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20242026
most citedEvaluating Podcast Recommendations with Profile-Aware LLM-as-a-Judge

5 citations · 9 across the 11 of their papers we have counts for

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6 papers · 1 filter

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.IR2025★ 2 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.IR2025★ 5 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.IR2025★ 1 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…