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 7701–7750 of 10817 papers

TitleStatusHype
Iterative Scene Graph Generation with Generative Transformers—0
Iterative Multi-document Neural Attention for Multiple Answer Prediction—0
Iterative Adversarial Attack on Image-guided Story Ending Generation—0
Iterated learning for emergent systematicity in VQA—0
Cycle-Consistency for Robust Visual Question Answering—0
QA: from Turing Test to Intelligent Information Service—0
Automated Testing and Improvement of Named Entity Recognition Systems—0
An Effective Contextual Language Modeling Framework for Speech Summarization with Augmented Features—0
Is This Just Fantasy? Language Model Representations Reflect Human Judgments of Event Plausibility—0
"Is This It?": Towards Ecologically Valid Benchmarks for Situated Collaboration—0
CyberBOT: Towards Reliable Cybersecurity Education via Ontology-Grounded Retrieval Augmented Generation—0
Is Table Retrieval a Solved Problem? Exploring Join-Aware Multi-Table Retrieval—0
Is Summary Useful or Not? An Extrinsic Human Evaluation of Text Summaries on Downstream Tasks—0
ISS-MULT: Intelligent Sample Selection for Multi-Task Learning in Question Answering—0
Is Sluice Resolution really just Question Answering?—0
CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark—0
Automated Story Generation as Question-Answering—0
ANEC: An Amharic Named Entity Corpus and Transformer Based Recognizer—0
ARTEMIS-DA: An Advanced Reasoning and Transformation Engine for Multi-Step Insight Synthesis in Data Analytics—0
A Cognitive Ideation Support Framework using IBM Watson Services—0
Is Retriever Merely an Approximator of Reader?—0
C-VQA: A Compositional Split of the Visual Question Answering (VQA) v1.0 Dataset—0
Is Relevance Propagated from Retriever to Generator in RAG?—0
Automated Historical Fact-Checking by Passage Retrieval, Word Statistics, and Virtual Question-Answering—0
ISO-TimeML Event Extraction in Persian Text—0
IslamicPCQA: A Dataset for Persian Multi-hop Complex Question Answering in Islamic Text Resources—0
Is It Dish Washer Safe? Automatically Answering ``Yes/No'' Questions Using Customer Reviews—0
Cut to the Chase: A Context Zoom-in Network for Reading Comprehension—0
Automated Graph Generation at Sentence Level for Reading Comprehension Based on Conceptual Graphs—0
Is Graph Structure Necessary for Multi-hop Question Answering?—0
Is GPT-3 all you need for Visual Question Answering in Cultural Heritage?—0
QCRI: Answer Selection for Community Question Answering - Experiments for Arabic and English—0
IS-GGT: Iterative Scene Graph Generation With Generative Transformers—0
ISCAS\_NLP at SemEval-2016 Task 1: Sentence Similarity Based on Support Vector Regression using Multiple Features—0
Curriculum Script Distillation for Multilingual Visual Question Answering—0
Is a Video worth n n Images? A Highly Efficient Approach to Transformer-based Video Question Answering—0
Is Aligning Embedding Spaces a Challenging Task? A Study on Heterogeneous Embedding Alignment Methods—0
ISAAQ - Mastering Textbook Questions with Pre-trained Transformers and Bottom-Up and Top-Down Attention—0
QirK: Question Answering via Intermediate Representation on Knowledge Graphs—0
QIRL: Boosting Visual Question Answering via Optimized Question-Image Relation Learning—0
Curriculum Learning for Compositional Visual Reasoning—0
Curriculum Learning Effectively Improves Low Data VQA—0
Automated Factual Benchmarking for In-Car Conversational Systems using Large Language Models—0
QnAMaker: Data to Bot in 2 Minutes—0
ISAAQ -- Mastering Textbook Questions with Pre-trained Transformers and Bottom-Up and Top-Down Attention—0
IrokoBench: A New Benchmark for African Languages in the Age of Large Language Models—0
QQATeam at Qur’an QA 2022: Fine-Tunning Arabic QA Models for Qur’an QA Task—0
QRMeM: Unleash the Length Limitation through Question then Reflection Memory Mechanism—0
Q-SFT: Q-Learning for Language Models via Supervised Fine-Tuning—0
Curriculum Learning Based on Reward Sparseness for Deep Reinforcement Learning of Task Completion Dialogue Management—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