Papers by Davide Bacciu

3 papers
JuriFindIT: an Italian legal retrieval dataset (2026.findings-eacl)

Copied to clipboard

Challenge: Statutory article retrieval (SAR) targets retrieval of legislative provisions relevant to a natural language question.
Approach: They propose a pipeline that integrates dense encoders with an heterogeneous legislative graph . they propose statutory article retrieval (SAR) is the first SAR dataset for the italian legal domain .
Outcome: The proposed pipeline improves over existing approaches.
Learning from Non-Binary Constituency Trees via Tensor Decomposition (2020.coling-main)

Copied to clipboard

Challenge: a binarisation procedure changes the structure of constituency trees, furthering constituents that are not binary.
Approach: They propose a binarised approach to binarise constituency trees by tensor-based models . they propose 'trunk-LSTM' model which exploits such a rich structure .
Outcome: The proposed model performs well on different NLP tasks.
Self-generated Replay Memories for Continual Neural Machine Translation (2024.naacl-long)

Copied to clipboard

Challenge: Neural Machine Translation systems exhibit strong performance in several different languages, but their ability to learn continuously is limited by catastrophic forgetting.
Approach: They propose a method that leverages a key property of encoder-decoder Transformers, i.e. their generative ability, to continuously learn Neural Machine Translation systems.
Outcome: The proposed approach can counteract catastrophic forgetting without explicit memorization of training data.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations