large language models

AIDME: A Scalable, Interpretable Framework for AI-Aided Scoping Reviews

Poster Presentation - The 48th International ACM SIGIR Conference on Research and Development in Information Retrieval. Padua, Italy.

AIDME: A Scalable, Interpretable Framework for AI-Aided Scoping Reviews

Scientific publishing is expanding rapidly across disciplines, making it increasingly difficult for researchers to organize, filter, and synthesize the literature. Systematic reviews address this challenge through structured analysis, but the early …

PILs of Knowledge: A Synthetic Benchmark for Evaluating Question Answering Systems in Healthcare

Patient Information Leaflets (PILs) provide essential information about medication usage, side effects, precautions, and interactions, making them a valuable resource for Question Answering (QA) systems in healthcare. However, no dedicated benchmark …

Large Language Models for Combinatorial Optimization: A Systematic Review

This systematic review explores the application of Large Language Models (LLMs) in Combinatorial Optimization (CO). We report our findings using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We conduct a …

Report on the 14th Italian Information Retrieval Workshop (IIR 2024)

IIR 2024, the 14th Italian Information Retrieval Workshop, served as the annual event for the IR and RS communities both in Italy and collaborating with Italian research institutions. This year's event spanned two days and featured studies on various …

Report on the Hands-On PhD Course on Responsible AI from the Lens of an Information Access Researcher

While the concept of responsible AI is becoming more and more popular, practitioners and researchers may often struggle to characterize responsible practices in their own work. This paper presents a four-day, PhD-level course on Responsible …

Enhancing Fact-Checking: From Crowdsourced Validation to Integration with Large Language Models

Information retrieval effectiveness evaluation is often carried out by means of test collections. Many works investigated possible sources of bias in such an approach. We propose a systematic approach to identify bias and its causes, and to remove …

Towards a Conversational-Based Agent for Healthcare

Workshop Talk - European Federation of Medical Informatics Special Topic Conference 2023 (EFMI STC 2023). Turin, Italy.