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 2276–2300 of 10817 papers

TitleStatusHype
BeamAggR: Beam Aggregation Reasoning over Multi-source Knowledge for Multi-hop Question Answering—0
STLLaVA-Med: Self-Training Large Language and Vision Assistant for Medical Question-AnsweringCode1
Follow-Up Questions Improve Documents Generated by Large Language Models—0
Changing Answer Order Can Decrease MMLU Accuracy—0
Handling Ontology Gaps in Semantic ParsingCode0
Context Matters: An Empirical Study of the Impact of Contextual Information in Temporal Question Answering Systems—0
SeaKR: Self-aware Knowledge Retrieval for Adaptive Retrieval Augmented GenerationCode1
Length Optimization in Conformal PredictionCode0
TrustUQA: A Trustful Framework for Unified Structured Data Question AnsweringCode0
Disentangling Knowledge-based and Visual Reasoning by Question Decomposition in KB-VQA—0
The Illusion of Competence: Evaluating the Effect of Explanations on Users' Mental Models of Visual Question Answering SystemsCode0
Enhancing Continual Learning in Visual Question Answering with Modality-Aware Feature DistillationCode0
FlowVQA: Mapping Multimodal Logic in Visual Question Answering with Flowcharts—0
Geode: A Zero-shot Geospatial Question-Answering Agent with Explicit Reasoning and Precise Spatio-Temporal Retrieval—0
Knowledge graph enhanced retrieval-augmented generation for failure mode and effects analysisCode1
Sanskrit Knowledge-based Systems: Annotation and Computational Tools—0
Understand What LLM Needs: Dual Preference Alignment for Retrieval-Augmented GenerationCode2
Explicit Diversity Conditions for Effective Question Answer Generation with Large Language Models—0
Evaluating Fairness in Large Vision-Language Models Across Diverse Demographic Attributes and PromptsCode0
Zero-Shot Long-Form Video Understanding through Screenplay—0
CaLMQA: Exploring culturally specific long-form question answering across 23 languagesCode0
Entropy-Based Decoding for Retrieval-Augmented Large Language ModelsCode0
Advancing Question Answering on Handwritten Documents: A State-of-the-Art Recognition-Based Model for HW-SQuAD—0
Leave No Document Behind: Benchmarking Long-Context LLMs with Extended Multi-Doc QACode2
CogMG: Collaborative Augmentation Between Large Language Model and Knowledge GraphCode1
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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