===Call for Industry Track Papers===
EMNLP Industry Track 2024 invites the submission of papers featuring substantial, original, and unpublished research on empirical methods for Natural Language Processing. The EMNLP 2024 Industry Track aims to highlight the mutual influence of language technology in academia and industry, which has significantly contributed to the proliferation of industrial applications. The track provides the opportunity for researchers, engineers, practitioners and users to meet and discuss the latest language technologies methods as deployed in a real-world setting and aims to be the premier forum for knowledge sharing across the boundary between academia and industry.
Contributions are invited across all spectrums of language technologies and systems, with a special emphasis on innovations and implementations that hold relevance to real-world applications. We encourage submissions from both non-profit and for-profit sectors, with the understanding that the end-users of these systems extend beyond the NLP community. Please note that if submissions involve proprietary data, there is no requirement to make this data available.
EMNLP Industry Track 2024 will be held as part of EMNLP 2024 in the Hyatt Regency Miami in Miami, Florida (USA).
===Paper Submission Information===
Submit via this Industry Track Papers submission link: https://openreview.net/group?id=EMNLP/2024/Industry_Track
===Important Dates===
Paper submission deadline: 18 July 2024
Notification: 1 October 2024
Camera-ready version of papers due: 15 October 2024
Main conference: 12 - 14 November 2024
Note: All deadlines are 11:59PM UTC-12:00 (“anywhere on Earth”).
Following the ACL and ARR policies, there is no anonymity period requirement.
===Submission Topics===
The EMNLP 2024 Industry Track provides the opportunity to highlight the key insights and new research challenges that arise from the development and deployment of real-world applications using language technologies. Relevant areas include:
System design, efficiency, maintainability and scalability of real-world applications, with topics in alphabetical order including, but not limited to:
- Benchmarks and methods for improving the latency and efficiency of systems
- Continuous maintenance and improvement of deployed systems
- Efficient methods for training and inference
- Enabling infrastructure for large-scale deployment
- Human-in-the-Loop approaches to application development
- Implementation at speed, scale or low-cost
- System combination
Novel applications and use cases, with topics in alphabetical order including, but not limited to:
- Best practices, lessons learned or a vision on deploying real-world applications
- Case studies, from design to deployment
- Description of an application or system
- Design of application-relevant datasets
- Development of methods under system constraints (model or data size)
- Novel NLP applications
Methods for deployed systems, with topics in alphabetical order including, but not limited to:
- Ethics, bias, fairness and harmlessness
- Interpretability
- Interactive systems
- Offline and online system evaluation methodologies
- Online learning
- Robustness
Visit https://2024.emnlp.org/calls/industry_track/ for more information.
For questions, please email: emnlp2024-industry-track [at] googlegroups.com