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 4501–4525 of 10817 papers

TitleStatusHype
Self-Improvement Programming for Temporal Knowledge Graph Question Answering—0
Stable Code Technical Report—0
Unveiling Divergent Inductive Biases of LLMs on Temporal DataCode0
Detect2Interact: Localizing Object Key Field in Visual Question Answering (VQA) with LLMs—0
Learning by Correction: Efficient Tuning Task for Zero-Shot Generative Vision-Language ReasoningCode0
VideoDistill: Language-aware Vision Distillation for Video Question Answering—0
Explainable Multi-hop Question Generation: An End-to-End Approach without Intermediate Question LabelingCode0
Small Language Models Learn Enhanced Reasoning Skills from Medical Textbooks—0
DOCMASTER: A Unified Platform for Annotation, Training, & Inference in Document Question-Answering—0
Design as Desired: Utilizing Visual Question Answering for Multimodal Pre-trainingCode0
How Robust are the Tabular QA Models for Scientific Tables? A Study using Customized DatasetCode0
Multi-hop Question Answering under Temporal Knowledge Editing—0
MANGO: A Benchmark for Evaluating Mapping and Navigation Abilities of Large Language ModelsCode0
Uncovering Bias in Large Vision-Language Models with Counterfactuals—0
Are Large Language Models Good at Utility Judgments?Code0
Leveraging Expert Input for Robust and Explainable AI-Assisted Lung Cancer Detection in Chest X-rays—0
EthioMT: Parallel Corpus for Low-resource Ethiopian Languages—0
MFORT-QA: Multi-hop Few-shot Open Rich Table Question Answering—0
Reshaping Free-Text Radiology Notes Into Structured Reports With Generative TransformersCode0
Boosting Conversational Question Answering with Fine-Grained Retrieval-Augmentation and Self-Check—0
mALBERT: Is a Compact Multilingual BERT Model Still Worth It?—0
Chain-of-Action: Faithful and Multimodal Question Answering through Large Language ModelsCode0
Can multiple-choice questions really be useful in detecting the abilities of LLMs?Code0
Intrinsic Subgraph Generation for Interpretable Graph based Visual Question AnsweringCode0
A Gaze-grounded Visual Question Answering Dataset for Clarifying Ambiguous Japanese Questions—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