Nicola De Cao

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 34

Top Topics

Gaussian Markov Random Field

Question Answering

Top Venues

Publications

Mohammed Saeed, Nicola De Cao, Paolo Papotti
Querying Large Language Models with SQL. EDBT (2024)
Constanza Fierro, Reinald Kim Amplayo, Fantine Huot, Nicola De Cao, Joshua Maynez, Shashi Narayan, Mirella Lapata
Learning to Plan and Generate Text with Citations. CoRR (2024)
Constanza Fierro, Reinald Kim Amplayo, Fantine Huot, Nicola De Cao, Joshua Maynez, Shashi Narayan, Mirella Lapata
Learning to Plan and Generate Text with Citations. ACL (1) (2024)
Mohammed Saeed, Nicola De Cao, Paolo Papotti
Querying Large Language Models with SQL. CoRR (2023)
Nicola De Cao, Ledell Wu, Kashyap Popat, Mikel Artetxe, Naman Goyal, Mikhail Plekhanov, Luke Zettlemoyer, Nicola Cancedda, Sebastian Riedel, Fabio Petroni
Multilingual Autoregressive Entity Linking. Trans. Assoc. Comput. Linguistics 10 (2022)
Martin Josifoski, Nicola De Cao, Maxime Peyrard, Fabio Petroni, Robert West
GenIE: Generative Information Extraction. NAACL-HLT (2022)
Nicola De Cao, Leon Schmid, Dieuwke Hupkes, Ivan Titov
Sparse Interventions in Language Models with Differentiable Masking. BlackboxNLP@EMNLP (2022)
Martin Josifoski, Nicola De Cao, Maxime Peyrard, Robert West
GenIE: Generative Information Extraction. CoRR (2021)
Nicola De Cao, Wilker Aziz, Ivan Titov
Editing Factual Knowledge in Language Models. CoRR (2021)
Michael Sejr Schlichtkrull, Nicola De Cao, Ivan Titov
Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking. ICLR (2021)
Nicola De Cao, Wilker Aziz, Ivan Titov
Editing Factual Knowledge in Language Models. EMNLP (1) (2021)
Nicola De Cao, Gautier Izacard, Sebastian Riedel, Fabio Petroni
Autoregressive Entity Retrieval. ICLR (2021)
Nicola De Cao, Wilker Aziz, Ivan Titov
Highly Parallel Autoregressive Entity Linking with Discriminative Correction. CoRR (2021)
Nicola De Cao, Ledell Wu, Kashyap Popat, Mikel Artetxe, Naman Goyal, Mikhail Plekhanov, Luke Zettlemoyer, Nicola Cancedda, Sebastian Riedel, Fabio Petroni
Multilingual Autoregressive Entity Linking. CoRR (2021)
Nicola De Cao, Leon Schmid, Dieuwke Hupkes, Ivan Titov
Sparse Interventions in Language Models with Differentiable Masking. CoRR (2021)
Sewon Min, Jordan L. Boyd-Graber, Chris Alberti, Danqi Chen, Eunsol Choi, Michael Collins, Kelvin Guu, Hannaneh Hajishirzi, Kenton Lee, Jennimaria Palomaki, Colin Raffel, Adam Roberts, Tom Kwiatkowski, Patrick S. H. Lewis, Yuxiang Wu, Heinrich Küttler, Linqing Liu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel, Sohee Yang, Minjoon Seo, Gautier Izacard, Fabio Petroni, Lucas Hosseini, Nicola De Cao, Edouard Grave, Ikuya Yamada, Sonse Shimaoka, Masatoshi Suzuki, Shumpei Miyawaki, Shun Sato, Ryo Takahashi, Jun Suzuki, Martin Fajcik, Martin Docekal, Karel Ondrej, Pavel Smrz, Hao Cheng, Yelong Shen, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Barlas Oguz, Xilun Chen, Vladimir Karpukhin, Stan Peshterliev, Dmytro Okhonko, Michael Sejr Schlichtkrull, Sonal Gupta, Yashar Mehdad, Wen-tau Yih
NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned. CoRR (2021)
Nicola De Cao, Wilker Aziz, Ivan Titov
Highly Parallel Autoregressive Entity Linking with Discriminative Correction. EMNLP (1) (2021)
