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

Showing 17011750 of 10817 papers

TitleStatusHype
Can AI-Generated Text be Reliably Detected?Code1
OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of GeneralizationCode1
Distilling Knowledge from Reader to Retriever for Question AnsweringCode1
Diversify Question Generation with Retrieval-Augmented Style TransferCode1
Dual-Key Multimodal Backdoors for Visual Question AnsweringCode1
Overview of the MEDIQA 2019 Shared Task on Textual Inference, Question Entailment and Question AnsweringCode1
Can ChatGPT Understand Too? A Comparative Study on ChatGPT and Fine-tuned BERTCode1
PAKTON: A Multi-Agent Framework for Question Answering in Long Legal AgreementsCode1
Efficiently Tuned Parameters are Task EmbeddingsCode1
DisentQA: Disentangling Parametric and Contextual Knowledge with Counterfactual Question AnsweringCode1
Disentangling 3D Prototypical Networks For Few-Shot Concept LearningCode1
PanGu-α: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel ComputationCode1
Pano-AVQA: Grounded Audio-Visual Question Answering on 360^ VideosCode1
PAQ: 65 Million Probably-Asked Questions and What You Can Do With ThemCode1
Can Explanations Be Useful for Calibrating Black Box Models?Code1
Parallel Context Windows for Large Language ModelsCode1
Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question AnsweringCode1
Discovering Spatio-Temporal Rationales for Video Question AnsweringCode1
Distantly-Supervised Dense Retrieval Enables Open-Domain Question Answering without Evidence AnnotationCode1
Why So Gullible? Enhancing the Robustness of Retrieval-Augmented Models against Counterfactual NoiseCode1
PathVQA: 30000+ Questions for Medical Visual Question AnsweringCode1
A Survey of Medical Vision-and-Language Applications and Their TechniquesCode1
CARE: Collaborative AI-Assisted Reading EnvironmentCode1
Can Language Models Solve Graph Problems in Natural Language?Code1
Discourse Analysis via Questions and Answers: Parsing Dependency Structures of Questions Under DiscussionCode1
Distantly-Supervised Evidence Retrieval Enables Question Answering without Evidence AnnotationCode1
Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning StrategiesCode1
DialSim: A Real-Time Simulator for Evaluating Long-Term Multi-Party Dialogue Understanding of Conversational AgentsCode1
Differentiable Reasoning on Large Knowledge Bases and Natural LanguageCode1
Can LLM Generate Culturally Relevant Commonsense QA Data? Case Study in Indonesian and SundaneseCode1
AI2-THOR: An Interactive 3D Environment for Visual AICode1
Phrase Retrieval Learns Passage Retrieval, TooCode1
Can LMs Learn New Entities from Descriptions? Challenges in Propagating Injected KnowledgeCode1
Physics of Language Models: Part 3.1, Knowledge Storage and ExtractionCode1
DialogLM: Pre-trained Model for Long Dialogue Understanding and SummarizationCode1
Can NLI Models Verify QA Systems' Predictions?Code1
Can NLI Models Verify QA Systems’ Predictions?Code1
Dialog Inpainting: Turning Documents into DialogsCode1
Development and bilingual evaluation of Japanese medical large language model within reasonably low computational resourcesCode1
Can Pre-trained Vision and Language Models Answer Visual Information-Seeking Questions?Code1
Detecting Hate Speech in Multi-modal MemesCode1
Point and Ask: Incorporating Pointing into Visual Question AnsweringCode1
DeVLBert: Learning Deconfounded Visio-Linguistic RepresentationsCode1
Detecting and Preventing Hallucinations in Large Vision Language ModelsCode1
Can questions summarize a corpus? Using question generation for characterizing COVID-19 researchCode1
Can Retriever-Augmented Language Models Reason? The Blame Game Between the Retriever and the Language ModelCode1
DEXTER: A Benchmark for open-domain Complex Question Answering using LLMsCode1
Direct Evaluation of Chain-of-Thought in Multi-hop Reasoning with Knowledge GraphsCode1
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighterCode1
Dense Hierarchical Retrieval for Open-Domain Question AnsweringCode1
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Benchmark Results

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