EARL: Workshop on Evaluating and Applying Recommendation Systems with Large Language Models

Irene Li; Ruihai Dong; Lei Li; Li Chen

doi:10.1145/3640457.3687110

EARL: Workshop on Evaluating and Applying Recommendation Systems with Large Language Models

Irene Li, Ruihai Dong, Lei Li, Li Chen

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

Abstract

This workshop aims to explore the evaluation and application of Large Language Models (LLMs) in recommendation systems (RSs), highlighting innovations, challenges, and future directions, focusing on enhancing RSs through LLM techniques such as prompting, fine-tuning, and developing conversational systems. By gathering researchers and partitioners from both academia and industry, the workshop focuses on discussing state-of-the-art techniques and ad- dressing challenges and innovative applications in various sectors. At last, the workshop encourages research on topics including LLM integration, evaluating LLM-based RSs, transparency, and conversational RS development, aiming to set a research agenda for future RS advancements.

Original language	English
Title of host publication	Proceedings of the 18th ACM Conference on Recommender Systems, RecSys 2024
Editors	Tommaso Di Noia, Pasquale Lops, Thorsten Joachims, Katrien Verbert, Pablo Castells, Zhenhua Dong, Ben London
Publisher	Association for Computing Machinery (ACM)
Pages	1262-1264
Number of pages	3
ISBN (Electronic)	9798400705052
ISBN (Print)	9798400705052
DOIs	https://doi.org/10.1145/3640457.3687110
Publication status	Published - 8 Oct 2024
Event	The 18th ACM Conference on Recommender Systems - Bari, Italy Duration: 14 Oct 2024 → 18 Oct 2024 https://recsys.acm.org/recsys24/ (Conference website) https://recsys.acm.org/recsys24/program/ (conference program)

Publication series

Name	Proceedings of the ACM Conference on Recommender Systems, RecSys
Publisher	Association for Computing Machinery

Conference

Conference	The 18th ACM Conference on Recommender Systems
Abbreviated title	RecSys 2024
Country/Territory	Italy
City	Bari
Period	14/10/24 → 18/10/24
Internet address	https://recsys.acm.org/recsys24/ (Conference website) https://recsys.acm.org/recsys24/program/ (conference program)

User-Defined Keywords

Evaluation and Application
Large Language Models (LLM)
Recommendation Systems

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1145/3640457.3687110

Cite this

Li, I., Dong, R., Li, L., & Chen, L. (2024). EARL: Workshop on Evaluating and Applying Recommendation Systems with Large Language Models. In T. D. Noia, P. Lops, T. Joachims, K. Verbert, P. Castells, Z. Dong, & B. London (Eds.), Proceedings of the 18th ACM Conference on Recommender Systems, RecSys 2024 (pp. 1262-1264). (Proceedings of the ACM Conference on Recommender Systems, RecSys). Association for Computing Machinery (ACM). https://doi.org/10.1145/3640457.3687110

Li, Irene ; Dong, Ruihai ; Li, Lei et al. / EARL: Workshop on Evaluating and Applying Recommendation Systems with Large Language Models. Proceedings of the 18th ACM Conference on Recommender Systems, RecSys 2024. editor / Tommaso Di Noia ; Pasquale Lops ; Thorsten Joachims ; Katrien Verbert ; Pablo Castells ; Zhenhua Dong ; Ben London. Association for Computing Machinery (ACM), 2024. pp. 1262-1264 (Proceedings of the ACM Conference on Recommender Systems, RecSys).

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title = "EARL: Workshop on Evaluating and Applying Recommendation Systems with Large Language Models",

abstract = "This workshop aims to explore the evaluation and application of Large Language Models (LLMs) in recommendation systems (RSs), highlighting innovations, challenges, and future directions, focusing on enhancing RSs through LLM techniques such as prompting, fine-tuning, and developing conversational systems. By gathering researchers and partitioners from both academia and industry, the workshop focuses on discussing state-of-the-art techniques and ad- dressing challenges and innovative applications in various sectors. At last, the workshop encourages research on topics including LLM integration, evaluating LLM-based RSs, transparency, and conversational RS development, aiming to set a research agenda for future RS advancements.",

keywords = "Evaluation and Application, Large Language Models (LLM), Recommendation Systems",

author = "Irene Li and Ruihai Dong and Lei Li and Li Chen",

note = "Publisher Copyright: {\textcopyright} 2024 Copyright held by the owner/author(s); The 18th ACM Conference on Recommender Systems, RecSys 2024 ; Conference date: 14-10-2024 Through 18-10-2024",

year = "2024",

month = oct,

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doi = "10.1145/3640457.3687110",

language = "English",

isbn = "9798400705052",

series = "Proceedings of the ACM Conference on Recommender Systems, RecSys",

publisher = "Association for Computing Machinery (ACM)",

pages = "1262--1264",

editor = "Noia, {Tommaso Di} and Pasquale Lops and Thorsten Joachims and Katrien Verbert and Pablo Castells and Zhenhua Dong and Ben London",

booktitle = "Proceedings of the 18th ACM Conference on Recommender Systems, RecSys 2024",

