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 5851–5900 of 10817 papers

TitleStatusHype
WeCheck: Strong Factual Consistency Checker via Weakly Supervised LearningCode0
To Adapt or to Annotate: Challenges and Interventions for Domain Adaptation in Open-Domain Question Answering—0
MULTI3NLU++: A Multilingual, Multi-Intent, Multi-Domain Dataset for Natural Language Understanding in Task-Oriented Dialogue—0
SLUE Phase-2: A Benchmark Suite of Diverse Spoken Language Understanding Tasks—0
Defending Against Disinformation Attacks in Open-Domain Question AnsweringCode0
On-the-fly Denoising for Data Augmentation in Natural Language UnderstandingCode0
Rethinking Label Smoothing on Multi-hop Question AnsweringCode0
Query Enhanced Knowledge-Intensive Conversation via Unsupervised Joint ModelingCode0
KNIFE: Distilling Reasoning Knowledge From Free-Text Rationales—0
Medical Knowledge Graph QA for Drug-Drug Interaction Prediction based on Multi-hop Machine Reading Comprehension—0
MetaCLUE: Towards Comprehensive Visual Metaphors Research—0
Tokenization Consistency Matters for Generative Models on Extractive NLP TasksCode0
Source-Free Domain Adaptation for Question Answering with Masked Self-trainingCode0
Task Preferences across Languages on Community Question Answering Platforms—0
PolQA: Polish Question Answering Dataset—0
Towards leveraging latent knowledge and Dialogue context for real-world conversational question answering—0
AugTriever: Unsupervised Dense Retrieval and Domain Adaptation by Scalable Data AugmentationCode0
SceneGATE: Scene-Graph based co-Attention networks for TExt visual question answering—0
Natural Language Processing in Customer Service: A Systematic Review—0
Plansformer: Generating Symbolic Plans using Transformers—0
CLAM: Selective Clarification for Ambiguous Questions with Generative Language Models—0
FiDO: Fusion-in-Decoder optimized for stronger performance and faster inference—0
Best-Answer Prediction in Q&A Sites Using User Information—0
CLIPPO: Image-and-Language Understanding from Pixels Only—0
Multi-VALUE: A Framework for Cross-Dialectal English NLP—0
Build-a-Bot: Teaching Conversational AI Using a Transformer-Based Intent Recognition and Question Answering Architecture—0
Despite "super-human" performance, current LLMs are unsuited for decisions about ethics and safety—0
Attentive Deep Neural Networks for Legal Document Retrieval—0
BigText-QA: Question Answering over a Large-Scale Hybrid Knowledge Graph—0
Momentum Contrastive Pre-training for Question Answering—0
Improving Generalization of Pre-trained Language Models via Stochastic Weight Averaging—0
MORTY: Structured Summarization for Targeted Information Extraction from Scholarly Articles—0
REVEAL: Retrieval-Augmented Visual-Language Pre-Training with Multi-Source Multimodal Knowledge MemoryCode0
From Cloze to Comprehension: Retrofitting Pre-trained Masked Language Model to Pre-trained Machine ReaderCode0
VideoCoCa: Video-Text Modeling with Zero-Shot Transfer from Contrastive Captioners—0
The Turing Deception—0
Successive Prompting for Decomposing Complex Questions—0
Learning Action-Effect Dynamics for Hypothetical Vision-Language Reasoning TaskCode0
ParsVQA-Caps: A Benchmark for Visual Question Answering and Image Captioning in Persian—0
Analysis of Drug repurposing Knowledge graphs for Covid-19—0
Dataset vs Reality: Understanding Model Performance from the Perspective of Information Need—0
Intent Recognition in Conversational Recommender Systems—0
QBERT: Generalist Model for Processing Questions—0
Applying Multilingual Models to Question Answering (QA)—0
Query-Driven Knowledge Base Completion using Multimodal Path Fusion over Multimodal Knowledge Graph—0
Toward Efficient Language Model Pretraining and Downstream Adaptation via Self-Evolution: A Case Study on SuperGLUE—0
Utilizing Background Knowledge for Robust Reasoning over Traffic SituationsCode0
Visual Question Answering From Another Perspective: CLEVR Mental Rotation TestsCode0
Fuse and Adapt: Investigating the Use of Pre-Trained Self-Supervising Learning Models in Limited Data NLU problems—0
Compound Tokens: Channel Fusion for Vision-Language Representation Learning—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