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 4076–4100 of 10817 papers

TitleStatusHype
Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance—0
Does the "most sinfully decadent cake ever" taste good? Answering Yes/No Questions from Figurative Contexts—0
Frustratingly Easy Model Ensemble for Abstractive Summarization—0
Better Early than Late: Fusing Topics with Word Embeddings for Neural Question Paraphrase Identification—0
Frustratingly Hard Evidence Retrieval for QA Over Books—0
Does the Generator Mind its Contexts? An Analysis of Generative Model Faithfulness under Context Transfer—0
Does Synthetic Data Generation of LLMs Help Clinical Text Mining?—0
Better Distractions: Transformer-based Distractor Generation and Multiple Choice Question Filtering—0
Full-Time Supervision based Bidirectional RNN for Factoid Question Answering—0
CoCo-BERT: Improving Video-Language Pre-training with Contrastive Cross-modal Matching and Denoising—0
Asking Too Much? The Rhetorical Role of Questions in Political Discourse—0
Annotate and Identify Modalities, Speech Acts and Finer-Grained Event Types in Chinese Text—0
Functorial Language Games for Question Answering—0
Does Similarity Matter? The Case of Answer Extraction from Technical Discussion Forums—0
FuRongWang at SemEval-2017 Task 3: Deep Neural Networks for Selecting Relevant Answers in Community Question Answering—0
Furthest Reasoning with Plan Assessment: Stable Reasoning Path with Retrieval-Augmented Large Language Models—0
Fuse and Adapt: Investigating the Use of Pre-Trained Self-Supervising Learning Models in Limited Data NLU problems—0
Best Response Shaping—0
Affective Visual Dialog: A Large-Scale Benchmark for Emotional Reasoning Based on Visually Grounded Conversations—0
Does QA-based intermediate training help fine-tuning language models for text classification?—0
Does Object Grounding Really Reduce Hallucination of Large Vision-Language Models?—0
BESTMVQA: A Benchmark Evaluation System for Medical Visual Question Answering—0
A Comprehensive Survey on Relation Extraction: Recent Advances and New Frontiers—0
HealthQ: Unveiling Questioning Capabilities of LLM Chains in Healthcare Conversations—0
Does my multimodal model learn cross-modal interactions? It's harder to tell than you might think!—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