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 1576–1600 of 10817 papers

TitleStatusHype
Large Language Models Reflect the Ideology of their CreatorsCode1
Leveraging the Domain Adaptation of Retrieval Augmented Generation Models for Question Answering and Reducing Hallucination—0
LongRAG: A Dual-Perspective Retrieval-Augmented Generation Paradigm for Long-Context Question AnsweringCode2
Which Client is Reliable?: A Reliable and Personalized Prompt-based Federated Learning for Medical Image Question Answering—0
VoiceTextBlender: Augmenting Large Language Models with Speech Capabilities via Single-Stage Joint Speech-Text Supervised Fine-TuningCode1
SimRAG: Self-Improving Retrieval-Augmented Generation for Adapting Large Language Models to Specialized Domains—0
Graphusion: A RAG Framework for Knowledge Graph Construction with a Global PerspectiveCode1
An Ontology-Enabled Approach For User-Centered and Knowledge-Enabled Explanations of AI SystemsCode0
ADEM-VL: Adaptive and Embedded Fusion for Efficient Vision-Language TuningCode1
An Adaptive Framework for Generating Systematic Explanatory Answer in Online Q&A PlatformsCode0
Optimizing LLMs with Direct Preferences: A Data Efficiency Perspective—0
Visual Question Answering in Ophthalmology: A Progressive and Practical Perspective—0
Distill-SynthKG: Distilling Knowledge Graph Synthesis Workflow for Improved Coverage and Efficiency—0
SG-FSM: A Self-Guiding Zero-Shot Prompting Paradigm for Multi-Hop Question Answering Based on Finite State Machine—0
Correct after Answer: Enhancing Multi-Span Question Answering with Post-Processing MethodCode0
Progressive Compositionality In Text-to-Image Generative ModelsCode1
Order Matters: Exploring Order Sensitivity in Multimodal Large Language Models—0
Atomic Fact Decomposition Helps Attributed Question Answering—0
ComPO: Community Preferences for Language Model Personalization—0
Steering Knowledge Selection Behaviours in LLMs via SAE-Based Representation EngineeringCode2
Learning-to-Defer for Extractive Question Answering—0
Improve Dense Passage Retrieval with Entailment Tuning—0
Object-Centric Temporal Consistency via Conditional Autoregressive Inductive Biases—0
RAG4ITOps: A Supervised Fine-Tunable and Comprehensive RAG Framework for IT Operations and Maintenance—0
Fine-Tuning LLMs for Reliable Medical Question-Answering Services—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