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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 9901–9950 of 10817 papers

TitleStatusHype
Second Place Solution of WSDM2023 Toloka Visual Question Answering Challenge—0
Secret-Keeping in Question Answering—0
SECURA: Sigmoid-Enhanced CUR Decomposition with Uninterrupted Retention and Low-Rank Adaptation in Large Language Models—0
Security and Privacy Challenges of Large Language Models: A Survey—0
See and Think: Embodied Agent in Virtual Environment—0
SpatialPIN: Enhancing Spatial Reasoning Capabilities of Vision-Language Models through Prompting and Interacting 3D Priors—0
Seeing and Reasoning with Confidence: Supercharging Multimodal LLMs with an Uncertainty-Aware Agentic Framework—0
Seeing Far and Clearly: Mitigating Hallucinations in MLLMs with Attention Causal Decoding—0
Seeing is Deceiving: Exploitation of Visual Pathways in Multi-Modal Language Models—0
Seeing is Knowing! Fact-based Visual Question Answering using Knowledge Graph Embeddings—0
Seeing More with Less: Human-like Representations in Vision Models—0
Seeing Through the Fog: A Cost-Effectiveness Analysis of Hallucination Detection Systems—0
Seek and Solve Reasoning for Table Question Answering—0
See or Recall: A Sanity Check for the Role of Vision in Solving Visualization Question Answer Tasks with Multimodal LLMs—0
See then Tell: Enhancing Key Information Extraction with Vision Grounding—0
"See the World, Discover Knowledge": A Chinese Factuality Evaluation for Large Vision Language Models—0
SegEQA: Video Segmentation Based Visual Attention for Embodied Question Answering—0
Segmentation-guided Attention for Visual Question Answering from Remote Sensing Images—0
Segmentation Guided Attention Networks for Visual Question Answering—0
SEGMENT+: Long Text Processing with Short-Context Language Models—0
Select2Plan: Training-Free ICL-Based Planning through VQA and Memory Retrieval—0
Selecting Contextual Peripheral Information for Answer Presentation: The Need for Pragmatic Models—0
Selecting Sentences versus Selecting Tree Constituents for Automatic Question Ranking—0
Selectively Answering Ambiguous Questions—0
Selectively Answering Visual Questions—0
Self-alignment of Large Video Language Models with Refined Regularized Preference Optimization—0
Self-Attentive Constituency Parsing for UCCA-based Semantic Parsing—0
Self-Convinced Prompting: Few-Shot Question Answering with Repeated Introspection—0
Self-Crowdsourcing Training for Relation Extraction—0
Self-DC: When to Reason and When to Act? Self Divide-and-Conquer for Compositional Unknown Questions—0
Large Language Models are In-context Teachers for Knowledge Reasoning—0
SelfGraphVQA: A Self-Supervised Graph Neural Network for Scene-based Question Answering—0
Self-Improvement Programming for Temporal Knowledge Graph Question Answering—0
Self-Knowledge Guided Retrieval Augmentation for Large Language Models—0
Self-Refinement of Language Models from External Proxy Metrics Feedback—0
Self-Reflective Planning with Knowledge Graphs: Enhancing LLM Reasoning Reliability for Question Answering—0
Self-ReS: Self-Reflection in Large Vision-Language Models for Long Video Understanding—0
Self-Segregating and Coordinated-Segregating Transformer for Focused Deep Multi-Modular Network for Visual Question Answering—0
Self-supervised Contrastive Cross-Modality Representation Learning for Spoken Question Answering—0
Self-supervised Dialogue Learning for Spoken Conversational Question Answering—0
Self-supervised Knowledge Triplet Learning for Zero-shot Question Answering—0
Self-Supervised learning with cross-modal transformers for emotion recognition—0
Self-supervised pre-training and contrastive representation learning for multiple-choice video QA—0
Self-Supervised Test-Time Learning for Reading Comprehension—0
WeaQA: Weak Supervision via Captions for Visual Question Answering—0
Self-Teaching Machines to Read and Comprehend with Large-Scale Multi-Subject Question-Answering Data—0
Self-Training for Jointly Learning to Ask and Answer Questions—0
Self-training improves Recurrent Neural Networks performance for Temporal Relation Extraction—0
Self-Training Large Language Models for Improved Visual Program Synthesis With Visual Reinforcement—0
Self-Training Large Language Models for Tool-Use Without Demonstrations—0
Show:102550
← PrevPage 199 of 217Next →
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