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 3101–3125 of 10817 papers

TitleStatusHype
VISREAS: Complex Visual Reasoning with Unanswerable Questions—0
Evaluating the Performance of ChatGPT for Spam Email Detection—0
ArabianGPT: Native Arabic GPT-based Large Language Model—0
Faithful Temporal Question Answering over Heterogeneous Sources—0
Biomedical Entity Linking as Multiple Choice Question AnsweringCode0
Interactive-KBQA: Multi-Turn Interactions for Knowledge Base Question Answering with Large Language ModelsCode1
Multimodal Transformer With a Low-Computational-Cost Guarantee—0
Cost-Adaptive Recourse Recommendation by Adaptive Preference Elicitation—0
SIMPLOT: Enhancing Chart Question Answering by Distilling EssentialsCode1
Leveraging Large Language Models for Concept Graph Recovery and Question Answering in NLP EducationCode1
CommVQA: Situating Visual Question Answering in Communicative ContextsCode0
Word-Sequence Entropy: Towards Uncertainty Estimation in Free-Form Medical Question Answering Applications and Beyond—0
Uncertainty-Aware Evaluation for Vision-Language ModelsCode1
Triad: A Framework Leveraging a Multi-Role LLM-based Agent to Solve Knowledge Base Question AnsweringCode1
Do LLMs Implicitly Determine the Suitable Text Difficulty for Users?Code0
Does the Generator Mind its Contexts? An Analysis of Generative Model Faithfulness under Context Transfer—0
Visual Hallucinations of Multi-modal Large Language ModelsCode1
Data Science with LLMs and Interpretable ModelsCode2
FanOutQA: A Multi-Hop, Multi-Document Question Answering Benchmark for Large Language ModelsCode2
ActiveRAG: Autonomously Knowledge Assimilation and Accommodation through Retrieval-Augmented AgentsCode2
RefuteBench: Evaluating Refuting Instruction-Following for Large Language ModelsCode0
Retrieval Helps or Hurts? A Deeper Dive into the Efficacy of Retrieval Augmentation to Language ModelsCode0
PQA: Zero-shot Protein Question Answering for Free-form Scientific Enquiry with Large Language ModelsCode0
Towards Building Multilingual Language Model for MedicineCode3
Self-DC: When to Reason and When to Act? Self Divide-and-Conquer for Compositional Unknown 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