| Vol-4200 urn:nbn:de:0074-4200-x Copyright © 2025 for the individual papers by the papers' authors. Copyright © 2025 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

# SmaLLEXT 2025
Small and Efficient Large Language Models for Knowledge Extraction 2025

## Proceedings of the Workshop on Small and Efficient Large Language Models for Knowledge Extraction (SmaLLEXT 2025)
co-located with CIKM 2025

## Seoul, Korea, November 14, 2025.

Edited by

### Felice Antonio Merra 1
Kristian Skračić 1
Daniele Malitesta 2
Jacek Golebiowski 3
Pasquale Minervini 4

1 Cognism, London, United Kingdom
2 Université Paris-Saclay, CentraleSupélec, Inria, Gif-sur-Yvette, France
3 distil labs, Berlin, Germany
4 University of Edinburgh and Miniml.AI, Edinburgh, United Kingdom

## Table of Contents

- Preface
  Summary: There were 7 papers submitted for peer review to this workshop. Out of these, 5 papers were accepted as peer-reviewed papers for this volume.
  1-5

### Peer-reviewed papers

- Exploring Approaches for Detecting Memorization of Recommender System Data in Large Language Models
  Antonio Colacicco, Vito Guida, Dario Di Palma, Fedelucio Narducci, Tommaso Di Noia
  6-14
- Exploiting LLMs to Improve Recommendation Diversity
  Basar Yilmaz, Ali Eren Cankaya, Ismail Sengor Altingovde, Pinar Karagoz, Ismail Hakki Toroslu
  15-24
- SEDA: A Self-Adapted Entity-Centric Data Augmentation for Boosting Grid-based Discontinuous NER Models
  Wen-Fang Su, Hsiao-Wei Chou, Wen-Yang Lin
  25-39
- CliqueParcel: An Approach for Batching LLM Prompts that Jointly Optimizes Efficiency and Faithfulness
  Jiayi Liu, Tinghan Yang, Jennifer Neville
  40-58
- Identifying Business Trends from Stock Market Data utilizing Domain-Specialized Sentence-RoBERTa and BERTopic Technique
  Ye Lim Jung, Hyoung Sun Yoo
  59-64

### Keynotes

- Automating Neural Network Design: Neural Architecture Search for Small and Efficient Models - Keynote
  Aaron Klein
  65-69
- Machine Learning Without Data: Training Small Expert Agents With Minimal Examples - Keynote
  Jacek Golebiowski, Maciej Gryka, Vineeth Reddy Guda, Gabi Kadlecová, Bartek Kruszczyński, Selim Nowicki, Jonas Verschueren, Usman Zafar
  70-77

2026-04-17: submitted by Felice Antonio Merra, Daniele Malitesta
2026-04-28: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) | valid HTML5 |