most citedEvaluating Podcast Recommendations with Profile-Aware LLM-as-a-Judge

5 citations · 8 across the 4 of their papers we have counts for

collaborators

6 papers

cs.LG2025

Mapping Faithful Reasoning in Language Models

Jiazheng Li, Andreas Damianou, J Rosser +2

Chain-of-thought (CoT) traces promise transparency for reasoning language models, but prior work shows they are not always faithful reflections of internal computation. This raises…

cs.IR20252 cited

Describe What You See with Multimodal Large Language Models to Enhance Video Recommendations

Marco De Nadai, Andreas Damianou, Mounia Lalmas

Existing video recommender systems rely primarily on user-defined metadata or on low-level visual and acoustic signals extracted by specialised encoders. These low-level features d…

cs.IR20255 cited

Evaluating Podcast Recommendations with Profile-Aware LLM-as-a-Judge

Francesco Fabbri, Gustavo Penha, Edoardo D'Amico +7

Evaluating personalized recommendations remains a central challenge, especially in long-form audio domains like podcasts, where traditional offline metrics suffer from exposure bia…

cs.CL2025

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models

Bernd Huber, Ghazal Fazelnia, Andreas Damianou +6

Large language models (LLMs) excel at generating contextually relevant content. However, tailoring these outputs to individual users for effective personalization is a significant…

cs.IR20251 cited

Text2Tracks: Prompt-based Music Recommendation via Generative Retrieval

Enrico Palumbo, Gustavo Penha, Andreas Damianou +5

In recent years, Large Language Models (LLMs) have enabled users to provide highly specific music recommendation requests using natural language prompts (e.g. "Can you recommend so…

cs.CY2025

Policy-as-Prompt: Rethinking Content Moderation in the Age of Large Language Models

Konstantina Palla, José Luis Redondo García, Claudia Hauff +5

Content moderation plays a critical role in shaping safe and inclusive online environments, balancing platform standards, user expectations, and regulatory frameworks. Traditionall…