3 citations · 7 across the 8 of their papers we have counts for
8 papers
Reasoning Capabilities and Invariability of Large Language Models
Alessandro Raganato, Rafael Peñaloza, Marco Viviani +1
Large Language Models (LLMs) have shown remarkable capabilities in manipulating natural language across multiple applications, but their ability to handle simple reasoning tasks is…
Investigating Task Arithmetic for Zero-Shot Information Retrieval
Marco Braga, Pranav Kasela, Alessandro Raganato +1
Large Language Models (LLMs) have shown impressive zero-shot performance across a variety of Natural Language Processing tasks, including document re-ranking. However, their effect…
SemEval-2025 Task 3: Mu-SHROOM, the Multilingual Shared Task on Hallucinations and Related Observable Overgeneration Mistakes
Raúl Vázquez, Timothee Mickus, Elaine Zosa +15
We present the Mu-SHROOM shared task which is focused on detecting hallucinations and other overgeneration mistakes in the output of instruction-tuned large language models (LLMs).…
Synthetic Data Generation with Large Language Models for Personalized Community Question Answering
Marco Braga, Pranav Kasela, Alessandro Raganato +1
Personalization in Information Retrieval (IR) is a topic studied by the research community since a long time. However, there is still a lack of datasets to conduct large-scale eval…
How to Blend Concepts in Diffusion Models
Lorenzo Olearo, Giorgio Longari, Simone Melzi +2
For the last decade, there has been a push to use multi-dimensional (latent) spaces to represent concepts; and yet how to manipulate these concepts or reason with them remains larg…
SemEval-2024 Shared Task 6: SHROOM, a Shared-task on Hallucinations and Related Observable Overgeneration Mistakes
Timothee Mickus, Elaine Zosa, Raúl Vázquez +5
This paper presents the results of the SHROOM, a shared task focused on detecting hallucinations: outputs from natural language generation (NLG) systems that are fluent, yet inaccu…