Overview
The NeurIPS 2019 Workshop on ‘Context and Compositionality in Biological and Artificial Neural Systems’ invites researchers to submit papers exploring the integration of semantic information across narratives. This workshop aims to bridge the gap between advancements in natural language processing (NLP) and insights from neuroscience, highlighting the importance of context in language understanding.
Background & Relevance
Understanding how both biological and artificial systems process language is crucial in the fields of machine learning and cognitive science. Recent developments in NLP have shifted from traditional methods to more sophisticated architectures like RNNs and Transformers, which effectively incorporate contextual information. This workshop seeks to address the complexities of representation and interpretability in these models, as well as their biological counterparts, thus contributing to a deeper understanding of language processing.
Key Details
- Workshop Dates: December 13-14, 2019
- Location: Vancouver Convention Center, Vancouver, Canada
- Submission Deadline: September 9, 2019, 22:00 PM UTC
- Decision Notification: September 29, 2019, 22:00 PM UTC
- Submission Link: CMT Submission
- Start of Submission Window: August 7, 2019
Eligibility & Participation
The workshop welcomes contributions from researchers in machine learning, NLP, and neuroscience. It is particularly aimed at those investigating the interplay between contextual and compositional aspects of language processing.
Submission or Application Guidelines
- All submissions must be in PDF format and adhere to the NeurIPS 2019 LaTeX style file.
- Submissions are limited to four pages, including figures and tables; references can be on additional pages.
- Papers must be anonymous to ensure a double-blind review process.
- Accepted papers will be presented in a poster session, with spotlight presentations for outstanding submissions.
- Published papers within the workshop’s scope are also welcome, with a light review process.
Additional Context / Real-World Relevance
The exploration of context and compositionality is essential for advancing both artificial intelligence and our understanding of human cognition. By examining how these elements interact in neural systems, researchers can develop more effective AI models that mimic human-like language understanding, ultimately benefiting various applications in technology and communication.
Conclusion
Researchers are encouraged to participate in this workshop to contribute to the ongoing dialogue about context and compositionality in neural systems. This is an excellent opportunity to share insights, collaborate, and advance the field of AI and cognitive science.
Category: CFP & Deadlines
Tags: neurips, nlp, machine learning, neuroscience, contextual processing, compositionality, deep learning, temporal processing
