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 7751–7800 of 10817 papers

TitleStatusHype
QUACKIE: A NLP Classification Task With Ground Truth Explanations—0
QuAC : Question Answering in Context—0
QuAC: Question Answering in Context—0
QUADRo: Dataset and Models for QUestion-Answer Database Retrieval—0
QuaLA-MiniLM: a Quantized Length Adaptive MiniLM—0
Large Language Models Leverage External Knowledge to Extend Clinical Insight Beyond Language Boundaries—0
Qualitative Modeling of Spatial Prepositions and Motion Expressions—0
Finding ReMO (Related Memory Object): A Simple Neural Architecture for Text based Reasoning—0
Graph Attention with Hierarchies for Multi-hop Question Answering—0
Compositional De-Attention Networks—0
GrapeQA: GRaph Augmentation and Pruning to Enhance Question-Answering—0
Quantifying Memorization and Retriever Performance in Retrieval-Augmented Vision-Language Models—0
Compositional Attention Networks for Interpretability in Natural Language Question Answering—0
Quantifying reliance on external information over parametric knowledge during Retrieval Augmented Generation (RAG) using mechanistic analysis—0
Quantifying the Knowledge in a DNN to Explain Knowledge Distillation for Classification—0
Quantum Algorithms for Compositional Text Processing—0
Quantum Language Model with Entanglement Embedding for Question Answering—0
QuArch: A Question-Answering Dataset for AI Agents in Computer Architecture—0
Finding the Middle Ground - A Model for Planning Satisficing Answers—0
QUASER: Question Answering with Scalable Extractive Rationalization—0
AstBERT: Enabling Language Model for Financial Code Understanding with Abstract Syntax Trees—0
QU-BIGIR at SemEval 2017 Task 3: Using Similarity Features for Arabic Community Question Answering Forums—0
Find The Gap: Knowledge Base Reasoning For Visual Question Answering—0
Grammatical structures for word-level sentiment detection—0
Grammarless Parsing for Joint Inference—0
Find the word that does not belong: A Framework for an Intrinsic Evaluation of Word Vector Representations—0
Query Expansion for Cross-Language Question Re-Ranking—0
Query expansion techniques for information retrieval: A survey—0
Grammar Detection for Sentiment Analysis through Improved Viterbi Algorithm—0
Compositional and Lexical Semantics in RoBERTa, BERT and DistilBERT: A Case Study on CoQA—0
Query Focused Multi-Document Summarization with Distant Supervision—0
Fine-Grained Discourse Structures in Continuation Semantics—0
A Statistical Framework for Data-dependent Retrieval-Augmented Models—0
Query pipeline optimization for cancer patient question answering systems—0
CLAM: Selective Clarification for Ambiguous Questions with Generative Language Models—0
Query Refinement Prompts for Closed-Book Long-Form Question Answering—0
Question-Context Alignment and Answer-Context Dependencies for Effective Answer Sentence Selection—0
Question Generation for Question Answering—0
Grammar-aware sentence classification on quantum computers—0
Question Analysis for Arabic Question Answering Systems—0
GRAM: Global Reasoning for Multi-Page VQA—0
Composite Semantic Relation Classification—0
GRAF: Graph Retrieval Augmented by Facts for Romanian Legal Multi-Choice Question Answering—0
Composing Ensembles of Pre-trained Models via Iterative Consensus—0
A statistical approach for Non-Sentential Utterance Resolution for Interactive QA System—0
Question Answering and Question Generation for Finnish—0
Question Answering and Question Generation as Dual Tasks—0
Fine-Grained Retrieval-Augmented Generation for Visual Question Answering—0
Fine-grained Semantic Textual Similarity for Serbian—0
Gradient-guided Attention Map Editing: Towards Efficient Contextual Hallucination Mitigation—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