b'Radu Florian'

research

∙ 05/26/2023

Slide, Constrain, Parse, Repeat: Synchronous SlidingWindows for Document AMR Parsing

The sliding window approach provides an elegant way to handle contexts o...

0 Sadhana Kumaravel, et al. ∙

research

∙ 04/24/2023

AMR Parsing with Instruction Fine-tuned Pre-trained Language Models

Instruction fine-tuned language models on a collection of instruction an...

0 Young-suk Lee, et al. ∙

research

∙ 03/01/2023

UDAPDR: Unsupervised Domain Adaptation via LLM Prompting and Distillation of Rerankers

Many information retrieval tasks require large labeled datasets for fine...

0 Jon Saad-Falcon, et al. ∙

research

∙ 01/23/2023

PrimeQA: The Prime Repository for State-of-the-Art Multilingual Question Answering Research and Development

The field of Question Answering (QA) has made remarkable progress in rec...

0 Avirup Sil, et al. ∙

research

∙ 12/02/2022

Moving Beyond Downstream Task Accuracy for Information Retrieval Benchmarking

Neural information retrieval (IR) systems have progressed rapidly in rec...

0 Keshav Santhanam, et al. ∙

research

∙ 06/16/2022

GAAMA 2.0: An Integrated System that Answers Boolean and Extractive Questions

Recent machine reading comprehension datasets include extractive and boo...

0 Scott McCarley, et al. ∙

research

∙ 05/15/2022

Not to Overfit or Underfit? A Study of Domain Generalization in Question Answering

Machine learning models are prone to overfitting their source (training)...

0 Md Arafat Sultan, et al. ∙

research

∙ 05/03/2022

Inducing and Using Alignments for Transition-based AMR Parsing

Transition-based parsers for Abstract Meaning Representation (AMR) rely ...

2 Andrew Drozdov, et al. ∙

research

∙ 04/20/2022

Synthetic Target Domain Supervision for Open Retrieval QA

Neural passage retrieval is a new and promising approach in open retriev...

0 Revanth Gangi Reddy, et al. ∙

research

∙ 02/26/2022

A Generative Model for Relation Extraction and Classification

Relation extraction (RE) is an important information extraction task whi...

0 Jian Ni, et al. ∙

research

∙ 12/15/2021

DocAMR: Multi-Sentence AMR Representation and Evaluation

Despite extensive research on parsing of English sentences into Abstract...

0 Tahira Naseem, et al. ∙

research

∙ 12/15/2021

Learning to Transpile AMR into SPARQL

We propose a transition-based system to transpile Abstract Meaning Repre...

8 Mihaela Bornea, et al. ∙

research

∙ 12/14/2021

Maximum Bayes Smatch Ensemble Distillation for AMR Parsing

AMR parsing has experienced an unprecendented increase in performance in...

0 Young-suk Lee, et al. ∙

research

∙ 12/14/2021

Do Answers to Boolean Questions Need Explanations? Yes

Existing datasets that contain boolean questions, such as BoolQ and TYDI...

0 Sara Rosenthal, et al. ∙

research

∙ 10/29/2021

Structure-aware Fine-tuning of Sequence-to-sequence Transformers for Transition-based AMR Parsing

Predicting linearized Abstract Meaning Representation (AMR) graphs using...

0 Jiawei Zhou, et al. ∙

research

∙ 05/07/2021

VAULT: VAriable Unified Long Text Representation for Machine Reading Comprehension

Existing models on Machine Reading Comprehension (MRC) require complex m...

0 Haoyang Wen, et al. ∙

research

∙ 04/29/2021

AMR Parsing with Action-Pointer Transformer

Abstract Meaning Representation parsing is a sentence-to-graph predictio...

0 Jiawei Zhou, et al. ∙

research

∙ 02/03/2021

Bootstrapping Multilingual AMR with Contextual Word Alignments

We develop high performance multilingualAbstract Meaning Representation ...

0 Janaki Sheth, et al. ∙

research

∙ 12/10/2020

Multilingual Transfer Learning for QA Using Translation as Data Augmentation

Prior work on multilingual question answering has mostly focused on usin...

0 Mihaela Bornea, et al. ∙

research

∙ 12/02/2020

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

End-to-end question answering (QA) requires both information retrieval (...

0 Revanth Gangi Reddy, et al. ∙

research

∙ 10/20/2020

Pushing the Limits of AMR Parsing with Self-Learning

Abstract Meaning Representation (AMR) parsing has experienced a notable ...

0 Young-suk Lee, et al. ∙

research

∙ 10/20/2020

Transition-based Parsing with Stack-Transformers

Modeling the parser state is key to good performance in transition-based...

0 Ramón Fernandez Astudillo, et al. ∙

research

∙ 10/16/2020

Cross-Lingual Relation Extraction with Transformers

Relation extraction (RE) is one of the most important tasks in informati...

