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Demo Data from SIGIR 2026 / reviewers in the wild / expert

Marco Bonizzato

dblp:123/6716 · DBLP profile ↗
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3ranked-venue papers
0as first author
2since 2021 · last 2025
0000-0001-7899-834XORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 3 · 2 since 2021Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Language models and text generation · 54% Deep learning architectures and training · 46%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning › Deep learning architectures and training › regularization
dropout		 0.912025
Hallucination Detox: Sensitivity Dropout (SenD) for Large Language Model Training · ACL (1) 2025
Natural language and speech › Language models and text generation
hallucination detection		 0.912025
Hallucination Detox: Sensitivity Dropout (SenD) for Large Language Model Training · ACL (1) 2025
Natural language and speech › Language models and text generation
hallucination mitigation		 0.912025
Hallucination Detox: Sensitivity Dropout (SenD) for Large Language Model Training · ACL (1) 2025
Machine learning › Deep learning architectures and training › regularization
training regularization		 0.912025
Hallucination Detox: Sensitivity Dropout (SenD) for Large Language Model Training · ACL (1) 2025
Natural language and speech › Language models and text generation
large language model training		 0.312025
Hallucination Detox: Sensitivity Dropout (SenD) for Large Language Model Training · ACL (1) 2025

Methods — techniques the papers use, named apart from their topics

sensitivity dropout · 0.9
YearPublicationVenuePosition
2025 Hallucination Detox: Sensitivity Dropout (SenD) for Large Language Model Training
abstract
Shahrad Mohammadzadeh, Juan David Guerra, Marco Bonizzato, Reihaneh Rabbany, Golnoosh Farnadi. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2025.
Shahrad Mohammadzadeh, Juan David Guerra, Marco Bonizzato, Reihaneh Rabbany, Golnoosh Farnadi
 ACL (1)3
2025 Robust prior-biased acquisition function for human-in-the-loop Bayesian optimization
Rose Guay-Hottin, Lison Kardassevitch, Hugo Pham, Guillaume Lajoie, Marco Bonizzato
 Knowl. Based Syst.5
2012 Motion planning for two 3D-Dubins vehicles with distance constraint
abstract
In this paper we consider the motion planning problem for a 3D-Dubins system consisting of a pair of Dubins vehicles moving in a 3D space while maintaining constant distance. We provide a motion planning algorithm and sufficient conditions on the initial and final configurations that guarantee the existence of admissible controls, moving a first step towards the complete controllability characterization of such type of systems. Results obtained in this paper are particularly relevant in order to solve formation control problem for multiple robots as aerial or underwater vehicles, which move in 3D spaces. Simulation results demonstrate the feasibility of the motion planning algorithm proposed in this paper.
Hamal Marino, Marco Bonizzato, Riccardo Bartalucci, Paolo Salaris, Lucia Pallottino
 IROS2