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 5251–5275 of 10817 papers

TitleStatusHype
Bridging Speech and Textual Pre-trained Models with Unsupervised ASR—0
Empowering Language Models with Active Inquiry for Deeper Understanding—0
Bridging Question Answering and Discourse The case of Multi-Sentence Questions—0
Answering while Summarizing: Multi-task Learning for Multi-hop QA with Evidence Extraction—0
Employing Text Matching Network to Recognise Nuclearity in Chinese Discourse—0
Empirical Study on Deep Learning Models for Question Answering—0
Bridging Information-Seeking Human Gaze and Machine Reading Comprehension—0
Answering Visual What-If Questions: From Actions to Predicted Scene Descriptions—0
AGQA 2.0: An Updated Benchmark for Compositional Spatio-Temporal Reasoning—0
Empirical Risk Minimization for Probabilistic Grammars: Sample Complexity and Hardness of Learning—0
Empirical Methods for the Study of Denotation in Nominalizations in Spanish—0
Bridging Context Gaps: Leveraging Coreference Resolution for Long Contextual Understanding—0
Empirically-motivated Generalizations of CCG Semantic Parsing Learning Algorithms—0
60 Data Points are Sufficient to Fine-Tune LLMs for Question-Answering—0
Answering Unseen Questions With Smaller Language Models Using Rationale Generation and Dense Retrieval—0
Emotion Classification of COVID-19 Chinese Microblogs based on the Emotion Category Description—0
Emotion-Cause Pair Extraction as Question Answering—0
EmoAssist: Emotional Assistant for Visual Impairment Community—0
Bridge to Answer: Structure-aware Graph Interaction Network for Video Question Answering—0
Answering Unanswered Questions through Semantic Reformulations in Spoken QA—0
A Glimpse in ChatGPT Capabilities and its impact for AI research—0
A criterion for Artificial General Intelligence: hypothetic-deductive reasoning, tested on ChatGPT—0
Emily: Developing An Emotion-affective Open-Domain Chatbot with Knowledge Graph-based Persona—0
Emerging Pixel Grounding in Large Multimodal Models Without Grounding Supervision—0
Bridge the Gap between Language models and Tabular Understanding—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