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 5026–5050 of 10817 papers

TitleStatusHype
Dialogizer: Context-aware Conversational-QA Dataset Generation from Textual Sources—0
Hallucination-minimized Data-to-answer Framework for Financial Decision-makers—0
Prompt Sketching for Large Language Models—0
Zero-shot Translation of Attention Patterns in VQA Models to Natural LanguageCode0
NLQxform: A Language Model-based Question to SPARQL TransformerCode0
JPAVE: A Generation and Classification-based Model for Joint Product Attribute Prediction and Value ExtractionCode0
Leveraging Structured Information for Explainable Multi-hop Question Answering and ReasoningCode0
Adapting Pre-trained Generative Models for Extractive Question Answering—0
In-Context Learning for Knowledge Base Question Answering for Unmanned Systems based on Large Language Models—0
CoVLM: Composing Visual Entities and Relationships in Large Language Models Via Communicative Decoding—0
Tailoring Self-Rationalizers with Multi-Reward DistillationCode0
FloodBrain: Flood Disaster Reporting by Web-based Retrieval Augmented Generation with an LLM—0
ChEF: A Comprehensive Evaluation Framework for Standardized Assessment of Multimodal Large Language Models—0
AI-TA: Towards an Intelligent Question-Answer Teaching Assistant using Open-Source LLMsCode0
Causal Question Answering with Reinforcement LearningCode0
Divide & Conquer for Entailment-aware Multi-hop Evidence Retrieval—0
Perturbation-based Active Learning for Question Answering—0
Active Reasoning in an Open-World Environment—0
An Introduction to Natural Language Processing Techniques and Framework for Clinical Implementation in Radiation Oncology—0
Hint-enhanced In-Context Learning wakes Large Language Models up for knowledge-intensive tasks—0
Predicting Question-Answering Performance of Large Language Models through Semantic Consistency—0
Long Story Short: a Summarize-then-Search Method for Long Video Question AnsweringCode0
ACQUIRED: A Dataset for Answering Counterfactual Questions In Real-Life VideosCode0
Modular Blended Attention Network for Video Question Answering—0
Learn to Refuse: Making Large Language Models More Controllable and Reliable through Knowledge Scope Limitation and Refusal Mechanism—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