| Vol-4046 urn:nbn:de:0074-4046-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).

# RecSys-in-HR 2025
Recommender Systems for Human Resources 2025

### Proceedings of the 5th Workshop on Recommender Systems for Human Resources (RecSys-in-HR 2025)
co-located with the 19th ACM Conference on Recommender Systems (RecSys 2025)

### Prague, Czech Republic, 22nd–26th September 2025.

Edited by

### Mesut Kaya *
Toine Bogers **
Guillaume Bied ***
Chris Johnson ****
Jens-Joris Decorte *****

* Jobindex A/S, Jobindex, Copenhagen, Denmark
** IT University of Copenhagen, Computer Science Department, Copenhagen, Denmark
*** Ghent University, Ghent, Belgium
**** Indeed, Indeed, USA
***** TechWolf, TechWolf, Ghent, Belgium

## Table of Contents

- Summary: There were 16 papers submitted for peer-review to this workshop. Out of these, 9 papers were accepted for this volume.

- An Efficient Long-Context Ranking Architecture With Calibrated LLM Distillation: Application to Person–Job Fit
  Warren Jouanneau, Emma Jouffroy, Marc Palyart
- Benchmarking Predictive and Recommendation Models for Knowledge Work Productivity on the RLKWiC Dataset
  Yuuki Tachioka
- Explained, yet misunderstood: How AI Literacy shapes HR Managers’ interpretation of User Interfaces in Recruiting Recommender Systems
  Yannick Kalff, Katharina Simbeck
- Evaluating LLM Behavior in Hiring: Implicit Weights, Fairness Across Groups, and Alignment with Human Preferences
  Morgane Hoffmann, Emma Jouffroy, Warren Jouanneau, Marc Palyart, Charles Pebereau
- From Retrieval to Ranking: A Two-Stage Neural Framework for Automated Skill Extraction
  Aleksander Bielinski, David Brazier
- JoLA: Job Landscape Aware Job Recommendation
  Solal Nathan, Guillaume Bied, Elia Perennes, Philippe Caillou, Bruno Crepon, Christophe Gaillac, Michèle Sebag
- Mind the Task Gap: Unsupervised Skill–Task Link Prediction for Workforce Upskilling
  Yee Sen Tan, Daryl Low, Eugene Chua, Alejandro Seif, Leo Li, Lois Ji
- Towards Explainable Job Title Matching: Leveraging Semantic Textual Relatedness and Knowledge Graphs
  Vadim Zadykian, Bruno Andrade, Haithem Afli
- Understanding and Defending Against Resume-Based Prompt Injections in HR AI
  Arda Akdemir, Joshua H. Levy

2025-09-12: submitted by Mesut Kaya, metadata incl. bibliographic data published under Creative Commons CC0
2025-09-28: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|