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Li, I, Dong, R, Li, L & Chen, L 2024, EARL: Workshop on Evaluating and Applying Recommendation Systems with Large Language Models. in TD Noia, P Lops, T Joachims, K Verbert, P Castells, Z Dong & B London (eds), Proceedings of the 18th ACM Conference on Recommender Systems, RecSys 2024. Proceedings of the ACM Conference on Recommender Systems, RecSys, Association for Computing Machinery (ACM), pp. 1262-1264, The 18th ACM Conference on Recommender Systems, Bari, Italy, 14/10/24. https://doi.org/10.1145/3640457.3687110

EARL: Workshop on Evaluating and Applying Recommendation Systems with Large Language Models. / Li, Irene; Dong, Ruihai; Li, Lei et al.
Proceedings of the 18th ACM Conference on Recommender Systems, RecSys 2024. ed. / Tommaso Di Noia; Pasquale Lops; Thorsten Joachims; Katrien Verbert; Pablo Castells; Zhenhua Dong; Ben London. Association for Computing Machinery (ACM), 2024. p. 1262-1264 (Proceedings of the ACM Conference on Recommender Systems, RecSys).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

TY - GEN

T1 - EARL: Workshop on Evaluating and Applying Recommendation Systems with Large Language Models

AU - Li, Irene

AU - Dong, Ruihai

AU - Li, Lei

AU - Chen, Li

PY - 2024/10/8

Y1 - 2024/10/8

N2 - This workshop aims to explore the evaluation and application of Large Language Models (LLMs) in recommendation systems (RSs), highlighting innovations, challenges, and future directions, focusing on enhancing RSs through LLM techniques such as prompting, fine-tuning, and developing conversational systems. By gathering researchers and partitioners from both academia and industry, the workshop focuses on discussing state-of-the-art techniques and ad- dressing challenges and innovative applications in various sectors. At last, the workshop encourages research on topics including LLM integration, evaluating LLM-based RSs, transparency, and conversational RS development, aiming to set a research agenda for future RS advancements.

AB - This workshop aims to explore the evaluation and application of Large Language Models (LLMs) in recommendation systems (RSs), highlighting innovations, challenges, and future directions, focusing on enhancing RSs through LLM techniques such as prompting, fine-tuning, and developing conversational systems. By gathering researchers and partitioners from both academia and industry, the workshop focuses on discussing state-of-the-art techniques and ad- dressing challenges and innovative applications in various sectors. At last, the workshop encourages research on topics including LLM integration, evaluating LLM-based RSs, transparency, and conversational RS development, aiming to set a research agenda for future RS advancements.

KW - Evaluation and Application

KW - Large Language Models (LLM)

KW - Recommendation Systems

UR - https://dl.acm.org/doi/10.1145/3640457.3687110

U2 - 10.1145/3640457.3687110

DO - 10.1145/3640457.3687110

M3 - Conference proceeding

SN - 9798400705052

T3 - Proceedings of the ACM Conference on Recommender Systems, RecSys

SP - 1262

EP - 1264

BT - Proceedings of the 18th ACM Conference on Recommender Systems, RecSys 2024

A2 - Noia, Tommaso Di

A2 - Lops, Pasquale

A2 - Joachims, Thorsten

A2 - Verbert, Katrien

A2 - Castells, Pablo

A2 - Dong, Zhenhua

A2 - London, Ben

PB - Association for Computing Machinery (ACM)

T2 - The 18th ACM Conference on Recommender Systems

Y2 - 14 October 2024 through 18 October 2024

ER -

Li I, Dong R, Li L, Chen L. EARL: Workshop on Evaluating and Applying Recommendation Systems with Large Language Models. In Noia TD, Lops P, Joachims T, Verbert K, Castells P, Dong Z, London B, editors, Proceedings of the 18th ACM Conference on Recommender Systems, RecSys 2024. Association for Computing Machinery (ACM). 2024. p. 1262-1264. (Proceedings of the ACM Conference on Recommender Systems, RecSys). doi: 10.1145/3640457.3687110

EARL: Workshop on Evaluating and Applying Recommendation Systems with Large Language Models

Abstract

Publication series

Conference

User-Defined Keywords

UN SDGs

Access to Document

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