CFP: TalentCLEF2026 Workshop/Lab (CLEF2026) - Skill and Job Title Intelligence for Human Capital Management
Luis Gasco
(* apologies for cross-posting *)
Call for Participation TalentCLEF Workshop/Lab (CLEF 2026)
Skill and Job Title Intelligence for Human Capital Management
https://talentclef.github.io/talentclef/
TalentCLEF is an initiative to advance Natural Language Processing (NLP) in Human Capital Management (HCM). It aims to create a public benchmark for model evaluation and promote collaboration to develop fair, multilingual, and flexible systems that improve Human Resources (HR) practices across different industries.
📅 Registration Deadline: April 23, 2026
Key information:
Registration: https://clef2026.clef-initiative.eu/
Why TalentCLEF?
The labor market is undergoing a profound transformation. Roles evolve faster than ever, skills become obsolete in years rather than decades, and organizations operate in increasingly multilingual and global environments. At the same time, Artificial Intelligence, and in particular Natural Language Processing and Large Language Models, is reshaping how talent is identified, matched, and developed, enabling organizations to analyze job requirements and candidate profiles at scale and to respond more rapidly to evolving workforce needs.
Despite this progress, talent intelligence systems still face major challenges. Much of the recent progress in NLP for Human Capital Management relies on private or restricted datasets, together with a lack of standardized evaluation frameworks, which hinders reproducibility and prevents the establishment of robust benchmarks. In addition, many approaches struggle to operate reliably in multilingual and cross-lingual settings, and growing concerns remain regarding fairness and ethical robustness in automated decision-making systems.
TalentCLEF 2026 addresses these challenges by providing open and privacy-preserving benchmarks, realistic use cases grounded in Human Capital Management workflows, and a shared evaluation framework that enables meaningful comparison of methods. By bridging research innovation with real-world requirements, TalentCLEF aims to foster the development of NLP systems that are not only accurate, but also transparent, fair, and applicable in practice.
Tasks Overview
TalentCLEF 2026 is structured into two independent but complementary tasks, allowing participants to compete in one or both.
Task A - Contextualized Job-Person Matching: Task A challenges participants to develop systems capable of identifying and ranking the most suitable candidate résumés for a given job offer, based on their overall relevance to the position. Unlike approaches that focus on isolated entities such as job titles or individual skills, this task emphasizes context-aware matching between full job descriptions and candidate profiles. The task is framed as an information retrieval problem, where each job offer is matched against a fixed set of candidate résumés, which are returned as a ranked list sorted by relevance. The evaluation is conducted in English and Spanish, with an additional cross-lingual setting, reflecting realistic recruitment scenarios in multilingual environments and encouraging the development of robust, language-aware matching models.
Task B - Job-Skill Matching with Skill Type Classification: Task B focuses on automatically identifying the skills associated with a given job title and classifying each retrieved skill according to its role within the job profile. Participants are required to retrieve relevant skills from a predefined gazetteer, but also to determine whether each relevant skill is core (required) or complementary (optional). This task reflects the growing importance of skill-based representations in Human Capital Management, supporting applications such as recruitment, workforce planning, and upskilling. By combining skill retrieval with relevance-based classification, Task B encourages approaches that go beyond simple matching and capture the nuanced importance of different skills across job roles.
Schedule
2nd February 2026 - Development data available for Tasks A
2nd February 2026 - Training data available for Task B
16th February 2026 - Development data available for Task B
2nd March 2026 - Codabench Release for Task A and Task B
13th April - 3rd May 2026 - Evaluation Period for Task A and Task B
23rd April - Official registration deadline
7th May 2025 – Publication of Official Results
30th May 2025 – Submission of CLEF 2025 Participant Working Notes (CEUR-WS)
27th June 2025 - Notification of Acceptance for Participant Papers
Publications and CLEF 2026 workshop
Teams participating in TalentCLEF will be invited to submit a system description paper for the CLEF 2026 Working Notes proceedings, published on CEUR-WS. Additionally, they will have the opportunity to present a brief overview of their approach at the TalentCLEF 2026 workshop, which will be co-located at CLEF 2026 and will take place in Jena, Germany, from September 21st to 24th, 2026.
Main Organizers
Luis Gascó, Avature
Hermenegildo Fabregat, Avature
Laura García-Sardiña, Avature
Paula Estrella, Avature, Spain
Casimiro Pío Carrino, Avature, Spain
Jens-Joris Decorte, TechWolf
Matthias De Lange, TechWolf
Daniel Deniz Cerpa, Avature, Spain
Álvaro Rodrigo, Universidad Nacional de Educación a Distancia (UNED)
Rabih Zbib, Avature, Spain