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 4226–4250 of 10817 papers

TitleStatusHype
Discovering Bias in Latent Space: An Unsupervised Debiasing Approach—0
Balancing Performance and Efficiency in Zero-shot Robotic Navigation—0
CSS: Contrastive Semantic Similarity for Uncertainty Quantification of LLMsCode0
UniOQA: A Unified Framework for Knowledge Graph Question Answering with Large Language Models—0
I've got the "Answer"! Interpretation of LLMs Hidden States in Question Answering—0
Chain of Agents: Large Language Models Collaborating on Long-Context Tasks—0
ACCORD: Closing the Commonsense Measurability GapCode0
Enhancing Retrieval-Augmented LMs with a Two-stage Consistency Learning Compressor—0
Multimodal Reasoning with Multimodal Knowledge Graph—0
On the Intrinsic Self-Correction Capability of LLMs: Uncertainty and Latent Concept—0
Translation Deserves Better: Analyzing Translation Artifacts in Cross-lingual Visual Question Answering—0
Diffusion-Refined VQA Annotations for Semi-Supervised Gaze FollowingCode0
Analyzing Social Biases in Japanese Large Language ModelsCode0
Story Generation from Visual Inputs: Techniques, Related Tasks, and Challenges—0
Ask-EDA: A Design Assistant Empowered by LLM, Hybrid RAG and Abbreviation De-hallucination—0
Utilizing Large Language Models for Automating Technical Customer Support—0
Graph Neural Network Enhanced Retrieval for Question Answering of LLMs—0
Explore then Determine: A GNN-LLM Synergy Framework for Reasoning over Knowledge Graph—0
Mixture of Rationale: Multi-Modal Reasoning Mixture for Visual Question Answering—0
Selectively Answering Visual Questions—0
EffiQA: Efficient Question-Answering with Strategic Multi-Model Collaboration on Knowledge Graphs—0
MedFuzz: Exploring the Robustness of Large Language Models in Medical Question Answering—0
Contextualized Sequence Likelihood: Enhanced Confidence Scores for Natural Language GenerationCode0
Superhuman performance in urology board questions by an explainable large language model enabled for context integration of the European Association of Urology guidelines: the UroBot study—0
CMDBench: A Benchmark for Coarse-to-fine Multimodal Data Discovery in Compound AI SystemsCode0
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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