SOTAVerified

Question Answering

Question answering can be segmented into domain-specific tasks like community question answering and knowledge-base question answering. Popular benchmark datasets for evaluation question answering systems include SQuAD, HotPotQA, bAbI, TriviaQA, WikiQA, and many others. Models for question answering are typically evaluated on metrics like EM and F1. Some recent top performing models are T5 and XLNet.

( Image credit: SQuAD )

Papers

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Showing 7801–7850 of 10817 papers

TitleStatusHype
Question Answering based Clinical Text Structuring Using Pre-trained Language Model—0
Question-Answering Based Summarization of Electronic Health Records using Retrieval Augmented Generation—0
Finely Tuned, 2 Billion Token Based Word Embeddings for Portuguese—0
Component Analysis for Visual Question Answering Architectures—0
FINET: Context-Aware Fine-Grained Named Entity Typing—0
Question Answering for Complex Electronic Health Records Database using Unified Encoder-Decoder Architecture—0
ComPO: Community Preferences for Language Model Personalization—0
Question Answering for Electronic Health Records: A Scoping Review of datasets and models—0
A State-transition Framework to Answer Complex Questions over Knowledge Base—0
Question Answering from Unstructured Text by Retrieval and Comprehension—0
A Memory Model for Question Answering from Streaming Data Supported by Rehearsal and Anticipation of Coreference Information—0
R2GQA: Retriever-Reader-Generator Question Answering System to Support Students Understanding Legal Regulations in Higher Education—0
Question Answering in Natural Language: the Special Case of Temporal Expressions—0
Question Answering in the Biomedical Domain—0
GPTs and Language Barrier: A Cross-Lingual Legal QA Examination—0
Question-Answering Model for Schizophrenia Symptoms and Their Impact on Daily Life using Mental Health Forums Data—0
Finetuning Language Models to Emit Linguistic Expressions of Uncertainty—0
Question Answering on Knowledge Bases and Text using Universal Schema and Memory Networks—0
Question Answering on Linked Data: Challenges and Future Directions—0
Question Answering on Patient Medical Records with Private Fine-Tuned LLMs—0
Question Answering on Scholarly Knowledge Graphs—0
Question Answering Over Biological Knowledge Graph via Amazon Alexa—0
Question Answering over Curated and Open Web Sources—0
GPTR: Gestalt-Perception Transformer for Diagram Object Detection—0
Question Answering over Freebase via Attentive RNN with Similarity Matrix based CNN—0
Question Answering over Freebase with Multi-Column Convolutional Neural Networks—0
CompMix: A Benchmark for Heterogeneous Question Answering—0
Question Answering over Knowledge Base using Factual Memory Networks—0
Question Answering over Knowledge Base using Language Model Embeddings—0
Question Answering over Knowledge Base with Neural Attention Combining Global Knowledge Information—0
Question Answering over Knowledge Graphs via Structural Query Patterns—0
Question Answering over Knowledge Graphs with Neural Machine Translation and Entity Linking—0
Question Answering over Linked Data Using First-order Logic—0
Improving Pre-trained Language Model Fine-tuning with Noise Stability Regularization—0
Question Answering Over Spatio-Temporal Knowledge Graph—0
GPT4Video: A Unified Multimodal Large Language Model for lnstruction-Followed Understanding and Safety-Aware Generation—0
Question-Answering (QA) Model for a Personalized Learning Assistant for Arabic Language—0
Question Answering Survey: Directions, Challenges, Datasets, Evaluation Matrices—0
Fine-tuning Smaller Language Models for Question Answering over Financial Documents—0
Question-Answering System for Bangla: Fine-tuning BERT-Bangla for a Closed Domain—0
Fine-tuning Strategies for Domain Specific Question Answering under Low Annotation Budget Constraints—0
Question Answering Systems Approaches and Challenges—0
Question answering systems for health professionals at the point of care -- a systematic review—0
Question Answering System using Multiple Information Source and Open Type Answer Merge—0
Fine-tuning Transformer-based Encoder for Turkish Language Understanding Tasks—0
Question answering using deep learning in low resource Indian language Marathi—0
Question Answering Using Enhanced Lexical Semantic Models—0
Question Answering Using Hierarchical Attention on Top of BERT Features—0
Question Answering via Integer Programming over Semi-Structured Knowledge—0
GPT-4V Explorations: Mining Autonomous Driving—0
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All datasetsSQuAD2.0SQuAD1.1HotpotQAPIQABoolQCOPATriviaQASQuAD1.1 devNatural QuestionsOpenBookQATruthfulQAMultiRC

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1IE-Net (ensemble)EM90.94—Unverified
2FPNet (ensemble)EM90.87—Unverified
3IE-NetV2 (ensemble)EM90.86—Unverified
4SA-Net on Albert (ensemble)EM90.72—Unverified
5SA-Net-V2 (ensemble)EM90.68—Unverified
6FPNet (ensemble)EM90.6—Unverified
7Retro-Reader (ensemble)EM90.58—Unverified
8EntitySpanFocusV2 (ensemble)EM90.52—Unverified
9TransNets + SFVerifier + SFEnsembler (ensemble)EM90.49—Unverified
10EntitySpanFocus+AT (ensemble)EM90.45—Unverified