Collocated with ACM SIGIR 2024, the second workshop of LLMs for Individuals, Groups, and Society (LLM-IGS) aims to create a collaborative and interdisciplinary platform that brings together creators, researchers, and practitioners of large language models. By fostering an open and forward-looking environment, the workshop seeks to facilitate discussions on the current landscape of personalizing LLMs, adapting LLMs to individual and group contexts, and aligning LLMs with the value and objectives of the society at large. It provides an opportunity for participants to share insights, exchange ideas, and explore innovative approaches in the field. The ultimate goal is to drive progress and shape the future of large language models for individuals, groups, and the society through collective expertise and collaboration.

Submission Guidelines

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• Previously unpublished manuscripts should be submitted as a PDF file in no longer than 4 pages (plus unlimited pages for references and appendices), according to the new ACM format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 SIGIR 2024). Appendices should be included in the same file with the main manuscript. 
• Manuscripts that have been published (including publically available preprints) can be submitted in its original format and will be lightly reviewed. 
• All submissions should be made through https://easychair.org/conferences/?conf=llmigs2. 

Important Dates

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

• Submission deadline: May 20, 2024
• Acceptance notification: June 7, 2024
• Camera-ready version due: June 21, 2024
• Workshop: July 18, 2024

Publications

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 lightly reviewed for their relevance to this workshop.

List of Topics

• 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.

Committees

Organizing committee

• Michael Bendersky (Google Research)
• Cheng Li (Google Research)
• Qiaozhu Mei (University of Michigan)
• Vanessa Murdock (Amazon Inc.)
• Jie Tang (Tsinghua University)
• Hongning Wang (University of Virginia)
• Hamed Zamani (University of Massachusetts Amherst)
• Mingyang Zhang (Google Research)
• Xingjian Zhang (University of Michigan)

Venue

The workshop will be held at the ACM SIGIR conference in Washington D.C., USA on July 18, 2024.

Contact

All questions about submissions should be emailed to llmigs2 AT easychair.org