Overview

The workshop welcomes submissions describing original research findings as well as relevant studies that are published recently in high-quality venues.

  • Previously unpublished manuscripts should be submitted as a PDF file in no longer than 4 pages (plus unlimited pages for references and appendices), according to the new ACM format published in ACM guidelines, selecting the generic “sigconf” sample (see the guideline of WSDM 2024). Appendices should be included in the same file with the main manuscript.
  • Manuscripts that have been published can be submitted in its original format and will be lightly reviewed.
  • All submissions should be made through EasyChair.

Important Dates

All deadlines are in Anywhere on Earth (AoE) time zone.

  • Submission deadline: January 15, 2024
  • Acceptance notification: February 1, 2024
  • Camera-ready version due: February 15, 2024
  • Workshop: March 8, 2024

List of Topics

Topics of the workshop will include but not limited to:

  • Novel models and algorithms for adapting large language models to personal contexts.
  • New developments in aligning large language models with the preferences and objectives of individuals, sub-populations, or the society at large.
  • Theoretical and empirical results of applying reinforcement learning from the feedback of individuals and groups of human users to LLMs.
  • Evaluation of personalization and societal alignment of LLMs, including datasets, metrics, and benchmarks.
  • Personalizing and aligning LLMs under resource constraints. For example, deploying personalized LLMs on mobile devices or aligning the output of frozen LLMs through APIs.
  • Applications of personalization and societal-alignment of LLMs, including but not limited to search engines, recommender systems, email/writing assistants, social networking, entertainment, education, healthcare, scientific discovery, and future of work.
  • Ethics of personalizing LLMs, including but not limited to privacy, fairness, bias, transparency, diversity, and other potential impacts of LLMs to individuals, groups, and the society.
  • Equitable applications of LLM to diverse user groups.

Publication

This workshop is non-archival. Relevant findings that have been published recently are welcome to be submitted to the workshop. For already published studies, the paper can be submitted in the original format. These submissions will be very lightly reviewed for their relevance to this workshop.