0 Jian Ni, et al. ∙

research

∙ 10/12/2020

Multi-Stage Pre-training for Low-Resource Domain Adaptation

Transfer learning techniques are particularly useful in NLP tasks where ...

0 Rong Zhang, et al. ∙

research

∙ 09/15/2020

Cascaded Models for Better Fine-Grained Named Entity Recognition

Named Entity Recognition (NER) is an essential precursor task for many n...

0 Parul Awasthy, et al. ∙

research

∙ 09/15/2020

Event Presence Prediction Helps Trigger Detection Across Languages

The task of event detection and classification is central to most inform...

0 Parul Awasthy, et al. ∙

research

∙ 05/18/2020

GPT-too: A language-model-first approach for AMR-to-text generation

Abstract Meaning Representations (AMRs) are broad-coverage sentence-leve...

0 Manuel Mager, et al. ∙

research

∙ 11/19/2019

Towards Lingua Franca Named Entity Recognition with BERT

Information extraction is an important task in NLP, enabling the automat...

0 Taesun Moon, et al. ∙

research

∙ 11/08/2019

The TechQA Dataset

We introduce TechQA, a domain-adaptation question answering dataset for ...

0 Vittorio Castelli, et al. ∙

research

∙ 10/31/2019

Neural Cross-Lingual Relation Extraction Based on Bilingual Word Embedding Mapping

Relation extraction (RE) seeks to detect and classify semantic relations...

0 Jian Ni, et al. ∙

research

∙ 10/30/2019

Ensembling Strategies for Answering Natural Questions

Many of the top question answering systems today utilize ensembling to i...

0 Anthony Ferritto, et al. ∙

research

∙ 09/11/2019

Frustratingly Easy Natural Question Answering

Existing literature on Question Answering (QA) mostly focuses on algorit...

0 Lin Pan, et al. ∙

research

∙ 08/16/2019

CFO: A Framework for Building Production NLP Systems

This paper introduces a novel orchestration framework, called CFO (COMPU...

0 Rishav Chakravarti, et al. ∙

research

∙ 05/31/2019

Rewarding Smatch: Transition-Based AMR Parsing with Reinforcement Learning

Our work involves enriching the Stack-LSTM transition-based AMR parser (...

0 Tahira Naseem, et al. ∙

research

∙ 09/06/2018

Exploring Graph-structured Passage Representation for Multi-hop Reading Comprehension with Graph Neural Networks

Multi-hop reading comprehension focuses on one type of factoid question,...

0 Linfeng Song, et al. ∙

research

∙ 06/26/2018

Neural Cross-Lingual Coreference Resolution and its Application to Entity Linking

We propose an entity-centric neural cross-lingual coreference model that...

0 Gourab Kundu, et al. ∙

research

∙ 12/05/2017

Neural Cross-Lingual Entity Linking

A major challenge in Entity Linking (EL) is making effective use of cont...

0 Avirup Sil, et al. ∙

research

∙ 12/05/2017

One for All: Towards Language Independent Named Entity Linking

Entity linking (EL) is the task of disambiguating mentions in text by as...

0 Avirup Sil, et al. ∙

research

∙ 07/08/2017

Weakly Supervised Cross-Lingual Named Entity Recognition via Effective Annotation and Representation Projection

The state-of-the-art named entity recognition (NER) systems are supervis...

0 Jian Ni, et al. ∙

research

∙ 07/08/2017

Improving Multilingual Named Entity Recognition with Wikipedia Entity Type Mapping

The state-of-the-art named entity recognition (NER) systems are statisti...

0 Jian Ni, et al. ∙

research

∙ 07/04/2017

Improving Slot Filling Performance with Attentive Neural Networks on Dependency Structures

Slot Filling (SF) aims to extract the values of certain types of attribu...

0 Lifu Huang, et al. ∙

research

∙ 03/13/2017

Reinforcement Learning for Transition-Based Mention Detection

This paper describes an application of reinforcement learning to the men...

0 Georgiana Dinu, et al. ∙

research

∙ 02/13/2017

Bilateral Multi-Perspective Matching for Natural Language Sentences

Natural language sentence matching is a fundamental technology for a var...

0 Zhiguo Wang, et al. ∙

research

∙ 12/13/2016

Multi-Perspective Context Matching for Machine Comprehension

Previous machine comprehension (MC) datasets are either too small to tra...

0 Zhiguo Wang, et al. ∙

research

∙ 06/24/2016

A Sentence Compression Based Framework to Query-Focused Multi-Document Summarization

We consider the problem of using sentence compression techniques to faci...

0 Lu Wang, et al. ∙

research

∙ 02/24/2016

Toward Mention Detection Robustness with Recurrent Neural Networks

One of the key challenges in natural language processing (NLP) is to yie...

0 Thien Huu Nguyen, et al. ∙

Radu Florian

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