Do We Really Need Specialization? Evaluating Generalist Text Embeddings for Zero-Shot Recommendation and Search

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Attimonelli, Matteo, De Bellis, Alessandro, Pomo, Claudio, Jannach, Dietmar, Di Sciascio, Eugenio, Di Noia, Tommaso
Format:	Preprint
Published:	2025
Subjects:	Information Retrieval Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Fashion Image-to-Image Translation for Complementary Item Retrieval
by: Attimonelli, Matteo, et al.
Published: (2024)

Do Recommender Systems Really Leverage Multimodal Content? A Comprehensive Analysis on Multimodal Representations for Recommendation
by: Pomo, Claudio, et al.
Published: (2025)

Do We Really Need to Drop Items with Missing Modalities in Multimodal Recommendation?
by: Malitesta, Daniele, et al.
Published: (2024)

Do Composed Image Retrieval Benchmarks Require Multimodal Composition?
by: Attimonelli, Matteo, et al.
Published: (2026)

Large-scale Benchmarks for Multimodal Recommendation with Ducho
by: Attimonelli, Matteo, et al.
Published: (2024)

Ducho 2.0: Towards a More Up-to-Date Unified Framework for the Extraction of Multimodal Features in Recommendation
by: Attimonelli, Matteo, et al.
Published: (2024)

Formalizing Multimedia Recommendation through Multimodal Deep Learning
by: Malitesta, Daniele, et al.
Published: (2023)

Stealthy LLM-Driven Data Poisoning Attacks Against Embedding-Based Retrieval-Augmented Recommender Systems
by: Nazary, Fatemeh, et al.
Published: (2025)

A Novel Evaluation Perspective on GNNs-based Recommender Systems through the Topology of the User-Item Graph
by: Malitesta, Daniele, et al.
Published: (2024)

Challenging the Myth of Graph Collaborative Filtering: a Reasoned and Reproducibility-driven Analysis
by: Anelli, Vito Walter, et al.
Published: (2023)

Type-Less yet Type-Aware Inductive Link Prediction with Pretrained Language Models
by: De Bellis, Alessandro, et al.
Published: (2025)

Training-free Graph-based Imputation of Missing Modalities in Multimodal Recommendation
by: Malitesta, Daniele, et al.
Published: (2026)

Dealing with Missing Modalities in Multimodal Recommendation: a Feature Propagation-based Approach
by: Malitesta, Daniele, et al.
Published: (2024)

XAI4LLM. Let Machine Learning Models and LLMs Collaborate for Enhanced In-Context Learning in Healthcare
by: Nazary, Fatemeh, et al.
Published: (2024)

FlowLet: Conditional 3D Brain MRI Synthesis using Wavelet Flow Matching
by: Danese, Danilo, et al.
Published: (2026)

A Reproducible and Fair Evaluation of Partition-aware Collaborative Filtering
by: de Gioia, Domenico, et al.
Published: (2025)

Evaluating ChatGPT as a Recommender System: A Rigorous Approach
by: Di Palma, Dario, et al.
Published: (2023)

KGUF: Simple Knowledge-aware Graph-based Recommender with User-based Semantic Features Filtering
by: Bufi, Salvatore, et al.
Published: (2024)

Interactive Question Answering Systems: Literature Review
by: Biancofiore, Giovanni Maria, et al.
Published: (2022)

Machine-learned Adversarial Attacks against Fault Prediction Systems in Smart Electrical Grids
by: Ardito, Carmelo, et al.
Published: (2023)

On the Impact of Graph Neural Networks in Recommender Systems: A Topological Perspective
by: Malitesta, Daniele, et al.
Published: (2025)

DataRec: A Python Library for Standardized and Reproducible Data Management in Recommender Systems
by: Mancino, Alberto Carlo Maria, et al.
Published: (2024)

A Survey on Intent-aware Recommender Systems
by: Jannach, Dietmar, et al.
Published: (2024)

Performance Comparison of Session-based Recommendation Algorithms based on GNNs
by: Shehzad, Faisal, et al.
Published: (2023)

Reproducibility of LLM-based Recommender Systems Research: Worrying Observations from an Initial Analysis
by: Shehzad, Faisal, et al.
Published: (2026)

Rethinking Group Recommender Systems in the Era of Generative AI: From One-Shot Recommendations to Agentic Group Decision Support
by: Jannach, Dietmar, et al.
Published: (2025)

Are the Hidden States Hiding Something? Testing the Limits of Factuality-Encoding Capabilities in LLMs
by: Servedio, Giovanni, et al.
Published: (2025)

Calibrated Recommendations: Survey and Future Directions
by: da Silva, Diego Corrêa, et al.
Published: (2025)

A Survey on Point-of-Interest Recommendations Leveraging Heterogeneous Data
by: Wang, Zehui, et al.
Published: (2023)

LLaMAs Have Feelings Too: Unveiling Sentiment and Emotion Representations in LLaMA Models Through Probing
by: Di Palma, Dario, et al.
Published: (2025)

Dot Product is All You Need: Bridging the Gap Between Item Recommendation and Link Prediction
by: Malitesta, Daniele, et al.
Published: (2024)

Do We Really Even Need Data?
by: Hoffman, Kentaro, et al.
Published: (2024)

A Worrying Reproducibility Study of Intent-Aware Recommendation Models
by: Shehzad, Faisal, et al.
Published: (2025)

Diffusion Recommender Models and the Illusion of Progress: A Concerning Study of Reproducibility and a Conceptual Mismatch
by: Benigni, Michael, et al.
Published: (2025)

A Survey on Popularity Bias in Recommender Systems
by: Klimashevskaia, Anastasiia, et al.
Published: (2023)

Do LLMs Memorize Recommendation Datasets? A Preliminary Study on MovieLens-1M
by: Di Palma, Dario, et al.
Published: (2025)

Investigating the hadron nature of high-energy photons with PeVatrons
by: Di Sciascio, Giuseppe
Published: (2024)

ViLLA-MMBench: A Unified Benchmark Suite for LLM-Augmented Multimodal Movie Recommendation
by: Nazary, Fatemeh, et al.
Published: (2025)

Exploring Approaches for Detecting Memorization of Recommender System Data in Large Language Models
by: Colacicco, Antonio, et al.
Published: (2026)

MambaOut: Do We Really Need Mamba for Vision?
by: Yu, Weihao, et al.
Published: (2024)