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

5 citations · 10 across the 13 of their papers we have counts for

collaborators

14 papers

cs.IR2026

The Disconnect Between Better Descriptive Reasoning Trace Quality and Recommendation Effectiveness

Gustavo Penha, Juan Elenter, Claudia Hauff +3

Recent work has focused on improving explicit natural-language descriptive reasoning traces for generative recommendation. This includes systems that augment semantic ID (SID) pred…

cs.IR2026

As It Was: Aligning LLM Search Evaluation with Historical User Preferences

Ali Vardasbi, Gustavo Penha, Enrico Palumbo +3

Large-scale search systems evolve faster than human quality assurance can scale, especially for long-tail intents and multilingual queries. LLM-as-a-judge approaches provide a scal…

cs.IR2026

Deploying Semantic ID-based Generative Retrieval for Large-Scale Podcast Discovery at Spotify

Edoardo D'Amico, Marco De Nadai, Praveen Chandar +41

Podcast listening is often grounded in a set of favorite shows, while listener intent can evolve over time. This combination of stable preferences and changing intent motivates rec…

cs.IR2025

From IR to RecSys: Evaluating LLM-based Judges in Cranfield-style Recommendation Collections

Gustavo Penha, Aleksandr V. Petrov, Claudia Hauff +9

The Cranfield paradigm has long provided reliable, reproducible evaluation in ad hoc retrieval, and recent work has begun extending this framework to recommender systems. A recent…

cs.CL2025

Stream: Scaling up Mechanistic Interpretability to Long Context in LLMs via Sparse Attention

J Rosser, José Luis Redondo García, Gustavo Penha +2

As Large Language Models (LLMs) scale to million-token contexts, traditional Mechanistic Interpretability techniques for analyzing attention scale quadratically with context length…

cs.IR2025

AudioBoost: Increasing Audiobook Retrievability in Spotify Search with Synthetic Query Generation

Enrico Palumbo, Gustavo Penha, Alva Liu +6

Spotify has recently introduced audiobooks as part of its catalog, complementing its music and podcast offering. Search is often the first entry point for users to access new items…

cs.IR2025

Semantic IDs for Joint Generative Search and Recommendation

Gustavo Penha, Edoardo D'Amico, Marco De Nadai +8

Generative models powered by Large Language Models (LLMs) are emerging as a unified solution for powering both recommendation and search tasks. A key design choice in these models…

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.LG2025

Adaptive Repetition for Mitigating Position Bias in LLM-Based Ranking

Ali Vardasbi, Gustavo Penha, Claudia Hauff +1

When using LLMs to rank items based on given criteria, or evaluate answers, the order of candidate items can influence the model's final decision. This sensitivity to item position…

cs.IR2025

Aligned Query Expansion: Efficient Query Expansion for Information Retrieval through LLM Alignment

Adam Yang, Gustavo Penha, Enrico Palumbo +1

With the breakthroughs in large language models (LLMs), query generation techniques that expand documents and queries with related terms are becoming increasingly popular in the in…

cs.IR2025

Contextualizing Spotify's Audiobook List Recommendations with Descriptive Shelves

Gustavo Penha, Alice Wang, Martin Achenbach +7

In this paper, we propose a pipeline to generate contextualized list recommendations with descriptive shelves in the domain of audiobooks. By creating several shelves for topics th…

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.IR2024

Bridging Search and Recommendation in Generative Retrieval: Does One Task Help the Other?

Gustavo Penha, Ali Vardasbi, Enrico Palumbo +2

Generative retrieval for search and recommendation is a promising paradigm for retrieving items, offering an alternative to traditional methods that depend on external indexes and…

cs.IR2024★ 4 cited

PODTILE: Facilitating Podcast Episode Browsing with Auto-generated Chapters

Azin Ghazimatin, Ekaterina Garmash, Gustavo Penha +14

Listeners of long-form talk-audio content, such as podcast episodes, often find it challenging to understand the overall structure and locate relevant sections. A practical solutio…