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 5901–5950 of 10817 papers

TitleStatusHype
DUAL: Textless Spoken Question Answering with Speech Discrete Unit Adaptive Learning—0
Logical Story Representations via FrameNet + Semantic Parsing—0
Divide and Conquer: Text Semantic Matching with Disentangled Keywords and Intents—0
Learning to Transpile AMR into SPARQL—0
Disaggregating Hops: Can We Guide a Multi-Hop Reasoning Language Model to Incrementally Learn at each Hop?—0
Bayesian Deep Learning for Interactive Community Question Answering—0
An Encoder Attribution Analysis for Dense Passage Retriever in Open-Domain Question Answering—0
MetaICL: Learning to Learn In Context—0
Task Formulation Matters When Learning Continuously: A Case Study in Visual Question Answering—0
Knowledge Base Index Compression via Dimensionality and Precision Reduction—0
StoryQA: Story Grounded Question Answering Dataset—0
JointLK: Joint Reasoning with Language Models and Knowledge Graphs for Commonsense Question Answering—0
Data Augmentation for Biomedical Factoid Question Answering—0
Re2G: Retrieve, Rerank, Generate—0
A Two-Stage Approach towards Generalization in Knowledge Base Question Answering—0
MANGO: Enhancing the Robustness of VQA Models via Adversarial Noise Generation—0
Incorporating Question Answering-Based Signals into Abstractive Summarization via Salient Span Selection—0
Improving Data Augmentation in Low-resource Question Answering with Active Learning in Multiple Stages—0
Mining Information from Event Structure Relation Graph for Event Argument Extraction—0
Improved and Efficient Conversational Slot Labeling through Question Answering—0
Cooperative Self-training of Machine Reading Comprehension—0
Probing the Role of Positional Information in Vision-Language Models—0
Context-guided Triple Matching for Multiple Choice Question Answering—0
CONQRR: Conversational Query Rewriting for Retrieval with Reinforcement Learning—0
ProQA: Structural Prompt-based Pre-training for Unified Question Answering—0
Retrieving Visual Facts For Few-Shot Visual Question Answering—0
QAFactEval: Improved QA-Based Factual Consistency Evaluation for Summarization—0
UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language ModelsCode2
Double Retrieval and Ranking for Accurate Question Answering—0
In Situ Answer Sentence Selection at Web-scale—0
Natural Language Deduction through Search over Statement Compositions—0
Ensemble Transformer for Efficient and Accurate Ranking Tasks: an Application to Question Answering SystemsCode0
Reasoning over Hybrid Chain for Table-and-Text Open Domain QA—0
Kformer: Knowledge Injection in Transformer Feed-Forward LayersCode1
CLIP-TD: CLIP Targeted Distillation for Vision-Language Tasks—0
A Benchmark for Generalizable and Interpretable Temporal Question Answering over Knowledge BasesCode0
Sequence-to-Sequence Models for Extracting Information from Registration and Legal DocumentsCode1
A Thousand Words Are Worth More Than a Picture: Natural Language-Centric Outside-Knowledge Visual Question Answering—0
Towards Automated Error Analysis: Learning to Characterize Errors—0
Grow-and-Clip: Informative-yet-Concise Evidence Distillation for Answer Explanation—0
On the Efficacy of Co-Attention Transformer Layers in Visual Question Answering—0
Uni-EDEN: Universal Encoder-Decoder Network by Multi-Granular Vision-Language Pre-training—0
SCROLLS: Standardized CompaRison Over Long Language SequencesCode1
COIN: Counterfactual Image Generation for VQA Interpretation—0
Extraction of Product Specifications from the Web -- Going Beyond Tables and Lists—0
Development of an Extractive Clinical Question Answering Dataset with Multi-Answer and Multi-Focus Questions—0
Does Entity Abstraction Help Generative Transformers Reason?—0
Multi Document Reading Comprehension—0
Interactive Attention AI to translate low light photos to captions for night scene understanding in women safety—0
V-Doc: Visual Questions Answers With Documents—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