4 papers
AutoBench: Automating LLM Evaluation through Reciprocal Peer Assessment
Dario Loi, Elena Maria MuiÃ, Federico Siciliano +4
We present AutoBench, a fully automated and self-sustaining framework for evaluating Large Language Models (LLMs) through reciprocal peer assessment. This paper provides a rigorous…
Redefining Retrieval Evaluation in the Era of LLMs
Giovanni Trappolini, Florin Cuconasu, Simone Filice +2
Traditional Information Retrieval (IR) metrics, such as nDCG, MAP, and MRR, assume that human users sequentially examine documents with diminishing attention to lower ranks. This a…
Renormalized Graph Representations for Node Classification
Francesco Caso, Giovanni Trappolini, Andrea Bacciu +2
Graph neural networks process information on graphs represented at a given resolution scale. We analyze the effect of using different coarse-grained graph resolutions, obtained thr…
ECLIPSE: Contrastive Dimension Importance Estimation with Pseudo-Irrelevance Feedback for Dense Retrieval
Giulio D'Erasmo, Giovanni Trappolini, Nicola Tonellotto +1
Recent advances in Information Retrieval have leveraged high-dimensional embedding spaces to improve the retrieval of relevant documents. Moreover, the Manifold Clustering Hypothes…