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

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