Day: May 7 2021
Location: Virtual (ICLR platform)
- All talks will be streamed during the workshop on the conference webpage.
- All talks have a live Q&A session and we have a panel discussion in the end. You can ask questions via Rocket.Chat or join the Zoom session directly. The links are also on the conference webpage.
- The poster sessions and the post workshop hang-out are held on Gather.Town. Links below in the schedule.
- Tweet with us @wea_su #WeaSuL2021
- For those new to the topic, we collected a list of papers to get an overview over the field.
| PDT | EDT | CEST | BJT | Event |
|---|---|---|---|---|
| 07:00 | 10:00 | 16:00 | 22:00 | Introduction and Opening Remarks |
| 07:10 | 10:10 | 16:10 | 22:10 | Invited Talk Dan Roth (University of Pennsylvania) |
| 08:25 | 11:25 | 17:25 | 23:25 | Invited Talk Marine Carpuat (University of Maryland) |
| 09:25 | 12:25 | 18:25 | 00:25 | Contributed Talk Dependency Structure Misspecification in Multi-Source Weak Supervision Models |
| 09:50 | 12:50 | 18:50 | 00:50 | Poster Spotlights 1 |
| 10:15 | 13:15 | 19:15 | 01:15 | Virtual Poster Session 1 |
| Link to Gather.Town Poster Room 1 | ||||
| AutoTriggER: Named Entity Recognition with Auxiliary Trigger Extraction | ||||
| Handling Long-Tail Queries with Slice-Aware Conversational Systems | ||||
| Tabular Data Modeling via Contextual Embeddings | ||||
| TADPOLE: Task ADapted Pre-training via anOmaLy dEtection | ||||
| Active WeaSuL: Improving Weak Supervision with Active Learning | ||||
| Transformer Language Models as Universal Computation Engines | ||||
| 11:15 | 14:15 | 20:15 | 02:15 | Welcome Back |
| 11:20 | 14:20 | 20:20 | 02:20 | Invited Talk Heng Ji (University of Illinois) |
| 12:05 | 15:05 | 21:05 | 03:05 | Contributed Talk Weakly Supervised Multi-task Learning for Concept-based Explainability |
| 12:30 | 15:30 | 21:30 | 03:30 | Contributed Talk Better adaptation to distribution shifts with Robust Pseudo-Labeling |
| 12:55 | 15:55 | 21:55 | 03:55 | Poster Spotlights 2 |
| 13:20 | 16:20 | 22:20 | 04:20 | Virtual Poster Session 2 |
| Link to Gather.Town Poster Room 2 | ||||
| Using system context information to complement weakly labeled data | ||||
| CIGMO: Learning categorical invariant deep generative models from grouped data | ||||
| Pre-Training by Completing Points Cloud | ||||
| Weakly-Supervised Group Disentanglement using Total Correlation | ||||
| Is Disentanglement all you need? Comparing Concept-based & Disentanglement Approaches | ||||
| Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks | ||||
| Weakly Supervision Multi-Task Learning for Concept-Based Explainability | ||||
| 14:20 | 17:20 | 23:20 | 05:20 | Welcome Back |
| 14:25 | 17:25 | 23:25 | 05:25 | Invited Talk Lu Jiang (Google Research) |
| 15:25 | 18:25 | 00:25 | 06:25 | Invited Talk Paroma Varma (Snorkel AI) |
| 16:10 | 19:10 | 01:10 | 07:10 | Virtual Panel Discussion |
| 17:10 | 20:10 | 02:10 | 08:10 | Conclusion |
| 17:25 | 20:25 | 02:25 | 08:25 | Post Workshop Hangout |
| Link to Gather.Town Hangout |