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 10751–10800 of 10817 papers

TitleStatusHype
Türkçe Dil Modellerinin Performans Karşılaştırması Performance Comparison of Turkish Language Models—0
Turkish Paraphrase Corpus—0
TVBench: Redesigning Video-Language Evaluation—0
TV-TREES: Multimodal Entailment Trees for Neuro-Symbolic Video Reasoning—0
TWEETQA: A Social Media Focused Question Answering Dataset—0
TwiRGCN: Temporally Weighted Graph Convolution for Question Answering over Temporal Knowledge Graphs—0
Twitter Named Entity Extraction and Linking Using Differential Evolution—0
Twitter Paraphrase Identification with Simple Overlap Features and SVMs—0
Two can play this Game: Visual Dialog with Discriminative Question Generation and Answering—0
Two is Better Than One: Answering Complex Questions by Multiple Knowledge Sources with Generalized Links—0
Two-Layer Retrieval-Augmented Generation Framework for Low-Resource Medical Question Answering Using Reddit Data: Proof-of-Concept Study—0
Two-stage Generative Question Answering on Temporal Knowledge Graph Using Large Language Models—0
Two-Turn Debate Doesn't Help Humans Answer Hard Reading Comprehension Questions—0
TxT: Crossmodal End-to-End Learning with Transformers—0
Type-Constrained Representation Learning in Knowledge Graphs—0
Type-dependent Prompt CycleQAG : Cycle Consistency for Multi-hop Question Generation—0
Type Prediction Systems—0
Typhoon: Thai Large Language Models—0
Typologie des questions \`a r\'eponses multiples pour un syst\`eme de question-r\'eponse (Typology of Multiple Answer Questions for a Question-answering System) [in French]—0
UBY - A Large-Scale Unified Lexical-Semantic Resource Based on LMF—0
UC2: Universal Cross-lingual Cross-modal Vision-and-Language Pre-training—0
U-CAM: Visual Explanation using Uncertainty based Class Activation Maps—0
UCCIX: Irish-eXcellence Large Language Model—0
SearchLVLMs: A Plug-and-Play Framework for Augmenting Large Vision-Language Models by Searching Up-to-Date Internet Knowledge—0
UFO: A UniFied TransfOrmer for Vision-Language Representation Learning—0
UFRGSent at SemEval-2022 Task 10: Structured Sentiment Analysis using a Question Answering Model—0
UHop: An Unrestricted-Hop Relation Extraction Framework for Knowledge-Based Question Answering—0
UH-PRHLT at SemEval-2016 Task 3: Combining Lexical and Semantic-based Features for Community Question Answering—0
Uhura: A Benchmark for Evaluating Scientific Question Answering and Truthfulness in Low-Resource African Languages—0
UINSUSKA-TiTech at SemEval-2017 Task 3: Exploiting Word Importance Levels for Similarity Features for CQA—0
UIT-E10dot3 at SemEval-2021 Task 5: Toxic Spans Detection with Named Entity Recognition and Question-Answering Approaches—0
UIT-Saviors at MEDVQA-GI 2023: Improving Multimodal Learning with Image Enhancement for Gastrointestinal Visual Question Answering—0
UKP: Computing Semantic Textual Similarity by Combining Multiple Content Similarity Measures—0
UMB@PerAnsSumm 2025: Enhancing Perspective-Aware Summarization with Prompt Optimization and Supervised Fine-Tuning—0
UMCC\_DLSI-(EPS): Paraphrases Detection Based on Semantic Distance—0
UMCC\_DLSI: Multidimensional Lexical-Semantic Textual Similarity—0
UMCC\_DLSI: Textual Similarity based on Lexical-Semantic features—0
UMD-TTIC-UW at SemEval-2016 Task 1: Attention-Based Multi-Perspective Convolutional Neural Networks for Textual Similarity Measurement—0
UMichigan: A Conditional Random Field Model for Resolving the Scope of Negation—0
UMLS-KGI-BERT: Data-Centric Knowledge Integration in Transformers for Biomedical Entity Recognition—0
Um novo corpo e os seus desafios (A new corpus and the challenges it offers)—0
Unanimous Prediction for 100\% Precision with Application to Learning Semantic Mappings—0
Unanswerable Questions about Images and Texts—0
UNCC Biomedical Semantic Question Answering Systems. BioASQ: Task-7B, Phase-B—0
UNCC QA: Biomedical Question Answering system—0
Uncertainty-Aware Attention Heads: Efficient Unsupervised Uncertainty Quantification for LLMs—0
Uncertainty-Aware Fusion: An Ensemble Framework for Mitigating Hallucinations in Large Language Models—0
Uncertainty-aware Language Modeling for Selective Question Answering—0
Uncertainty-Based Abstention in LLMs Improves Safety and Reduces Hallucinations—0
Uncertainty based Class Activation Maps for Visual Question Answering—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