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 8001–8050 of 10817 papers

TitleStatusHype
Real Life Application of a Question Answering System Using BERT Language Model—0
FQuAD2.0: French Question Answering and knowing that you know nothing—0
Assisting Scene Graph Generation with Self-Supervision—0
Assessment of Answers: Online Subjective Examination—0
FQuAD: French Question Answering Dataset—0
Goal-Oriented Semantic Communication for Wireless Visual Question Answering—0
Real-World Deployment and Evaluation of Kwame for Science, An AI Teaching Assistant for Science Education in West Africa—0
Complex Factoid Question Answering with a Free-Text Knowledge Graph—0
Goal-Oriented Multi-Task BERT-Based Dialogue State Tracker—0
Complete Chess Games Enable LLM Become A Chess Master—0
A Dataset for Arabic Textual Entailment—0
Reimagining Retrieval Augmented Language Models for Answering Queries—0
ReasonBert: Pre-trained to Reason with Distant Supervision—0
ReasonChainQA: Text-based Complex Question Answering with Explainable Evidence Chains—0
GNN is a Counter? Revisiting GNN for Question Answering—0
Assessing Users' Reputation from Syntactic and Semantic Information in Community Question Answering—0
Reasoning and Tools for Human-Level Forecasting—0
Reasoning Chain Based Adversarial Attack for Multi-hop Question Answering—0
Reasoning Court: Combining Reasoning, Action, and Judgment for Multi-Hop Reasoning—0
Reasoning-Driven Question-Answering for Natural Language Understanding—0
Reasoning Elicitation in Language Models via Counterfactual Feedback—0
Reasoning in Conversation: Solving Subjective Tasks through Dialogue Simulation for Large Language Models—0
GMSA: Enhancing Context Compression via Group Merging and Layer Semantic Alignment—0
Reasoning Like Program Executors—0
Framework for Question-Answering in Sanskrit through Automated Construction of Knowledge Graphs—0
Complementary Evidence Identification in Open-Domain Question Answering—0
AmazUtah_NLP at SemEval-2024 Task 9: A MultiChoice Question Answering System for Commonsense Defying Reasoning—0
MMLU-SR: A Benchmark for Stress-Testing Reasoning Capability of Large Language Models—0
Framing QA as Building and Ranking Intersentence Answer Justifications—0
Competence-based Question Generation—0
Reasoning over Hierarchical Question Decomposition Tree for Explainable Question Answering—0
Reasoning Over History: Context Aware Visual Dialog—0
Reasoning over Hybrid Chain for Table-and-Text Open Domain Question Answering—0
Reasoning over Hybrid Chain for Table-and-Text Open Domain QA—0
Reasoning over Logically Interacted Conditions for Question Answering—0
GLUECoS: An Evaluation Benchmark for Code-Switched NLP—0
Reasoning Over Virtual Knowledge Bases With Open Predicate Relations—0
Reasoning over Vision and Language: Exploring the Benefits of Supplemental Knowledge—0
GLUECoS : An Evaluation Benchmark for Code-Switched NLP—0
A Comprehensive Comparison of Machine Learning Based Methods Used in Bengali Question Classification—0
Reasoning with Large Language Models, a Survey—0
Assessing the Verifiability of Attributions in News Text—0
Comparing Word Representations for Implicit Discourse Relation Classification—0
REFIND: Retrieval-Augmented Factuality Hallucination Detection in Large Language Models—0
GlossBoot: Bootstrapping Multilingual Domain Glossaries from the Web—0
RECALL: A Benchmark for LLMs Robustness against External Counterfactual Knowledge—0
Comparing Recurrent and Convolutional Architectures for English-Hindi Neural Machine Translation—0
Assessing the Robustness of Visual Question Answering Models—0
Recent Advances in Deep Learning Based Dialogue Systems: A Systematic Survey—0
REFINE on Scarce Data: Retrieval Enhancement through Fine-Tuning via Model Fusion of Embedding Models—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