Papers Machine Reading Comprehension
“Machine Reading Comprehension” 태그가 달린 논문 562편 · 필터 해제
NorQuAD: Norwegian Question Answering Dataset
In this paper we present NorQuAD: the first Norwegian question answering dataset for machine reading comprehension. The dataset consists of 4,752 manually created question-answer pairs. We here detail the data collection…
Machine Reading ComprehensionQuestion AnsweringReading ComprehensionInformation Extraction from Documents: Question Answering vs Token Classification in real-world setups
Research in Document Intelligence and especially in Document Key Information Extraction (DocKIE) has been mainly solved as Token Classification problem. Recent breakthroughs in both natural language processing (NLP) and …
ClassificationFew-Shot LearningKey Information ExtractionMachine Reading Comprehension+5Evaluating the Robustness of Machine Reading Comprehension Models to Low Resource Entity Renaming
Question answering (QA) models have shown compelling results in the task of Machine Reading Comprehension (MRC). Recently these systems have proved to perform better than humans on held-out test sets of datasets e.g. SQu…
Machine Reading ComprehensionQuestion AnsweringReading ComprehensionMiniRBT: A Two-stage Distilled Small Chinese Pre-trained Model
In natural language processing, pre-trained language models have become essential infrastructures. However, these models often suffer from issues such as large size, long inference time, and challenging deployment. Moreo…
Machine Reading ComprehensionReading Comprehensiontext-classificationText Classification+1A Data-centric Framework for Improving Domain-specific Machine Reading Comprehension Datasets
Low-quality data can cause downstream problems in high-stakes applications. Data-centric approach emphasizes on improving dataset quality to enhance model performance. High-quality datasets are needed for general-purpose…
Machine Reading ComprehensionReading ComprehensionRetrievalA Multiple Choices Reading Comprehension Corpus for Vietnamese Language Education
Machine reading comprehension has been an interesting and challenging task in recent years, with the purpose of extracting useful information from texts. To attain the computer ability to understand the reading text and …
ArticlesMachine Reading ComprehensionMultiple-choiceNatural Language Inference+1Context-faithful Prompting for Large Language Models
Large language models (LLMs) encode parametric knowledge about world facts and have shown remarkable performance in knowledge-driven NLP tasks. However, their reliance on parametric knowledge may cause them to overlook c…
counterfactualMachine Reading ComprehensionReading ComprehensionRelation ExtractionRevealing Weaknesses of Vietnamese Language Models Through Unanswerable Questions in Machine Reading Comprehension
Although the curse of multilinguality significantly restricts the language abilities of multilingual models in monolingual settings, researchers now still have to rely on multilingual models to develop state-of-the-art s…
Machine Reading ComprehensionReading ComprehensionVietnamese Language ModelsVietnamese Machine Reading ComprehensionClinical Concept and Relation Extraction Using Prompt-based Machine Reading Comprehension
Objective: To develop a natural language processing system that solves both clinical concept extraction and relation extraction in a unified prompt-based machine reading comprehension (MRC) architecture with good general…
Clinical Concept ExtractionMachine Reading ComprehensionReading ComprehensionRelation+2LUKE-Graph: A Transformer-based Approach with Gated Relational Graph Attention for Cloze-style Reading Comprehension
Incorporating prior knowledge can improve existing pre-training models in cloze-style machine reading and has become a new trend in recent studies. Notably, most of the existing models have integrated external knowledge …
Common Sense ReasoningGraph AttentionKnowledge GraphsMachine Reading Comprehension+2Orca: A Few-shot Benchmark for Chinese Conversational Machine Reading Comprehension
The conversational machine reading comprehension (CMRC) task aims to answer questions in conversations, which has been a hot research topic in recent years because of its wide applications. However, existing CMRC benchma…
Machine Reading ComprehensionReading ComprehensionCross-Lingual Question Answering over Knowledge Base as Reading Comprehension
Although many large-scale knowledge bases (KBs) claim to contain multilingual information, their support for many non-English languages is often incomplete. This incompleteness gives birth to the task of cross-lingual qu…
Cross-Lingual Question AnsweringMachine Reading ComprehensionQuestion AnsweringReading ComprehensionNatural Response Generation for Chinese Reading Comprehension
Machine reading comprehension (MRC) is an important area of conversation agents and draws a lot of attention. However, there is a notable limitation to current MRC benchmarks: The labeled answers are mostly either spans …
Chinese Reading ComprehensionMachine Reading ComprehensionReading ComprehensionResponse GenerationThe Impacts of Unanswerable Questions on the Robustness of Machine Reading Comprehension Models
Pretrained language models have achieved super-human performances on many Machine Reading Comprehension (MRC) benchmarks. Nevertheless, their relative inability to defend against adversarial attacks has spurred skepticis…
Adversarial AttackMachine Reading ComprehensionNatural Language UnderstandingReading ComprehensionKILDST: Effective Knowledge-Integrated Learning for Dialogue State Tracking using Gazetteer and Speaker Information
Dialogue State Tracking (DST) is core research in dialogue systems and has received much attention. In addition, it is necessary to define a new problem that can deal with dialogue between users as a step toward the conv…
Dialogue State TrackingMachine Reading ComprehensionReading ComprehensionSchedulingIntegrating Semantic Information into Sketchy Reading Module of Retro-Reader for Vietnamese Machine Reading Comprehension
Machine Reading Comprehension has become one of the most advanced and popular research topics in the fields of Natural Language Processing in recent years. The classification of answerability questions is a relatively si…
Machine Reading ComprehensionReading ComprehensionVietnamese Machine Reading ComprehensionXLM-RRethinking Label Smoothing on Multi-hop Question Answering
Multi-Hop Question Answering (MHQA) is a significant area in question answering, requiring multiple reasoning components, including document retrieval, supporting sentence prediction, and answer span extraction. In this …
Image ClassificationMachine Reading ComprehensionMachine TranslationMulti-hop Question Answering+5Medical Knowledge Graph QA for Drug-Drug Interaction Prediction based on Multi-hop Machine Reading Comprehension
Drug-drug interaction prediction is a crucial issue in molecular biology. Traditional methods of observing drug-drug interactions through medical experiments require significant resources and labor. This paper presents a…
Entity EmbeddingsGraph Neural NetworkGraph Question AnsweringMachine Reading Comprehension+2Bridging The Gap: Entailment Fused-T5 for Open-retrieval Conversational Machine Reading Comprehension
Open-retrieval conversational machine reading comprehension (OCMRC) simulates real-life conversational interaction scenes. Machines are required to make a decision of "Yes/No/Inquire" or generate a follow-up question whe…
Decision MakingMachine Reading ComprehensionQuestion GenerationQuestion-Generation+2From Cloze to Comprehension: Retrofitting Pre-trained Masked Language Model to Pre-trained Machine Reader
We present Pre-trained Machine Reader (PMR), a novel method for retrofitting pre-trained masked language models (MLMs) to pre-trained machine reading comprehension (MRC) models without acquiring labeled data. PMR can res…
ClassificationExtractive Question-AnsweringLanguage ModelingLanguage Modelling+6