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Stefano Campese

3 accepted papers

2025

Analyzing and Improving Coherence of Large Language Models in Question Answering

NAACL 2025long

Large language models (LLMs) have recently revolutionized natural language processing. These models, however, often suffer from instability or lack of coherence, that is the ability of the models to generate semantically equivalent outputs when receiving diverse yet semantically equivalent input var…

Cited by 0SourcePDFScholar
2024

Datasets for Multilingual Answer Sentence Selection

EMNLP 2024finding

Answer Sentence Selection (AS2) is a critical task for designing effective retrieval-based Question Answering (QA) systems. Most advancements in AS2 focus on English due to the scarcity of annotated datasets for other languages. This lack of resources prevents the training of effective AS2 models in…

Cited by 1SourcePDFScholar
2023

QUADRo: Dataset and Models for QUestion-Answer Database Retrieval

EMNLP 2023long findings

An effective approach to design automated Question Answering (QA) systems is to efficiently retrieve answers from pre-computed databases containing question/answer pairs. One of the main challenges to this design is the lack of training/testing data. Existing resources are limited in size and topic…

Cited by 0SourceScholar