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 2801–2825 of 10817 papers

TitleStatusHype
Pretraining and Updates of Domain-Specific LLM: A Case Study in the Japanese Business Domain—0
Improving Health Question Answering with Reliable and Time-Aware Evidence RetrievalCode0
Enhancing Visual Question Answering through Question-Driven Image Captions as PromptsCode1
Synthetic Dataset Creation and Fine-Tuning of Transformer Models for Question Answering in SerbianCode0
Small Models Are (Still) Effective Cross-Domain Argument ExtractorsCode0
MM-PhyQA: Multimodal Physics Question-Answering With Multi-Image CoT Prompting—0
View Selection for 3D Captioning via Diffusion RankingCode3
Language Models Meet Anomaly Detection for Better Interpretability and GeneralizabilityCode0
Audio Dialogues: Dialogues dataset for audio and music understanding—0
Learning to Localize Objects Improves Spatial Reasoning in Visual-LLMsCode0
LLoCO: Learning Long Contexts OfflineCode2
On Unified Prompt Tuning for Request Quality Assurance in Public Code Review—0
RiskLabs: Predicting Financial Risk Using Large Language Model based on Multimodal and Multi-Sources Data—0
Unraveling the Dilemma of AI Errors: Exploring the Effectiveness of Human and Machine Explanations for Large Language Models—0
OpenBias: Open-set Bias Detection in Text-to-Image Generative ModelsCode1
Enhancing Question Answering for Enterprise Knowledge Bases using Large Language Models—0
Groundedness in Retrieval-augmented Long-form Generation: An Empirical Study—0
Superposition Prompting: Improving and Accelerating Retrieval-Augmented GenerationCode2
Transferable and Efficient Non-Factual Content Detection via Probe Training with Offline Consistency CheckingCode0
Identifying Shopping Intent in Product QA for Proactive Recommendations—0
LLMs' Reading Comprehension Is Affected by Parametric Knowledge and Struggles with Hypothetical Statements—0
Ada-LEval: Evaluating long-context LLMs with length-adaptable benchmarksCode2
Visually Descriptive Language Model for Vector Graphics ReasoningCode9
MoReVQA: Exploring Modular Reasoning Models for Video Question Answering—0
SurveyAgent: A Conversational System for Personalized and Efficient Research Survey—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