Hyperspherical Variational Auto-Encoders. - Tim R. Davidson; Luca Falorsi; Nicola De Cao; Thomas Kipf; Jakub M. Tomczak (UAI, 2018)

MolGAN: An implicit generative model for small molecular graphs. - Nicola De Cao; Thomas Kipf (CoRR, 2018)

Explorations in Homeomorphic Variational Auto-Encoding. - Luca Falorsi; Pim de Haan; Tim R. Davidson; Nicola De Cao; Maurice Weiler; Patrick Forré; Taco S. Cohen (CoRR, 2018)

Question Answering by Reasoning Across Documents with Graph Convolutional Networks. - Nicola De Cao; Wilker Aziz; Ivan Titov 001 (NAACL-HLT (1), 2019)

Block Neural Autoregressive Flow. - Nicola De Cao; Wilker Aziz; Ivan Titov 001 (UAI, 2019)

How do Decisions Emerge across Layers in Neural Models? Interpretation with Differentiable Masking. - Nicola De Cao; Michael Sejr Schlichtkrull; Wilker Aziz; Ivan Titov 001 (EMNLP (1), 2020)

NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned. - Sewon Min; Jordan L. Boyd-Graber; Chris Alberti; Danqi Chen 001; Eunsol Choi; Michael Collins 001; Kelvin Guu; Hannaneh Hajishirzi; Kenton Lee; Jennimaria Palomaki; Colin Raffel; Adam Roberts; et al. (NeurIPS (Competition and Demos), 2020)

The Power Spherical distribution. - Nicola De Cao; Wilker Aziz (CoRR, 2020)

KILT: a Benchmark for Knowledge Intensive Language Tasks. - Fabio Petroni; Aleksandra Piktus; Angela Fan; Patrick Lewis 001; Majid Yazdani; Nicola De Cao; James Thorne; Yacine Jernite; Vassilis Plachouras; Tim Rocktäschel; Sebastian Riedel 001 (CoRR, 2020)

A Memory Efficient Baseline for Open Domain Question Answering. - Gautier Izacard; Fabio Petroni; Lucas Hosseini; Nicola De Cao; Sebastian Riedel 001; Edouard Grave (CoRR, 2020)

Editing Factual Knowledge in Language Models. - Nicola De Cao; Wilker Aziz; Ivan Titov 001 (EMNLP (1), 2021)

Highly Parallel Autoregressive Entity Linking with Discriminative Correction. - Nicola De Cao; Wilker Aziz; Ivan Titov 001 (EMNLP (1), 2021)

Autoregressive Entity Retrieval. - Nicola De Cao; Gautier Izacard; Sebastian Riedel 001; Fabio Petroni (ICLR, 2021)

Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking. - Michael Sejr Schlichtkrull; Nicola De Cao; Ivan Titov 001 (ICLR, 2021)

KILT: a Benchmark for Knowledge Intensive Language Tasks. - Fabio Petroni; Aleksandra Piktus; Angela Fan; Patrick Lewis 001; Majid Yazdani; Nicola De Cao; James Thorne; Yacine Jernite; Vladimir Karpukhin; Jean Maillard; Vassilis Plachouras; Tim Rocktäschel; et al. (NAACL-HLT, 2021)

GenIE: Generative Information Extraction. - Martin Josifoski; Nicola De Cao; Maxime Peyrard; Robert West 001 (CoRR, 2021)

Sparse Interventions in Language Models with Differentiable Masking. - Nicola De Cao; Leon Schmid; Dieuwke Hupkes; Ivan Titov 001 (BlackboxNLP@EMNLP, 2022)

GenIE: Generative Information Extraction. - Martin Josifoski; Nicola De Cao; Maxime Peyrard; Fabio Petroni; Robert West 001 (NAACL-HLT, 2022)

Multilingual Autoregressive Entity Linking. - Nicola De Cao; Ledell Wu; Kashyap Popat; Mikel Artetxe; Naman Goyal 001; Mikhail Plekhanov; Luke Zettlemoyer; Nicola Cancedda; Sebastian Riedel 001; Fabio Petroni (Trans. Assoc. Comput. Linguistics, 2022)

Learning to Plan and Generate Text with Citations. - Constanza Fierro; Reinald Kim Amplayo; Fantine Huot; Nicola De Cao; Joshua Maynez; Shashi Narayan; Mirella Lapata (ACL (1), 2024)

Querying Large Language Models with SQL. - Mohammed Saeed 002; Nicola De Cao; Paolo Papotti (EDBT, 2024)