activity
20242026
collaborators

5 papers

cs.IR2026

Embedding Surgery: Localized Updates for Adaptive Ranking Correction in Dense Retrieval

Maddalena Amendola, Antonio Mallia, Raffaele Perego

Dense retrieval systems are core components of modern search engines, recommendation platforms, and retrieval-augmented generation pipelines. They encode documents and queries into…

cs.CY2026

Gender Disparities in StackOverflow's Community-Based Question Answering: A Matter of Quantity versus Quality

Maddalena Amendola, Cosimo Rulli, Carlos Castillo +2

Community Question-Answering platforms, such as Stack Overflow (SO), are valuable knowledge exchange and problem-solving resources. These platforms incorporate mechanisms to assess…

cs.IR2025

Spatially-Enhanced Retrieval-Augmented Generation for Walkability and Urban Discovery

Maddalena Amendola, Chiara Pugliese, Raffaele Perego +1

Large Language Models (LLMs) have become foundational tools in artificial intelligence, supporting a wide range of applications beyond traditional natural language processing, incl…

cs.IR2024

Understanding and Addressing Gender Bias in Expert Finding Task

Maddalena Amendola, Carlos Castillo, Andrea Passarella +1

The Expert Finding (EF) task is critical in community Question&Answer (CQ&A) platforms, significantly enhancing user engagement by improving answer quality and reducing response ti…

cs.IR2024

Leveraging Topic Specificity and Social Relationships for Expert Finding in Community Question Answering Platforms

Maddalena Amendola, Andrea Passarella, Raffaele Perego

Online Community Question Answering (CQA) platforms have become indispensable tools for users seeking expert solutions to their technical queries. The effectiveness of these platfo…