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 2451–2475 of 10817 papers

TitleStatusHype
Deep Video Discovery: Agentic Search with Tool Use for Long-form Video Understanding—0
PerMedCQA: Benchmarking Large Language Models on Medical Consumer Question Answering in Persian Language—0
Task Specific Pruning with LLM-Sieve: How Many Parameters Does Your Task Really Need?—0
Analyzing Mitigation Strategies for Catastrophic Forgetting in End-to-End Training of Spoken Language Models—0
PPT: A Process-based Preference Learning Framework for Self Improving Table Question Answering Models—0
CXReasonBench: A Benchmark for Evaluating Structured Diagnostic Reasoning in Chest X-raysCode0
Are the Hidden States Hiding Something? Testing the Limits of Factuality-Encoding Capabilities in LLMs—0
Zero-Shot Anomaly Detection in Battery Thermal Images Using Visual Question Answering with Prior Knowledge—0
UNCLE: Uncertainty Expressions in Long-Form Generation—0
Evaluating Large Language Model with Knowledge Oriented Language Specific Simple Question AnsweringCode0
CUB: Benchmarking Context Utilisation Techniques for Language Models—0
Grounding Chest X-Ray Visual Question Answering with Generated Radiology Reports—0
CT-Agent: A Multimodal-LLM Agent for 3D CT Radiology Question Answering—0
Augmenting LLM Reasoning with Dynamic Notes Writing for Complex QA—0
Tools in the Loop: Quantifying Uncertainty of LLM Question Answering Systems That Use Tools—0
Continually Self-Improving Language Models for Bariatric Surgery Question--Answering—0
VoxRAG: A Step Toward Transcription-Free RAG Systems in Spoken Question Answering—0
EarthSE: A Benchmark Evaluating Earth Scientific Exploration Capability for Large Language Models—0
A Causal Approach to Mitigate Modality Preference Bias in Medical Visual Question Answering—0
Seeing Far and Clearly: Mitigating Hallucinations in MLLMs with Attention Causal Decoding—0
Collaboration among Multiple Large Language Models for Medical Question Answering—0
Steering LVLMs via Sparse Autoencoder for Hallucination Mitigation—0
Visual Question Answering on Multiple Remote Sensing Image Modalities—0
Leveraging Online Data to Enhance Medical Knowledge in a Small Persian Language ModelCode0
SNAP: A Benchmark for Testing the Effects of Capture Conditions on Fundamental Vision TasksCode0
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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