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 3501–3550 of 10817 papers

TitleStatusHype
Retrieval-augmented Multi-modal Chain-of-Thoughts Reasoning for Large Language Models—0
MedXChat: A Unified Multimodal Large Language Model Framework towards CXRs Understanding and Generation—0
VaQuitA: Enhancing Alignment in LLM-Assisted Video Understanding—0
Good Questions Help Zero-Shot Image ReasoningCode1
Recursive Visual ProgrammingCode1
GNN2R: Weakly-Supervised Rationale-Providing Question Answering over Knowledge GraphsCode0
ChatGPT as a Math Questioner? Evaluating ChatGPT on Generating Pre-university Math QuestionsCode0
Unleashing the Potential of Large Language Model: Zero-shot VQA for Flood Disaster Scenario—0
How to Configure Good In-Context Sequence for Visual Question AnsweringCode1
Towards Learning a Generalist Model for Embodied NavigationCode2
Bridging Background Knowledge Gaps in Translation with Automatic ExplicitationCode0
NLEBench+NorGLM: A Comprehensive Empirical Analysis and Benchmark Dataset for Generative Language Models in NorwegianCode0
On Significance of Subword tokenization for Low Resource and Efficient Named Entity Recognition: A case study in Marathi—0
TextGenSHAP: Scalable Post-hoc Explanations in Text Generation with Long Documents—0
Knowledge Graph Reasoning Based on Attention GCN—0
From Beginner to Expert: Modeling Medical Knowledge into General LLMs—0
Towards leveraging LLMs for Conditional QA—0
Axiomatic Preference Modeling for Longform Question Answering—0
Harnessing the Power of Prompt-based Techniques for Generating School-Level Questions using Large Language ModelsCode0
Semantic Parsing for Question Answering over Knowledge Graphs—0
Zero-Shot Video Question Answering with Procedural Programs—0
ESG Accountability Made Easy: DocQA at Your Service—0
LL3DA: Visual Interactive Instruction Tuning for Omni-3D Understanding, Reasoning, and PlanningCode2
How Generative-AI can be Effectively used in Government Chatbots—0
Uncertainty Guided Global Memory Improves Multi-Hop Question AnsweringCode0
DreamSync: Aligning Text-to-Image Generation with Image Understanding Feedback—0
Universal Self-Consistency for Large Language Model Generation—0
Reinforcement Replaces Supervision: Query focused Summarization using Deep Reinforcement LearningCode0
Enhancing Answer Selection in Community Question Answering with Pre-trained and Large Language Models—0
Towards Top-Down Reasoning: An Explainable Multi-Agent Approach for Visual Question Answering—0
AviationGPT: A Large Language Model for the Aviation Domain—0
How to Build an AI Tutor That Can Adapt to Any Course Using Knowledge Graph-Enhanced Retrieval-Augmented Generation (KG-RAG)—0
E-ViLM: Efficient Video-Language Model via Masked Video Modeling with Semantic Vector-Quantized Tokenizer—0
Emergent Open-Vocabulary Semantic Segmentation from Off-the-shelf Vision-Language ModelsCode1
Ascle: A Python Natural Language Processing Toolkit for Medical Text GenerationCode1
Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in MedicineCode5
LLaMA-VID: An Image is Worth 2 Tokens in Large Language ModelsCode2
The curse of language biases in remote sensing VQA: the role of spatial attributes, language diversity, and the need for clear evaluation—0
Characterizing Video Question Answering with Sparsified Inputs—0
Knowledge Unlearning for LLMs: Tasks, Methods, and Challenges—0
Releasing the CRaQAn (Coreference Resolution in Question-Answering): An open-source dataset and dataset creation methodology using instruction-following models—0
A Comparative and Experimental Study on Automatic Question Answering Systems and its Robustness against Word Jumbling—0
LLMGA: Multimodal Large Language Model based Generation AssistantCode2
Cerbero-7B: A Leap Forward in Language-Specific LLMs Through Enhanced Chat Corpus Generation and EvaluationCode1
EgoThink: Evaluating First-Person Perspective Thinking Capability of Vision-Language ModelsCode1
Video-Bench: A Comprehensive Benchmark and Toolkit for Evaluating Video-based Large Language ModelsCode1
Increasing Coverage and Precision of Textual Information in Multilingual Knowledge GraphsCode1
Optimizing and Fine-tuning Large Language Model for Urban Renewal—0
Fully Authentic Visual Question Answering Dataset from Online CommunitiesCode0
MEDITRON-70B: Scaling Medical Pretraining for Large Language ModelsCode4
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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