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 3701–3725 of 10817 papers

TitleStatusHype
Self-Updatable Large Language Models with Parameter Integration—0
Benchmarking Large Language Models for Conversational Question Answering in Multi-instructional Documents—0
Unleashing the Potentials of Likelihood Composition for Multi-modal Language ModelsCode0
BabelBench: An Omni Benchmark for Code-Driven Analysis of Multimodal and Multistructured DataCode0
Optimizing and Evaluating Enterprise Retrieval-Augmented Generation (RAG): A Content Design PerspectiveCode0
Quantifying reliance on external information over parametric knowledge during Retrieval Augmented Generation (RAG) using mechanistic analysis—0
Addition is All You Need for Energy-efficient Language Models—0
World to Code: Multi-modal Data Generation via Self-Instructed Compositional Captioning and FilteringCode0
Reference Trustable Decoding: A Training-Free Augmentation Paradigm for Large Language ModelsCode0
Towards Robust Extractive Question Answering Models: Rethinking the Training MethodologyCode0
See then Tell: Enhancing Key Information Extraction with Vision Grounding—0
Does RAG Introduce Unfairness in LLMs? Evaluating Fairness in Retrieval-Augmented Generation SystemsCode0
Video DataFlywheel: Resolving the Impossible Data Trinity in Video-Language Understanding—0
MedViLaM: A multimodal large language model with advanced generalizability and explainability for medical data understanding and generationCode0
TrojVLM: Backdoor Attack Against Vision Language Models—0
HealthQ: Unveiling Questioning Capabilities of LLM Chains in Healthcare Conversations—0
3D-CT-GPT: Generating 3D Radiology Reports through Integration of Large Vision-Language Models—0
Zero-Shot Multi-Hop Question Answering via Monte-Carlo Tree Search with Large Language Models—0
Charting the Future: Using Chart Question-Answering for Scalable Evaluation of LLM-Driven Data Visualizations—0
Exploring Language Model Generalization in Low-Resource Extractive QACode0
AIPatient: Simulating Patients with EHRs and LLM Powered Agentic Workflow—0
Enhancing Explainability in Multimodal Large Language Models Using Ontological Context—0
Rehearsing Answers to Probable Questions with Perspective-Taking—0
Revisiting the Superficial Alignment Hypothesis—0
T3: A Novel Zero-shot Transfer Learning Framework Iteratively Training on an Assistant Task for a Target Task—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