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 1551–1600 of 10817 papers

TitleStatusHype
Resilience in Knowledge Graph Embeddings—0
Attention Overlap Is Responsible for The Entity Missing Problem in Text-to-image Diffusion Models!—0
AutoBench-V: Can Large Vision-Language Models Benchmark Themselves?Code0
Efficient Bilinear Attention-based Fusion for Medical Visual Question Answering—0
LLM Robustness Against Misinformation in Biomedical Question AnsweringCode0
Get Large Language Models Ready to Speak: A Late-fusion Approach for Speech Generation—0
MedGo: A Chinese Medical Large Language Model—0
Rethinking Data Synthesis: A Teacher Model Training Recipe with Interpretation—0
R-LLaVA: Improving Med-VQA Understanding through Visual Region of Interest—0
Sensor2Text: Enabling Natural Language Interactions for Daily Activity Tracking Using Wearable Sensors—0
GiVE: Guiding Visual Encoder to Perceive Overlooked Information—0
EfficientEQA: An Efficient Approach for Open Vocabulary Embodied Question Answering—0
A Survey of Large Language Models for Arabic Language and its Dialects—0
PatentAgent: Intelligent Agent for Automated Pharmaceutical Patent Analysis—0
Natural Language Processing for the Legal Domain: A Survey of Tasks, Datasets, Models, and Challenges—0
FLAASH: Flow-Attention Adaptive Semantic Hierarchical Fusion for Multi-Modal Tobacco Content Analysis—0
Not All Heads Matter: A Head-Level KV Cache Compression Method with Integrated Retrieval and ReasoningCode1
Can Code-Switched Texts Activate a Knowledge Switch in LLMs? A Case Study on English-Korean Code-Switching—0
BioMistral-NLU: Towards More Generalizable Medical Language Understanding through Instruction Tuning—0
Visual Text Matters: Improving Text-KVQA with Visual Text Entity Knowledge-aware Large Multimodal AssistantCode0
Decoding on Graphs: Faithful and Sound Reasoning on Knowledge Graphs through Generation of Well-Formed Chains—0
Interpretable Bilingual Multimodal Large Language Model for Diverse Biomedical Tasks—0
Geometric Feature Enhanced Knowledge Graph Embedding and Spatial Reasoning—0
DeCoRe: Decoding by Contrasting Retrieval Heads to Mitigate HallucinationsCode1
Aggregated Knowledge Model: Enhancing Domain-Specific QA with Fine-Tuned and Retrieval-Augmented Generation Models—0
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