Fabio Petroni, Aleksandra Piktus, Angela Fan, Patrick S. H. Lewis, Majid Yazdani, Nicola De Cao, James Thorne, Yacine Jernite, Vladimir Karpukhin, Jean Maillard, Vassilis Plachouras, Tim Rocktäschel, Sebastian Riedel
KILT: a Benchmark for Knowledge Intensive Language Tasks. NAACL-HLT (2021)
Nicola De Cao, Michael Sejr Schlichtkrull, Wilker Aziz, Ivan Titov
How do Decisions Emerge across Layers in Neural Models? Interpretation with Differentiable Masking. CoRR (2020)
Fabio Petroni, Aleksandra Piktus, Angela Fan, Patrick S. H. Lewis, Majid Yazdani, Nicola De Cao, James Thorne, Yacine Jernite, Vassilis Plachouras, Tim Rocktäschel, Sebastian Riedel
KILT: a Benchmark for Knowledge Intensive Language Tasks. CoRR (2020)
Michael Sejr Schlichtkrull, Nicola De Cao, Ivan Titov
Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking. CoRR (2020)
Gautier Izacard, Fabio Petroni, Lucas Hosseini, Nicola De Cao, Sebastian Riedel, Edouard Grave
A Memory Efficient Baseline for Open Domain Question Answering. CoRR (2020)
Sewon Min, Jordan L. Boyd-Graber, Chris Alberti, Danqi Chen, Eunsol Choi, Michael Collins, Kelvin Guu, Hannaneh Hajishirzi, Kenton Lee, Jennimaria Palomaki, Colin Raffel, Adam Roberts, Tom Kwiatkowski, Patrick S. H. Lewis, Yuxiang Wu, Heinrich Küttler, Linqing Liu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel, Sohee Yang, Minjoon Seo, Gautier Izacard, Fabio Petroni, Lucas Hosseini, Nicola De Cao, Edouard Grave, Ikuya Yamada, Sonse Shimaoka, Masatoshi Suzuki, Shumpei Miyawaki, Shun Sato, Ryo Takahashi, Jun Suzuki, Martin Fajcik, Martin Docekal, Karel Ondrej, Pavel Smrz, Hao Cheng, Yelong Shen, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Barlas Oguz, Xilun Chen, Vladimir Karpukhin, Stan Peshterliev, Dmytro Okhonko, Michael Sejr Schlichtkrull, Sonal Gupta, Yashar Mehdad, Wen-tau Yih
NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned. NeurIPS (Competition and Demos) (2020)
Nicola De Cao, Michael Sejr Schlichtkrull, Wilker Aziz, Ivan Titov
How do Decisions Emerge across Layers in Neural Models? Interpretation with Differentiable Masking. EMNLP (1) (2020)
Nicola De Cao, Gautier Izacard, Sebastian Riedel, Fabio Petroni
Autoregressive Entity Retrieval. CoRR (2020)
Nicola De Cao, Wilker Aziz
The Power Spherical distribution. CoRR (2020)
Nicola De Cao, Wilker Aziz, Ivan Titov
Block Neural Autoregressive Flow. UAI (2019)
Nicola De Cao, Wilker Aziz, Ivan Titov
Question Answering by Reasoning Across Documents with Graph Convolutional Networks. NAACL-HLT (1) (2019)
Nicola De Cao, Ivan Titov, Wilker Aziz
Block Neural Autoregressive Flow. CoRR (2019)
Tim R. Davidson, Luca Falorsi, Nicola De Cao, Thomas Kipf, Jakub M. Tomczak
Hyperspherical Variational Auto-Encoders. CoRR (2018)
Tim R. Davidson, Luca Falorsi, Nicola De Cao, Thomas Kipf, Jakub M. Tomczak
Hyperspherical Variational Auto-Encoders. UAI (2018)
Nicola De Cao, Thomas Kipf
MolGAN: An implicit generative model for small molecular graphs. CoRR (2018)
Nicola De Cao, Wilker Aziz, Ivan Titov
Question Answering by Reasoning Across Documents with Graph Convolutional Networks. CoRR (2018)
Luca Falorsi, Pim de Haan, Tim R. Davidson, Nicola De Cao, Maurice Weiler, Patrick Forré, Taco S. Cohen
Explorations in Homeomorphic Variational Auto-Encoding. CoRR (2018)