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 7051–7075 of 10817 papers

TitleStatusHype
One vs. Many QA Matching with both Word-level and Sentence-level Attention Network—0
On Generality and Knowledge Transferability in Cross-Domain Duplicate Question Detection for Heterogeneous Community Question Answering—0
On Generating Characteristic-rich Question Sets for QA Evaluation—0
On Incorporating Semantic Prior Knowlegde in Deep Learning Through Embedding-Space Constraints—0
On Incorporating Semantic Prior Knowledge in Deep Learning Through Embedding-Space Constraints—0
On Knowledge distillation from complex networks for response prediction—0
Online Continual Knowledge Learning for Language Models—0
Hallucination-minimized Data-to-answer Framework for Financial Decision-makers—0
On Making Reading Comprehension More Comprehensive—0
On Measuring Social Biases in Prompt-Based Learning—0
Hallucination Detection: Robustly Discerning Reliable Answers in Large Language Models—0
On Mechanistic Circuits for Extractive Question-Answering—0
On metric embedding for boosting semantic similarity computations—0
EVE: Efficient Vision-Language Pre-training with Masked Prediction and Modality-Aware MoE—0
Event analysis for information extraction from business-based technical documents—0
ConQuest: Contextual Question Paraphrasing through Answer-Aware Synthetic Question Generation—0
Optimizing open-domain question answering with graph-based retrieval augmented generation—0
On scalable oversight with weak LLMs judging strong LLMs—0
On Scaling Up a Multilingual Vision and Language Model—0
On Significance of Subword tokenization for Low Resource and Efficient Named Entity Recognition: A case study in Marathi—0
Optimizing Visual Question Answering Models for Driving: Bridging the Gap Between Human and Machine Attention Patterns—0
On the Cognition of Visual Question Answering Models and Human Intelligence: A Comparative Study—0
Event Detection via Derangement Question Answering—0
On the Distribution, Sparsity, and Inference-time Quantization of Attention Values in Transformers—0
Option Comparison Network for Multiple-choice Reading Comprehension—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