3 citations · 14 across the 29 of their papers we have counts for
12 papers · 1 filter
Word Sense Linking: Disambiguating Outside the Sandbox
Andrei Stefan Bejgu, Edoardo Barba, Luigi Procopio +2
Word Sense Disambiguation (WSD) is the task of associating a word in a given context with its most suitable meaning among a set of possible candidates. While the task has recently…
LLMs Lost in Translation: M-ALERT uncovers Cross-Linguistic Safety Inconsistencies
Felix Friedrich, Simone Tedeschi, Patrick Schramowski +5
Building safe Large Language Models (LLMs) across multiple languages is essential in ensuring both safe access and linguistic diversity. To this end, we conduct a large-scale, comp…
Truth or Mirage? Towards End-to-End Factuality Evaluation with LLM-Oasis
Alessandro Scirè, Andrei Stefan Bejgu, Simone Tedeschi +3
After the introduction of Large Language Models (LLMs), there have been substantial improvements in the performance of Natural Language Generation (NLG) tasks, including Text Summa…
Beyond Correlation: Interpretable Evaluation of Machine Translation Metrics
Stefano Perrella, Lorenzo Proietti, Pere-Lluís Huguet Cabot +2
Machine Translation (MT) evaluation metrics assess translation quality automatically. Recently, researchers have employed MT metrics for various new use cases, such as data filteri…
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…
AutoML-guided Fusion of Entity and LLM-based Representations for Document Classification
Boshko Koloski, Senja Pollak, Roberto Navigli +1
Large semantic knowledge bases are grounded in factual knowledge. However, recent approaches to dense text representations (i.e. embeddings) do not efficiently exploit these resour…
Guardians of the Machine Translation Meta-Evaluation: Sentinel Metrics Fall In!
Stefano Perrella, Lorenzo Proietti, Alessandro Scirè +2
Annually, at the Conference of Machine Translation (WMT), the Metrics Shared Task organizers conduct the meta-evaluation of Machine Translation (MT) metrics, ranking them according…
ReLiK: Retrieve and LinK, Fast and Accurate Entity Linking and Relation Extraction on an Academic Budget
Riccardo Orlando, Pere-Lluis Huguet Cabot, Edoardo Barba +1
Entity Linking (EL) and Relation Extraction (RE) are fundamental tasks in Natural Language Processing, serving as critical components in a wide range of applications. In this paper…
Maverick: Efficient and Accurate Coreference Resolution Defying Recent Trends
Giuliano Martinelli, Edoardo Barba, Roberto Navigli
Large autoregressive generative models have emerged as the cornerstone for achieving the highest performance across several Natural Language Processing tasks. However, the urge to…
ALERT: A Comprehensive Benchmark for Assessing Large Language Models' Safety through Red Teaming
Simone Tedeschi, Felix Friedrich, Patrick Schramowski +4
When building Large Language Models (LLMs), it is paramount to bear safety in mind and protect them with guardrails. Indeed, LLMs should never generate content promoting or normali…
Aurora-M: Open Source Continual Pre-training for Multilingual Language and Code
Taishi Nakamura, Mayank Mishra, Simone Tedeschi +42
Pretrained language models are an integral part of AI applications, but their high computational cost for training limits accessibility. Initiatives such as Bloom and StarCoder aim…
FENICE: Factuality Evaluation of summarization based on Natural language Inference and Claim Extraction
Alessandro Scirè, Karim Ghonim, Roberto Navigli
Recent advancements in text summarization, particularly with the advent of Large Language Models (LLMs), have shown remarkable performance. However, a notable challenge persists as…