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 4851–4900 of 10817 papers

TitleStatusHype
RMLVQA: A Margin Loss Approach for Visual Question Answering With Language Biases—0
Discovering the Real Association: Multimodal Causal Reasoning in Video Question Answering—0
Image as a Foreign Language: BEiT Pretraining for Vision and Vision-Language Tasks—0
Context-Aware Alignment and Mutual Masking for 3D-Language Pre-TrainingCode1
VQACL: A Novel Visual Question Answering Continual Learning SettingCode1
Rethinking with Retrieval: Faithful Large Language Model InferenceCode1
GPTR: Gestalt-Perception Transformer for Diagram Object Detection—0
Hungry Hungry Hippos: Towards Language Modeling with State Space ModelsCode2
Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLPCode7
A Survey on Table-and-Text HybridQA: Concepts, Methods, Challenges and Future Directions—0
TextBox 2.0: A Text Generation Library with Pre-trained Language ModelsCode3
Large Language Models Encode Clinical KnowledgeCode1
Improving Complex Knowledge Base Question Answering via Question-to-Action and Question-to-Question AlignmentCode0
STRUDEL: Structured Dialogue Summarization for Dialogue Comprehension—0
OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of GeneralizationCode1
When are Lemons Purple? The Concept Association Bias of Vision-Language Models—0
From Images to Textual Prompts: Zero-shot VQA with Frozen Large Language ModelsCode0
Parallel Context Windows for Large Language ModelsCode1
UnICLAM:Contrastive Representation Learning with Adversarial Masking for Unified and Interpretable Medical Vision Question Answering—0
Analyzing Semantic Faithfulness of Language Models via Input Intervention on Question AnsweringCode0
ZEROTOP: Zero-Shot Task-Oriented Semantic Parsing using Large Language Models—0
Language models are better than humans at next-token predictionCode0
Towards Unsupervised Visual Reasoning: Do Off-The-Shelf Features Know How to Reason?—0
Optimization Techniques for Unsupervised Complex Table Reasoning via Self-Training FrameworkCode1
Extrinsic Evaluation of Machine Translation Metrics—0
To Adapt or to Annotate: Challenges and Interventions for Domain Adaptation in Open-Domain Question Answering—0
Are Deep Neural Networks SMARTer than Second Graders?Code1
WeCheck: Strong Factual Consistency Checker via Weakly Supervised LearningCode0
Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step QuestionsCode2
Defending Against Disinformation Attacks in Open-Domain Question AnsweringCode0
On-the-fly Denoising for Data Augmentation in Natural Language UnderstandingCode0
SLUE Phase-2: A Benchmark Suite of Diverse Spoken Language Understanding Tasks—0
MULTI3NLU++: A Multilingual, Multi-Intent, Multi-Domain Dataset for Natural Language Understanding in Task-Oriented Dialogue—0
(QA)^2: Question Answering with Questionable AssumptionsCode0
Source-Free Domain Adaptation for Question Answering with Masked Self-trainingCode0
Evaluating Human-Language Model InteractionCode1
MetaCLUE: Towards Comprehensive Visual Metaphors Research—0
Rethinking Label Smoothing on Multi-hop Question AnsweringCode0
Query Enhanced Knowledge-Intensive Conversation via Unsupervised Joint ModelingCode0
Tokenization Consistency Matters for Generative Models on Extractive NLP TasksCode0
Medical Knowledge Graph QA for Drug-Drug Interaction Prediction based on Multi-hop Machine Reading Comprehension—0
Visconde: Multi-document QA with GPT-3 and Neural RerankingCode1
Don't Generate, Discriminate: A Proposal for Grounding Language Models to Real-World EnvironmentsCode1
KNIFE: Distilling Reasoning Knowledge From Free-Text Rationales—0
MIST: Multi-modal Iterative Spatial-Temporal Transformer for Long-form Video Question AnsweringCode1
Can Retriever-Augmented Language Models Reason? The Blame Game Between the Retriever and the Language ModelCode1
Task Preferences across Languages on Community Question Answering Platforms—0
Towards leveraging latent knowledge and Dialogue context for real-world conversational question answering—0
PolQA: Polish Question Answering Dataset—0
AugTriever: Unsupervised Dense Retrieval and Domain Adaptation by Scalable Data AugmentationCode0
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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