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 651–700 of 10817 papers

TitleStatusHype
Unmasking Deceptive Visuals: Benchmarking Multimodal Large Language Models on Misleading Chart Question Answering—0
SUNAR: Semantic Uncertainty based Neighborhood Aware Retrieval for Complex QA—0
Relation Extraction with Instance-Adapted Predicate DescriptionsCode0
4D-Bench: Benchmarking Multi-modal Large Language Models for 4D Object UnderstandingCode0
Progressive Prompt Detailing for Improved Alignment in Text-to-Image Generative ModelsCode0
MARS: A Multi-Agent Framework Incorporating Socratic Guidance for Automated Prompt Optimization—0
Does Chain-of-Thought Reasoning Help Mobile GUI Agent? An Empirical StudyCode0
Chain-of-Tools: Utilizing Massive Unseen Tools in the CoT Reasoning of Frozen Language ModelsCode2
A Study into Investigating Temporal Robustness of LLMs—0
MTBench: A Multimodal Time Series Benchmark for Temporal Reasoning and Question AnsweringCode1
PVChat: Personalized Video Chat with One-Shot Learning—0
Dense Passage Retrieval in Conversational SearchCode0
Big Help or Big Brother? Auditing Tracking, Profiling, and Personalization in Generative AI Assistants—0
UMIT: Unifying Medical Imaging Tasks via Vision-Language ModelsCode0
DocVideoQA: Towards Comprehensive Understanding of Document-Centric Videos through Question Answering—0
MKG-Rank: Enhancing Large Language Models with Knowledge Graph for Multilingual Medical Question Answering—0
Typed-RAG: Type-aware Multi-Aspect Decomposition for Non-Factoid Question AnsweringCode0
Agentic Keyframe Search for Video Question AnsweringCode1
A Vision Centric Remote Sensing Benchmark—0
ECKGBench: Benchmarking Large Language Models in E-commerce Leveraging Knowledge Graph—0
GraspCoT: Integrating Physical Property Reasoning for 6-DoF Grasping under Flexible Language Instructions—0
Bridging Technology and Humanities: Evaluating the Impact of Large Language Models on Social Sciences Research with DeepSeek-R1—0
AutoDrive-QA- Automated Generation of Multiple-Choice Questions for Autonomous Driving Datasets Using Large Vision-Language Models—0
Bias Evaluation and Mitigation in Retrieval-Augmented Medical Question-Answering Systems—0
Optimizing Retrieval Strategies for Financial Question Answering Documents in Retrieval-Augmented Generation SystemsCode1
EfficientLLaVA:Generalizable Auto-Pruning for Large Vision-language Models—0
MAMM-Refine: A Recipe for Improving Faithfulness in Generation with Multi-Agent Collaboration—0
UPME: An Unsupervised Peer Review Framework for Multimodal Large Language Model Evaluation—0
KoGNER: A Novel Framework for Knowledge Graph Distillation on Biomedical Named Entity Recognition—0
GraspCorrect: Robotic Grasp Correction via Vision-Language Model-Guided Feedback—0
Solla: Towards a Speech-Oriented LLM That Hears Acoustic ContextCode0
TruthLens:A Training-Free Paradigm for DeepFake Detection—0
Uncertainty Distillation: Teaching Language Models to Express Semantic Confidence—0
EIAD: Explainable Industrial Anomaly Detection Via Multi-Modal Large Language Models—0
Synthetic Clarification and Correction Dialogues about Data-Centric Tasks -- A Teacher-Student Approach—0
Synthetic Data Generation Using Large Language Models: Advances in Text and Code—0
MDocAgent: A Multi-Modal Multi-Agent Framework for Document UnderstandingCode3
How much do LLMs learn from negative examples?Code0
CARE: A QLoRA-Fine Tuned Multi-Domain Chatbot With Fast Learning On Minimal Hardware—0
Identifying and Mitigating Position Bias of Multi-image Vision-Language Models—0
Marten: Visual Question Answering with Mask Generation for Multi-modal Document UnderstandingCode0
Where do Large Vision-Language Models Look at when Answering Questions?Code2
RAG-RL: Advancing Retrieval-Augmented Generation via RL and Curriculum Learning—0
HICD: Hallucination-Inducing via Attention Dispersion for Contrastive Decoding to Mitigate Hallucinations in Large Language ModelsCode0
VITED: Video Temporal Evidence Distillation—0
HIS-GPT: Towards 3D Human-In-Scene Multimodal Understanding—0
VideoMind: A Chain-of-LoRA Agent for Long Video ReasoningCode3
Unified Autoregressive Visual Generation and Understanding with Continuous Tokens—0
Knowledge-Aware Iterative Retrieval for Multi-Agent Systems—0
MES-RAG: Bringing Multi-modal, Entity-Storage, and Secure Enhancements to RAGCode0
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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