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

Showing 576600 of 10817 papers

TitleStatusHype
MatTools: Benchmarking Large Language Models for Materials Science ToolsCode1
EgoTextVQA: Towards Egocentric Scene-Text Aware Video Question AnsweringCode1
Carpe Diem: On the Evaluation of World Knowledge in Lifelong Language ModelsCode1
CARE: Collaborative AI-Assisted Reading EnvironmentCode1
Efficiently Tuned Parameters are Task EmbeddingsCode1
Capturing Row and Column Semantics in Transformer Based Question Answering over TablesCode1
Adaptive Information Seeking for Open-Domain Question AnsweringCode1
Beyond NED: Fast and Effective Search Space Reduction for Complex Question Answering over Knowledge BasesCode1
Effective Human-AI Teams via Learned Natural Language Rules and OnboardingCode1
Structure-aware Domain Knowledge Injection for Large Language ModelsCode1
Ranked Voting based Self-Consistency of Large Language ModelsCode1
Educational Question Generation of Children Storybooks via Question Type Distribution Learning and Event-Centric SummarizationCode1
Efficient and Reproducible Biomedical Question Answering using Retrieval Augmented GenerationCode1
EgoToM: Benchmarking Theory of Mind Reasoning from Egocentric VideosCode1
Can Retriever-Augmented Language Models Reason? The Blame Game Between the Retriever and the Language ModelCode1
AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-TuningCode1
Can't Remember Details in Long Documents? You Need Some R&RCode1
Adapting Pretrained Text-to-Text Models for Long Text SequencesCode1
EgoThink: Evaluating First-Person Perspective Thinking Capability of Vision-Language ModelsCode1
Can questions summarize a corpus? Using question generation for characterizing COVID-19 researchCode1
Can Question Rewriting Help Conversational Question Answering?Code1
ECBench: Can Multi-modal Foundation Models Understand the Egocentric World? A Holistic Embodied Cognition BenchmarkCode1
Can NLI Models Verify QA Systems’ Predictions?Code1
Benchmarking Multimodal Mathematical Reasoning with Explicit Visual DependencyCode1
Can Pre-trained Vision and Language Models Answer Visual Information-Seeking Questions?Code1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1IE-Net (ensemble)EM90.94Unverified
2FPNet (ensemble)EM90.87Unverified
3IE-NetV2 (ensemble)EM90.86Unverified
4SA-Net on Albert (ensemble)EM90.72Unverified
5SA-Net-V2 (ensemble)EM90.68Unverified
6FPNet (ensemble)EM90.6Unverified
7Retro-Reader (ensemble)EM90.58Unverified
8EntitySpanFocusV2 (ensemble)EM90.52Unverified
9TransNets + SFVerifier + SFEnsembler (ensemble)EM90.49Unverified
10EntitySpanFocus+AT (ensemble)EM90.45Unverified