activity
20162024
collaborators

6 papers

cs.AI2024

Speechworthy Instruction-tuned Language Models

Hyundong Cho, Nicolaas Jedema, Leonardo F. R. Ribeiro +5

Current instruction-tuned language models are exclusively trained with textual preference data and thus are often not aligned with the unique requirements of other modalities, such…

cs.CL2023

SQUARE: Automatic Question Answering Evaluation using Multiple Positive and Negative References

Matteo Gabburo, Siddhant Garg, Rik Koncel Kedziorski +1

Evaluation of QA systems is very challenging and expensive, with the most reliable approach being human annotations of correctness of answers for questions. Recent works (AVA, BEM)…

cs.CL2023

Context-Aware Transformer Pre-Training for Answer Sentence Selection

Luca Di Liello, Siddhant Garg, Alessandro Moschitti

Answer Sentence Selection (AS2) is a core component for building an accurate Question Answering pipeline. AS2 models rank a set of candidate sentences based on how likely they answ…

cs.CL2023

Learning Answer Generation using Supervision from Automatic Question Answering Evaluators

Matteo Gabburo, Siddhant Garg, Rik Koncel-Kedziorski +1

Recent studies show that sentence-level extractive QA, i.e., based on Answer Sentence Selection (AS2), is outperformed by Generation-based QA (GenQA) models, which generate answers…

cs.CL2023

QUADRo: Dataset and Models for QUestion-Answer Database Retrieval

Stefano Campese, Ivano Lauriola, Alessandro Moschitti

An effective paradigm for building Automated Question Answering systems is the re-use of previously answered questions, e.g., for FAQs or forum applications. Given a database (DB)…

cs.CL2016

Addressing Community Question Answering in English and Arabic

Giovanni Da San Martino, Alberto Barrón-Cedeño, Salvatore Romeo +5

This paper studies the impact of different types of features applied to learning to re-rank questions in community Question Answering. We tested our models on two datasets released…