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NIST will hold a virtual workshop on Technical Language Processing on 24-25 September 2024. Online registration is $33.00 USD and is available via the workshop webpage. The two-day virtual event brings together industry, government, and academic stakeholders through the NIST Technical Language Processing Community of Interest (TLP COI), and it offers a valuable platform to connect, share insights, and explore the evolving landscape of TLP.
The workshop will include presentations and roundtable discussions to share experiences and results of TLP in various fields and explore the latest tools and methodologies in TLP applications with real-world examples from industry, government, and academic research. Event topics include Current Tools and Best Practices; Emerging Applications and Use Cases; and Methods and Philosophies for Quantifying Impacts.
Featured speakers include: Faez Ahmaed (Massachusetts Institute of Technology); Fazel Ansari (Institute of Management Science); Peter Chung (University of Maryland); and Rachael Sexton (NIST). Panelists include: Jamie Coble (University of Tennessee Knoxville); Joshua Gen (Logistics Management Institute); Nate Hertlein (Air Force Research Laboratory); Melinda Hodkiewicz (University of Western Australia); Manjish Naik (John Bean Technologies Corporation); and Roberto Sala (Università degli studi di Bergamo).
In an era where industry, artificial intelligence, and human-centered intelligent automation converge, staying ahead in communications and language processing is crucial. This year’s TLP COI meeting and workshop will emphasize:
- Risk Awareness: Understanding and managing risks in TLP development and applications.
- Accessibility: Making TLP tools and resources more accessible.
- Longevity: Ensuring the sustainable development of TLP technologies.
Additional Key Topics include:
- Introductory TLP: Exploring the fundamentals and differentiating TLP from Natural Language Processing.
- Current TLP Landscape: State of the practice and best practices.
- Risk Awareness: Integrating risk management in TLP development.
- Data Sharing and Resources: Privacy-aware data sharing and available resources.
- Needs, Gaps, and Applications: Identifying imminent needs and applications in various sectors.
- Metrics and Measurement: Quantifying and qualifying the impact of TLP.
- Exploring LLMs: Industrial and technical applications of large language models (LLMs).
- Humans as Observers: Enhancing the interaction between operators and monitoring systems.
- Standards Mining and Support: Accelerating model creation and validation from documentation.
For any inquiries about the workshop, please reach out to Dr. M. Sharp at michael.sharp [at] nist.gov (michael[dot]sharp[at]nist[dot]gov).