Call for Papers

Underserved communities often lack adequate access to advanced natural language processing (NLP) technologies due to limited linguistic data, insufficient computational resources, or inadequate AI governance frameworks. This gap hinders equitable access to NLP advancements, exacerbating the digital divide. Our workshop aims to address this by fostering a multidisciplinary dialogue around the development of language models (LMs) that prioritize cultural sensitivity, resource efficiency, and sustainable AI practices. We invites researchers, practitioners, and policymakers to address challenges and propose innovative solutions for building and deploying language models for underserved languages and communities.

Topics of Interest

We invite submissions of full papers, ongoing work, position papers, and survey papers on topics including, but not limited to:

Measuring and Governing AI
Developing reliable evaluation methods for LMs under constraints in data, compute, and expertise. How can psychometrics, auditing frameworks, or validity theory guide responsible measurement and governance?
Benchmarking and Fairness
Building inclusive benchmarks and evaluation pipelines that reduce bias, improve cultural and linguistic representation, and ensure fair performance across underserved communities.
Pluralistic Alignment
Designing approaches for aligning LMs with diverse values, cultural norms, and epistemologies, including participatory and community-driven methods.
Open and Inclusive Infrastructure
Creating open datasets, benchmarks, models, and participatory platforms that support sustainable and equitable NLP research and deployment.

Submission Guidelines

We welcome long papers (8 pages) and short papers (4 pages), excluding references. Submissions must follow the AAAI 2026 style guidelines.