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 5376–5400 of 10817 papers

TitleStatusHype
CoRAG: Collaborative Retrieval-Augmented Generation—0
A Transformer Based Approach towards Identification of Discourse Unit Segments and Connectives—0
Learning to Navigate Wikipedia by Taking Random Walks—0
Implicit Relation Linking for Question Answering over Knowledge Graph—0
LaMP-QA: A Benchmark for Personalized Long-form Question Answering—0
Implicit Discourse Relation Recognition with Context-aware Character-enhanced Embeddings—0
Implicit Dimension Identification in User-Generated Text with LSTM Networks—0
Language-aware Visual Semantic Distillation for Video Question Answering—0
Language bias in Visual Question Answering: A Survey and Taxonomy—0
Language Features Matter: Effective Language Representations for Vision-Language Tasks—0
Designing dialogue systems: A mean, grumpy, sarcastic chatbot in the browser—0
Implications of Deep Circuits in Improving Quality of Quantum Question Answering—0
A Training-free LLM Framework with Interaction between Contextually Related Subtasks in Solving Complex Tasks—0
Language Independent Sentence-Level Subjectivity Analysis with Feature Selection—0
Learning to Map Natural Language Statements into Knowledge Base Representations for Knowledge Base Construction—0
Implementation Notes for the Soft Cosine Measure—0
LEMON: LanguagE ModeL for Negative Sampling of Knowledge Graph Embeddings—0
Language Model-Guided Knowledge Subgraphs for Question Answering—0
Language Model is All You Need: Natural Language Understanding as Question Answering—0
Imperfect Vision Encoders: Efficient and Robust Tuning for Vision-Language Models—0
Language Model Pre-training for Hierarchical Document Representations—0
Detect, Describe, Discriminate: Moving Beyond VQA for MLLM Evaluation—0
Language Models are Causal Knowledge Extractors for Zero-shot Video Question Answering—0
Analysis of Visual Question Answering Algorithms with attention model—0
CopyBERT: A Unified Approach to Question Generation with Self-Attention—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