Kidist Amde Mekonnen

I am a third-year ELLIS PhD researcher in the Information Retrieval Lab at the University of Amsterdam, where I work with Prof. dr. Maarten de Rijke as my promotor and Dr. Andrew Yates as my co-promotor.

My research focuses on generative retrieval, recommendation, neural information retrieval, multilingual retrieval, retrieval-augmented generation, and scalable retrieval systems. I study how retrieval systems can represent, generate, rank, and adapt to information needs across languages and domains. My work connects generative information retrieval with efficient learning objectives, continual memory, robust decoding, and evaluation for real-world retrieval settings.

🔍 Research Interests

• Generative information retrieval
• Neural information retrieval and recommender systems
• Multilingual and low-resource retrieval
• Continual learning for retrieval systems
• Robust decoding and evaluation for generative retrieval
• Retrieval-augmented generation and scalable retrieval systems
• Broader interests in generative modeling, multimodal learning, and reinforcement learning

📝 Selected Publications

A Parametric Memory Head for Continual Generative Retrieval [DOI] (Full Paper, to appear) The 49th International ACM SIGIR Conference on Research and Development in Information Retrieval Kidist Amde Mekonnen, Yubao Tang, and Maarten de Rijke

Lost in Decoding? Reproducing and Stress-Testing the Look-Ahead Prior in Generative Retrieval [DOI] (Reproducibility Track, to appear) The 49th International ACM SIGIR Conference on Research and Development in Information Retrieval Kidist Amde Mekonnen, Yongkang Li, Yubao Tang, Simon Lupart, and Maarten de Rijke

The Multilingual Curse at the Retrieval Layer: Evidence from Amharic [arXiv] [PDF]
The 1st Workshop on Multilinguality in the Era of Large Language Models, ACL 2026
Yosef Worku Alemneh^†, Kidist Amde Mekonnen^†, and Maarten de Rijke
^†Equal contribution

uva-irlab-conv at SemEval-2026 Task 8: Multi-Turn RAG with Learned Sparse Retrieval and Listwise Reranking [arXiv] [PDF]
The 20th International Workshop on Semantic Evaluation, ACL 2026
Simon Lupart, Kidist Amde Mekonnen, Zahra Abbasiantaeb, and Mohammad Aliannejadi

Lightweight and Direct Document Relevance Optimization for Generative Information Retrieval [DOI] (Full Paper) The 48th International ACM SIGIR Conference on Research and Development in Information Retrieval Kidist Amde Mekonnen, Yubao Tang, and Maarten de Rijke

Optimized Text Embeddings & Benchmarks for Amharic Passage Retrieval [Paper]
Findings of the Association for Computational Linguistics
Kidist Amde Mekonnen^†, Yosef Worku Alemneh^†, and Maarten de Rijke
^†Equal contribution

Adv-KD: Adversarial Knowledge Distillation for Faster Diffusion Sampling [Paper]

Conditioning GAN Without Training Dataset [Paper]

Balanced Face Dataset: Guiding StyleGAN for Labeled Synthetic Face Image Dataset for Underrepresented Group [Paper]

💡 Research Highlights

• Continual generative retrieval: developing parametric-memory approaches that allow generative retrieval systems to update and retain document knowledge over time.
• Decoding and robustness: reproducing and stress-testing look-ahead decoding priors to understand when generative retrieval gains are reliable under query variation and cross-lingual shift.
• Direct relevance optimization: designing lightweight objectives for improving document relevance in generative information retrieval.
• Multilingual and low-resource retrieval: studying retrieval-layer failures in multilingual systems, with evidence from Amharic retrieval benchmarks, optimized text embeddings, and MeLLM 2026 work on the multilingual curse.
• Recommendation and RAG: exploring generative recommendation, semantic identifiers, trie-constrained generation, and retrieval-augmented systems.

🎓 Education and Experience

• 2023–Present, ELLIS PhD Researcher, University of Amsterdam, The Netherlands
• Apr. 2022–Oct. 2022, Data Science Research Intern, Nanovery, Newcastle upon Tyne, United Kingdom
• 2020–2023, MSc in Data Science, University of Trento, Italy
• 2019–2020, MSc in Machine Intelligence, African Institute for Mathematical Sciences / AMMI, Rwanda
• 2017–2019, Assistant Lecturer, Department of Computer Science, University of Gondar, Ethiopia
• 2013–2017, BSc in Computer Science, University of Gondar, Ethiopia

🤝 Teaching and Service

• Recommender Systems, University of Amsterdam, MSc Artificial Intelligence, 2025–2026. Developed and delivered lectures on generative recommendation and Snellius-based practical experimentation. [2025 Slides] [2026 GenRec Slides] [Snellius Guide]
• Information Retrieval 0, University of Amsterdam, BSc Artificial Intelligence, 2025. Teaching assistant for labs, assignments, project feedback, grading, and exam assessment.
• BSc thesis supervision, University of Amsterdam, 2026. Supervising a thesis project on multilingual search for low-resource languages.
• Teaching Assistant, AddisCoder — programming and algorithms outreach. [Blog]
• Hackathon mentor and organizer support, European Summer School on Information Retrieval, ESSIR 2024
• Mentor, MeetMentors
• Core Team Volunteer, Women in AI & Robotics, Sep. 2021–Apr. 2022
• Reviewer for major information retrieval and machine learning venues, including NeurIPS 2026, SIGIR 2026 across multiple tracks, and ECIR 2025; received ECIR best reviewer recognition. [Certificate]