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 43914400 of 10817 papers

TitleStatusHype
Detecting and Resolving Shell Nouns in German0
Detecting and Evaluating Medical Hallucinations in Large Vision Language Models0
Bag of Tricks for Effective Language Model Pretraining and Downstream Adaptation: A Case Study on GLUE0
A neural document language modeling framework for spoken document retrieval0
Detect, Describe, Discriminate: Moving Beyond VQA for MLLM Evaluation0
Detect2Interact: Localizing Object Key Field in Visual Question Answering (VQA) with LLMs0
A Neural Comprehensive Ranker (NCR) for Open-Domain Question Answering0
Despite "super-human" performance, current LLMs are unsuited for decisions about ethics and safety0
Bactrainus: Optimizing Large Language Models for Multi-hop Complex Question Answering Tasks0
Adversarial Attacks Beyond the Image Space0
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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