We are pleased to invite paper submissions to “The First Workshop on Learning with Natural Language Supervision” at ACL 2022.
Our workshop will offer a central meeting point for research on language-based supervision, enabling researchers within and beyond NLP to discuss how language processing models and algorithms can be brought to bear on problems beyond the textual realm (e.g. visual recognition, robotics, program synthesis, sequential decision making). Inspired by the relationship between language and human cognitive development, our workshop will emphasize broader use of language not just as an input modality but a fundamental source of information about the structure of tasks and problem domains. We are sourcing four-page submissions (due Feb 15 if submitted via ARR, and Feb 28 if submitted directly to the workshop) for archival and non-archival tracks. Relevant topics for submissions include (but are not limited to):
- Language-based task specifications (e.g. for classification or interactive decision-making).
- Language-guided search heuristics (e.g. for planning or theorem proving).
- Learning from user feedback in conversational agents.
- Generating and learning from natural language explanations and rationales.
- Understanding and improving prompt design (in NLP and beyond).
- Language guidance for improving safety and robustness.
- Language-guided meta-learning.
- Computational models of interactions between language and other aspects of cognition (e.g., categorization and memory).
nl-supervision-workshop [at] googlegroups.com
https://sites.google.com/corp/princeton.edu/nl-supervision
- For papers submitted directly to the workshop:
- Submission site opens: January 15, 2022
- Submission deadline: Feb 28, 2022
- Reviews due: March 21, 2022
- For papers submitted via ACL rolling review:
- Submission deadline: February 15, 2022
- Reviews due: March 15
- Decisions announced: March 26, 2022
- Camera-ready papers due: April 20, 2022
- Day of workshop: May 26, 2022
- Submissions should be a maximum of four pages, plus any number of pages for references.
- Submissions should be fully anonymized for double-blind review.
- Submissions should use the ACL 2022 style file.
- Dual submission: for our non-archival track only, we accept submissions that are under review in other venues.