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 801–825 of 10817 papers

TitleStatusHype
SemViQA: A Semantic Question Answering System for Vietnamese Information Fact-CheckingCode2
FunBench: Benchmarking Fundus Reading Skills of MLLMs—0
Towards Efficient Educational Chatbots: Benchmarking RAG Frameworks—0
GlossGPT: GPT for Word Sense Disambiguation using Few-shot Chain-of-Thought PromptingCode0
Streaming Video Question-Answering with In-context Video KV-Cache RetrievalCode2
AILS-NTUA at SemEval-2025 Task 8: Language-to-Code prompting and Error Fixing for Tabular Question AnsweringCode0
CL-MoE: Enhancing Multimodal Large Language Model with Dual Momentum Mixture-of-Experts for Continual Visual Question Answering—0
Fine-Grained Retrieval-Augmented Generation for Visual Question Answering—0
WebFAQ: A Multilingual Collection of Natural Q&A Datasets for Dense Retrieval—0
MedHallTune: An Instruction-Tuning Benchmark for Mitigating Medical Hallucination in Vision-Language ModelsCode0
TempRetriever: Fusion-based Temporal Dense Passage Retrieval for Time-Sensitive Questions—0
PreMind: Multi-Agent Video Understanding for Advanced Indexing of Presentation-style Videos—0
Protecting multimodal large language models against misleading visualizationsCode0
Bisecting K-Means in RAG for Enhancing Question-Answering Tasks Performance in Telecommunications—0
M-LLM Based Video Frame Selection for Efficient Video Understanding—0
ChineseEcomQA: A Scalable E-commerce Concept Evaluation Benchmark for Large Language ModelsCode1
From Retrieval to Generation: Comparing Different Approaches—0
Med-RLVR: Emerging Medical Reasoning from a 3B base model via reinforcement Learning—0
Few-Shot Multilingual Open-Domain QA from 5 ExamplesCode0
Can Large Language Models Unveil the Mysteries? An Exploration of Their Ability to Unlock Information in Complex Scenarios—0
UQABench: Evaluating User Embedding for Prompting LLMs in Personalized Question AnsweringCode1
END: Early Noise Dropping for Efficient and Effective Context Denoising—0
Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement—0
Nexus: An Omni-Perceptive And -Interactive Model for Language, Audio, And Vision—0
Talking to the brain: Using Large Language Models as Proxies to Model Brain Semantic Representation—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