AACL-IJCNLP 2026 · The First Workshop on Pluralistic Value Alignment of LLMs
PlurVA-LLM
Pluralistic Value Alignment of Large Language Models
Multiple Values. Multiple Languages. Unified Alignment.
Welcome to the First Workshop on Pluralistic Value Alignment of LLMs (PlurVA-LLM) !
Large language models (LLMs) have achieved remarkable progress and are widely used in applications such as content generation, information retrieval, and decision support. As these systems are deployed globally, concerns have emerged about the values and norms implicitly embedded in them. Beyond technical performance, LLMs may encode cultural assumptions and biases that influence user decisions, shape societal perceptions, and fail to reflect the diversity of human values across regions and communities. Addressing this challenge requires pluralistic alignment, which aims to develop language models that can recognize, reason about, and adapt to diverse value systems across different cultural and social contexts.
The PlurVA-LLM workshop aims to achieve two primary goals:
First, it aims to provide a dedicated venue for advancing research on pluralistic value alignment in large language models. We invite submissions from researchers in NLP, machine learning, AI safety, social science, philosophy, and related fields. Topics of interest include the theoretical foundations and formalizations of pluralistic value alignment, methods for aligning LLMs with diverse value systems, benchmarks and evaluation protocols, human AI collaboration for constructing value sensitive datasets, interpretability and analysis of value alignment, applications in downstream systems and real world deployment, as well as multilingual, multicultural, low resource, and multimodal perspectives. The workshop will feature invited keynote talks, a panel discussion, and oral and poster sessions where accepted papers will be presented.
Second, it will host a shared task on pluralistic value alignment across China, Indonesia, and Sri Lanka, evaluating whether large language models can produce locally grounded value judgments across different cultural contexts. Participants are asked to build a single unified system that, given a scenario and a target country, generates the response most consistent with that country’s annotated human value preferences. The benchmark integrates Chinese daily life dilemmas, Indonesian dilemmas grounded in Pancasila values, and Sri Lankan value judgment tasks in English and Sinhala. The task examines whether models can adapt across different value frameworks rather than defaulting to a single generic norm, with evaluation emphasizing balanced performance across all countries.
News
| Date | Announcement |
|---|---|
| 2026-07-01 | Shared task test set released and leaderboard open for submissions The test set for the PlurVA-LLM Shared Task has been released, and the leaderboard is now open for submissions on Codabench. Participants can submit their predictions through the leaderboard page. |
| 2026-06-19 | Student co-organizers joined the workshop team We are pleased to welcome our student co-organizers to the PlurVA-LLM organizing team. They will support workshop coordination, shared-task communication, website maintenance, publicity and participant engagement. |
| 2026-06-10 | Submission portal and CFP links updated The CFP page has been updated with the correct submission links and detailed submission routes. Authors can now access the submission portal through the CFP page. |
| 2026-06-07 | Second Call for Papers released We have released the second Call for Papers for PlurVA-LLM @ AACL 2026. The updated CFP includes submission tracks for archival papers, non-archival extended abstracts, already accepted/published work, and ARR-reviewed papers. |
| 2026-06-07 | Shared task page updated We have updated the PlurVA-LLM Shared Task page with detailed information on task settings, tracks, benchmark datasets, evaluation protocol, submission format, leaderboard links and timeline. |
| 2026-05-25 | Development set released for registered shared-task teams The development set for the PlurVA-LLM Shared Task has been released to registered teams. Participants may use it for system development and internal validation according to the rules of their selected track. |
| 2026-04-24 | 🚨Call for Papers for the PlurVA-LLM Workshop @AACL-IJCNLP2026 is now open. Please visit the CFP page on this website for submission details. |
Important Dates
Key deadlines for the PlurVA-LLM Shared Task and Workshop. All deadlines are 11:59 PM Anywhere on Earth (AoE).
Shared Task
Leaderboard Submission Deadline
Final submission deadline for the shared task leaderboard. Participants must submit their predictions on Codabench before this date. Shared task leaderboard session is extended into 27 July 2026.
Finalization Form Deadline
The team must submit the documentation and code to the organizer before 30th July through "Finalization Form" (Track-1: Resource Constrained Track (https://forms.gle/Hy4W5xMY7DqCVSef9) and Track-2: Open Track (https://forms.gle/fqfubLA7XrtEgeND6)). If the team didn't submit on time, the team score will be excluded in the final leaderboard. Documentation must brief the detail regarding data used to improve the model, prompting details, fine-tuning details (learning rate, epoch, etc.).
Final Ranking & Announcement
The organizer will conduct a final review of participant qualifications and restrictions and do the leaderboard finalization at the beginning of August.
Workshop
Archival and Non-archival Papers Submission Deadline
Submission deadline for archival and non-archival papers to the PlurVA-LLM 2026 workshop. Shared task participants are also welcomed to submit a system description paper; the title should start with prefix: "PlurVA-LLM-2026 Shared Task Track-N: ", where N represents Track-1 or Track-2.
Archival and Non-archival Papers Acceptance Notification
Acceptance notification for archival and non-archival paper submissions.
ARR Track Commitment Deadline
Commitment deadline for papers already peer-reviewed through ACL Rolling Review (ARR).
ARR Track Acceptance Notification
Acceptance notification for the ARR track.