Search Results for author: Vittorio Castelli

Found 16 papers, 1 papers with code

Towards Robust Neural Retrieval Models with Synthetic Pre-Training

no code implementations15 Apr 2021 Revanth Gangi Reddy, Vikas Yadav, Md Arafat Sultan, Martin Franz, Vittorio Castelli, Heng Ji, Avirup Sil

Recent work has shown that commonly available machine reading comprehension (MRC) datasets can be used to train high-performance neural information retrieval (IR) systems.

Information Retrieval Machine Reading Comprehension

End-to-End QA on COVID-19: Domain Adaptation with Synthetic Training

no code implementations2 Dec 2020 Revanth Gangi Reddy, Bhavani Iyer, Md Arafat Sultan, Rong Zhang, Avi Sil, Vittorio Castelli, Radu Florian, Salim Roukos

End-to-end question answering (QA) requires both information retrieval (IR) over a large document collection and machine reading comprehension (MRC) on the retrieved passages.

Domain Adaptation Information Retrieval +2

Scalable Cross-lingual Treebank Synthesis for Improved Production Dependency Parsers

no code implementations COLING 2020 Yousef El-Kurdi, Hiroshi Kanayama, Efsun Sarioglu Kayi, Vittorio Castelli, Todd Ward, Radu Florian

We present scalable Universal Dependency (UD) treebank synthesis techniques that exploit advances in language representation modeling which leverage vast amounts of unlabeled general-purpose multilingual text.

Data Augmentation

Improved Synthetic Training for Reading Comprehension

no code implementations24 Oct 2020 Yanda Chen, Md Arafat Sultan, Vittorio Castelli

Automatically generated synthetic training examples have been shown to improve performance in machine reading comprehension (MRC).

Knowledge Distillation Machine Reading Comprehension

Cross-Task Knowledge Transfer for Query-Based Text Summarization

no code implementations WS 2019 Elozino Egonmwan, Vittorio Castelli, Md. Arafat Sultan

We demonstrate the viability of knowledge transfer between two related tasks: machine reading comprehension (MRC) and query-based text summarization.

Machine Reading Comprehension Machine Translation +3

CFO: A Framework for Building Production NLP Systems

no code implementations IJCNLP 2019 Rishav Chakravarti, Cezar Pendus, Andrzej Sakrajda, Anthony Ferritto, Lin Pan, Michael Glass, Vittorio Castelli, J. William Murdock, Radu Florian, Salim Roukos, Avirup Sil

This paper introduces a novel orchestration framework, called CFO (COMPUTATION FLOW ORCHESTRATOR), for building, experimenting with, and deploying interactive NLP (Natural Language Processing) and IR (Information Retrieval) systems to production environments.

Information Retrieval Machine Reading Comprehension +1

A Joint Model for Answer Sentence Ranking and Answer Extraction

no code implementations TACL 2016 Md. Arafat Sultan, Vittorio Castelli, Radu Florian

Answer sentence ranking and answer extraction are two key challenges in question answering that have traditionally been treated in isolation, i. e., as independent tasks.

Information Retrieval Question Answering +1

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