparation. Considering that such tasks share fundamental properties inherent to tables, representation learning for tabular data is an important direction to explore further. These works also surfaced many open challenges such as finding effective data encodings, pretraining objectives and downstream tasks.
The Table Representation Learning workshop is the first workshop in this emerging research area and has the following main goals: 1) motivating tabular data as a first-class modality for representation learning and further shaping this area, 2) show-casing impactful applications of pretrained table models and discussing future opportunities thereof, and 3) facilitating discussion and collaboration across the machine learning, natural language processing, and data management communities.
Important dates
- Submission open:
20 August 2022 - Submission deadline:
20 September 202226 September 2022 15:00 GMT - Notifications:
20 October 2022 - Talk pre-recording upload for submissions accepted as oral (SlidesLive):
10 November 2022 - Slides for submissions accepted as oral (OpenReview):
15 November 2022 - Poster pitch recording for submissions accepted as posters (optional; 2min .mp4; to be published on website; email to m.hulsebos@uva.nl):
15 November 2022 - Poster submission (neurips.cc):
15 November 2022 - Camera-ready paper (OpenReview):
15 November 2022 - Workshop: 2 December 2022
Feedback
Did you attend and/or contribute to the workshop or would you be interested in joining next year? We would love to get your feedback to improve the organization for future editions. Please fill in the below form (responses are anonymous!).
Further info
Sponsors
We are grateful to the sponsors for supporting this workshop:
