170 citations · 301 across the 16 of their papers we have counts for
16 papers
Modeling the merger-ringdown of an eccentric test-mass inspiral into a Kerr black hole using the effective-one-body framework
Guglielmo Faggioli, Alessandra Buonanno, Maarten van de Meent +1
We characterize and phenomenologically model the merger-ringdown of gravitational waves emitted by a small compact object that plunges and merges into a Kerr black hole from equato…
Advancing the Effective-One-Body Framework in the Test-Mass Limit
Nami Nishimura, Alessandra Buonanno, Guglielmo Faggioli +2
We present SEOB-TML, an enhanced effective-one-body (EOB) framework for the test-mass limit, optimized for quasi-circular, spin-aligned binary black holes. On the dynamical side, w…
Analysis of late-time tails in spin-aligned eccentric binary black hole mergers
Tousif Islam, Guglielmo Faggioli, Gaurav Khanna
We present a comprehensive analysis of late-time tails in gravitational radiation from merging spin-aligned eccentric binary black holes, using high-accuracy point-particle black h…
Peaking into the abyss: Characterizing the merger of equatorial-eccentric-geodesic plunges in rotating black holes
Guglielmo Faggioli, Maarten van de Meent, Alessandra Buonanno +1
We study the gravitational waveforms generated by critical, equatorial plunging geodesics of the Kerr metric that start from an unstable-circular-orbit, which describe the test-mas…
Judging the Judges: A Collection of LLM-Generated Relevance Judgements
Hossein A. Rahmani, Clemencia Siro, Mohammad Aliannejadi +6
Using Large Language Models (LLMs) for relevance assessments offers promising opportunities to improve Information Retrieval (IR), Natural Language Processing (NLP), and related fi…
Variations in Relevance Judgments and the Shelf Life of Test Collections
Andrew Parry, Maik Fröbe, Harrisen Scells +5
The fundamental property of Cranfield-style evaluations, that system rankings are stable even when assessors disagree on individual relevance decisions, was validated on traditiona…
LLMJudge: LLMs for Relevance Judgments
Hossein A. Rahmani, Emine Yilmaz, Nick Craswell +6
The LLMJudge challenge is organized as part of the LLM4Eval workshop at SIGIR 2024. Test collections are essential for evaluating information retrieval (IR) systems. The evaluation…
Report on the 1st Workshop on Large Language Model for Evaluation in Information Retrieval (LLM4Eval 2024) at SIGIR 2024
Hossein A. Rahmani, Clemencia Siro, Mohammad Aliannejadi +6
The first edition of the workshop on Large Language Model for Evaluation in Information Retrieval (LLM4Eval 2024) took place in July 2024, co-located with the ACM SIGIR Conference…
Phenomenology and origin of late-time tails in eccentric binary black hole mergers
Tousif Islam, Guglielmo Faggioli, Gaurav Khanna +3
We investigate the late-time tail behavior in gravitational waves from merging eccentric binary black holes (BBH) using black hole perturbation theory. For simplicity, we focus onl…
Words Blending Boxes. Obfuscating Queries in Information Retrieval using Differential Privacy
Francesco Luigi De Faveri, Guglielmo Faggioli, Nicola Ferro
Ensuring the effectiveness of search queries while protecting user privacy remains an open issue. When an Information Retrieval System (IRS) does not protect the privacy of its use…
Testing eccentric corrections to the radiation-reaction force in the test-mass limit of effective-one-body models
Guglielmo Faggioli, Maarten van de Meent, Alessandra Buonanno +3
In this work, we test an effective-one-body radiation-reaction force for eccentric planar orbits of a test mass in a Kerr background, which contains third-order post-Newtonian (PN)…
Perspectives on Large Language Models for Relevance Judgment
Guglielmo Faggioli, Laura Dietz, Charles Clarke +8
When asked, large language models (LLMs) like ChatGPT claim that they can assist with relevance judgments but it is not clear whether automated judgments can reliably be used in ev…
Query Performance Prediction for Neural IR: Are We There Yet?
Guglielmo Faggioli, Thibault Formal, Stefano Marchesin +3
Evaluation in Information Retrieval relies on post-hoc empirical procedures, which are time-consuming and expensive operations. To alleviate this, Query Performance Prediction (QPP…
Towards Feature Selection for Ranking and Classification Exploiting Quantum Annealers
Maurizio Ferrari Dacrema, Fabio Moroni, Riccardo Nembrini +3
Feature selection is a common step in many ranking, classification, or prediction tasks and serves many purposes. By removing redundant or noisy features, the accuracy of ranking o…
Towards simulating a realistic data analysis with an optimised angular power spectrum of spectroscopic galaxy surveys
Guglielmo Faggioli, Konstantinos Tanidis, Stefano Camera
The angular power spectrum is a natural tool to analyse the observed galaxy number count fluctuations. In a standard analysis, the angular galaxy distribution is sliced into concen…
Disentangling multiple high-energy emission components in the Vela X pulsar wind nebula with the Fermi Large Area Telescope
L. Tibaldo, R. Zanin, G. Faggioli +4
Vela X is a pulsar wind nebula in which two relativistic particle populations with distinct spatial and spectral distributions dominate the emission at different wavelengths. An ex…