1 citations · 4 across the 11 of their papers we have counts for
12 papers
ReTraceQA: Evaluating Reasoning Traces of Small Language Models in Commonsense Question Answering
Francesco Maria Molfese, Luca Moroni, Ciro Porcaro +2
While Small Language Models (SLMs) have demonstrated promising performance on an increasingly wide array of commonsense reasoning benchmarks, current evaluation practices rely almo…
AgREE: Agentic Reasoning for Knowledge Graph Completion on Emerging Entities
Ruochen Zhao, Simone Conia, Eric Peng +2
Open-domain Knowledge Graph Completion (KGC) faces significant challenges in an ever-changing world, especially when considering the continual emergence of new entities in daily ne…
Right Answer, Wrong Score: Uncovering the Inconsistencies of LLM Evaluation in Multiple-Choice Question Answering
Francesco Maria Molfese, Luca Moroni, Luca Gioffré +3
One of the most widely used tasks for evaluating Large Language Models (LLMs) is Multiple-Choice Question Answering (MCQA). While open-ended question answering tasks are more chall…
KG-TRICK: Unifying Textual and Relational Information Completion of Knowledge for Multilingual Knowledge Graphs
Zelin Zhou, Simone Conia, Daniel Lee +6
Multilingual knowledge graphs (KGs) provide high-quality relational and textual information for various NLP applications, but they are often incomplete, especially in non-English l…
Towards Cross-Cultural Machine Translation with Retrieval-Augmented Generation from Multilingual Knowledge Graphs
Simone Conia, Daniel Lee, Min Li +3
Translating text that contains entity names is a challenging task, as cultural-related references can vary significantly across languages. These variations may also be caused by tr…
ZEBRA: Zero-Shot Example-Based Retrieval Augmentation for Commonsense Question Answering
Francesco Maria Molfese, Simone Conia, Riccardo Orlando +1
Current Large Language Models (LLMs) have shown strong reasoning capabilities in commonsense question answering benchmarks, but the process underlying their success remains largely…
Do Large Language Models Have an English Accent? Evaluating and Improving the Naturalness of Multilingual LLMs
Yanzhu Guo, Simone Conia, Zelin Zhou +3
Current Large Language Models (LLMs) are predominantly designed with English as the primary language, and even the few that are multilingual tend to exhibit strong English-centric…
Increasing Coverage and Precision of Textual Information in Multilingual Knowledge Graphs
Simone Conia, Min Li, Daniel Lee +3
Recent work in Natural Language Processing and Computer Vision has been using textual information -- e.g., entity names and descriptions -- available in knowledge graphs to ground…
Exploring Non-Verbal Predicates in Semantic Role Labeling: Challenges and Opportunities
Riccardo Orlando, Simone Conia, Roberto Navigli
Although we have witnessed impressive progress in Semantic Role Labeling (SRL), most of the research in the area is carried out assuming that the majority of predicates are verbs.…
Echoes from Alexandria: A Large Resource for Multilingual Book Summarization
Alessandro Scirè, Simone Conia, Simone Ciciliano +1
In recent years, research in text summarization has mainly focused on the news domain, where texts are typically short and have strong layout features. The task of full-book summar…
Semantic Role Labeling Meets Definition Modeling: Using Natural Language to Describe Predicate-Argument Structures
Simone Conia, Edoardo Barba, Alessandro Scirè +1
One of the common traits of past and present approaches for Semantic Role Labeling (SRL) is that they rely upon discrete labels drawn from a predefined linguistic inventory to clas…
Entity Disambiguation with Entity Definitions
Luigi Procopio, Simone Conia, Edoardo Barba +1
Local models have recently attained astounding performances in Entity Disambiguation (ED), with generative and extractive formulations being the most promising research directions.…