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

Showing 22012250 of 10817 papers

TitleStatusHype
From Problem-Solving to Teaching Problem-Solving: Aligning LLMs with Pedagogy using Reinforcement LearningCode1
Distantly-Supervised Evidence Retrieval Enables Question Answering without Evidence AnnotationCode1
Cognitive Visual-Language Mapper: Advancing Multimodal Comprehension with Enhanced Visual Knowledge AlignmentCode1
Consistency-preserving Visual Question Answering in Medical ImagingCode1
Consistency Regularization for Cross-Lingual Fine-TuningCode1
FSPO: Few-Shot Preference Optimization of Synthetic Preference Data in LLMs Elicits Effective Personalization to Real UsersCode1
Why So Gullible? Enhancing the Robustness of Retrieval-Augmented Models against Counterfactual NoiseCode1
Direct Evaluation of Chain-of-Thought in Multi-hop Reasoning with Knowledge GraphsCode1
Gemini Goes to Med School: Exploring the Capabilities of Multimodal Large Language Models on Medical Challenge Problems & HallucinationsCode1
Generalizing from SIMPLE to HARD Visual Reasoning: Can We Mitigate Modality Imbalance in VLMs?Code1
Discourse Analysis via Questions and Answers: Parsing Dependency Structures of Questions Under DiscussionCode1
Generating with Confidence: Uncertainty Quantification for Black-box Large Language ModelsCode1
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighterCode1
Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning StepsCode1
CogMG: Collaborative Augmentation Between Large Language Model and Knowledge GraphCode1
Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder TransformersCode1
DialSim: A Real-Time Simulator for Evaluating Long-Term Multi-Party Dialogue Understanding of Conversational AgentsCode1
Constructing Benchmarks and Interventions for Combating Hallucinations in LLMsCode1
Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning StrategiesCode1
DialogLM: Pre-trained Model for Long Dialogue Understanding and SummarizationCode1
Glance and Focus: Memory Prompting for Multi-Event Video Question AnsweringCode1
Learning Video Context as Interleaved Multimodal SequencesCode1
Differentiable Reasoning on Large Knowledge Bases and Natural LanguageCode1
DeVLBert: Learning Deconfounded Visio-Linguistic RepresentationsCode1
Development and bilingual evaluation of Japanese medical large language model within reasonably low computational resourcesCode1
DEXTER: A Benchmark for open-domain Complex Question Answering using LLMsCode1
Code-Style In-Context Learning for Knowledge-Based Question AnsweringCode1
Context-Aware Answer Extraction in Question AnsweringCode1
GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question AnsweringCode1
Gracefully Filtering Backdoor Samples for Generative Large Language Models without RetrainingCode1
CSMeD: Bridging the Dataset Gap in Automated Citation Screening for Systematic Literature ReviewsCode1
Dialog Inpainting: Turning Documents into DialogsCode1
Context Awareness Gate For Retrieval Augmented GenerationCode1
GraphNeT: Graph neural networks for neutrino telescope event reconstructionCode1
Distilled Dual-Encoder Model for Vision-Language UnderstandingCode1
Graphusion: A RAG Framework for Knowledge Graph Construction with a Global PerspectiveCode1
Dual-Key Multimodal Backdoors for Visual Question AnsweringCode1
Improving Large Language Models via Fine-grained Reinforcement Learning with Minimum Editing ConstraintCode1
Less is More: Pretrain a Strong Siamese Encoder for Dense Text Retrieval Using a Weak DecoderCode1
Physics of Language Models: Part 3.1, Knowledge Storage and ExtractionCode1
Code-Mixed Question Answering Challenge: Crowd-sourcing Data and Techniques0
All You May Need for VQA are Image Captions0
CodeForTheChange at SemEval-2019 Task 8: Skip-Thoughts for Fact Checking in Community Question Answering0
AcademicGPT: Empowering Academic Research0
CoCo-BERT: Improving Video-Language Pre-training with Contrastive Cross-modal Matching and Denoising0
Uncertainty Quantification for LLMs through Minimum Bayes Risk: Bridging Confidence and Consistency0
Asking Too Much? The Rhetorical Role of Questions in Political Discourse0
Asking the Right Questions in Low Resource Template Extraction0
Adaptive Query Rewriting: Aligning Rewriters through Marginal Probability of Conversational Answers0
Detecting and Resolving Shell Nouns in German0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1IE-Net (ensemble)EM90.94Unverified
2FPNet (ensemble)EM90.87Unverified
3IE-NetV2 (ensemble)EM90.86Unverified
4SA-Net on Albert (ensemble)EM90.72Unverified
5SA-Net-V2 (ensemble)EM90.68Unverified
6FPNet (ensemble)EM90.6Unverified
7Retro-Reader (ensemble)EM90.58Unverified
8EntitySpanFocusV2 (ensemble)EM90.52Unverified
9TransNets + SFVerifier + SFEnsembler (ensemble)EM90.49Unverified
10EntitySpanFocus+AT (ensemble)EM90.45Unverified