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 2651–2700 of 10817 papers

TitleStatusHype
CAPO: Reinforcing Consistent Reasoning in Medical Decision-Making—0
A Question Answering Approach to Emotion Cause Extraction—0
Efficient In-Domain Question Answering for Resource-Constrained Environments—0
Capabilities of Gemini Models in Medicine—0
Can You Unpack That? Learning to Rewrite Questions-in-Context—0
A Question Answering Approach for Emotion Cause Extraction—0
Can you even tell left from right? Presenting a new challenge for VQA—0
Can MLLMs Generalize to Multi-Party dialog? Exploring Multilingual Response Generation in Complex Scenarios—0
Active Reasoning in an Open-World Environment—0
Efficient Knowledge Feeding to Language Models: A Novel Integrated Encoder-Decoder Architecture—0
EfficientLLaVA: Generalizable Auto-Pruning for Large Vision-language Models—0
Can We Infer Confidential Properties of Training Data from LLMs?—0
A Quantitative Evaluation of Natural Language Question Interpretation for Question Answering Systems—0
Active Reading Comprehension: A Dataset for Learning the Question-Answer Relationship Strategy—0
Can We Generate Visual Programs Without Prompting LLMs?—0
Can We Create a Tool for General Domain Event Analysis?—0
Document-level Event Extraction with Efficient End-to-end Learning of Cross-event Dependencies—0
Can Visual Language Models Replace OCR-Based Visual Question Answering Pipelines in Production? A Case Study in Retail—0
AI-KU: Using Co-Occurrence Modeling for Semantic Similarity—0
Can Vision-Language Models Answer Face to Face Questions in the Real-World?—0
Abductive Matching in Question Answering—0
EfficientEQA: An Efficient Approach for Open Vocabulary Embodied Question Answering—0
Can Transformers Reason About Effects of Actions?—0
Can Small Language Models Help Large Language Models Reason Better?: LM-Guided Chain-of-Thought—0
Do Question Answering Modeling Improvements Hold Across Benchmarks?—0
Can SAR improve RSVQA performance?—0
Efficient crowdsourcing of crowd-generated microtasks—0
A Procedural Definition of Multi-word Lexical Units—0
Can Question Generation Debias Question Answering Models? A Case Study on Question–Context Lexical Overlap—0
AiFu at SemEval-2019 Task 10: A Symbolic and Sub-symbolic Integrated System for SAT Math Question Answering—0
Efficient Deployment of Conversational Natural Language Interfaces over Databases—0
Efficient Few-Shot Continual Learning in Vision-Language Models—0
A Probabilistic Model for Joint Learning of Word Embeddings from Texts and Images—0
Can Pre-training help VQA with Lexical Variations?—0
AIDA: Artificial Intelligent Dialogue Agent—0
Can predicate-argument relationships be extracted from UD trees?—0
A Probabilistic-Logic based Commonsense Representation Framework for Modelling Inferences with Multiple Antecedents and Varying Likelihoods—0
Evaluating the Ebb and Flow: An In-depth Analysis of Question-Answering Trends across Diverse Platforms—0
Can Open Domain Question Answering Systems Answer Visual Knowledge Questions?—0
A Probabilistic Lexical Model for Ranking Textual Inferences—0
A Probabilistic Annotation Model for Crowdsourcing Coreference—0
AIA-BDE: A Corpus of FAQs in Portuguese and their Variations—0
Actively Seeking and Learning from Live Data—0
Efficient Bilinear Attention-based Fusion for Medical Visual Question Answering—0
Can Multimodal LLMs do Visual Temporal Understanding and Reasoning? The answer is No!—0
A Pretraining Numerical Reasoning Model for Ordinal Constrained Question Answering on Knowledge Base—0
Can LLMs Generate Human-Like Wayfinding Instructions? Towards Platform-Agnostic Embodied Instruction Synthesis—0
Can LLMs assist with Ambiguity? A Quantitative Evaluation of various Large Language Models on Word Sense Disambiguation—0
A Preliminary Study of o1 in Medicine: Are We Closer to an AI Doctor?—0
Can Large Language Models Unveil the Mysteries? An Exploration of Their Ability to Unlock Information in Complex Scenarios—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