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 1801–1850 of 10817 papers

TitleStatusHype
MedViLaM: A multimodal large language model with advanced generalizability and explainability for medical data understanding and generationCode0
See then Tell: Enhancing Key Information Extraction with Vision Grounding—0
CoTKR: Chain-of-Thought Enhanced Knowledge Rewriting for Complex Knowledge Graph Question AnsweringCode1
T2Vs Meet VLMs: A Scalable Multimodal Dataset for Visual Harmfulness RecognitionCode1
HealthQ: Unveiling Questioning Capabilities of LLM Chains in Healthcare Conversations—0
Zero-Shot Multi-Hop Question Answering via Monte-Carlo Tree Search with Large Language Models—0
TrojVLM: Backdoor Attack Against Vision Language Models—0
3D-CT-GPT: Generating 3D Radiology Reports through Integration of Large Vision-Language Models—0
Revisiting the Superficial Alignment Hypothesis—0
Rehearsing Answers to Probable Questions with Perspective-Taking—0
AIPatient: Simulating Patients with EHRs and LLM Powered Agentic Workflow—0
Exploring Language Model Generalization in Low-Resource Extractive QACode0
Charting the Future: Using Chart Question-Answering for Scalable Evaluation of LLM-Driven Data Visualizations—0
Enhancing Explainability in Multimodal Large Language Models Using Ontological Context—0
DisGeM: Distractor Generation for Multiple Choice Questions with Span MaskingCode0
Efficient In-Domain Question Answering for Resource-Constrained Environments—0
Integrating Hierarchical Semantic into Iterative Generation Model for Entailment Tree Explanation—0
Robotic Environmental State Recognition with Pre-Trained Vision-Language Models and Black-Box Optimization—0
Episodic Memory Verbalization using Hierarchical Representations of Life-Long Robot Experience—0
ZALM3: Zero-Shot Enhancement of Vision-Language Alignment via In-Context Information in Multi-Turn Multimodal Medical Dialogue—0
T3: A Novel Zero-shot Transfer Learning Framework Iteratively Training on an Assistant Task for a Target Task—0
Uni-Med: A Unified Medical Generalist Foundation Model For Multi-Task Learning Via Connector-MoECode1
E.T. Bench: Towards Open-Ended Event-Level Video-Language UnderstandingCode2
DARE: Diverse Visual Question Answering with Robustness Evaluation—0
Enhancing Post-Hoc Attributions in Long Document Comprehension via Coarse Grained Answer Decomposition—0
SynTQA: Synergistic Table-based Question Answering via Mixture of Text-to-SQL and E2E TQACode0
Detecting Temporal Ambiguity in QuestionsCode0
Enhancing Temporal Sensitivity and Reasoning for Time-Sensitive Question Answering—0
Unlocking Markets: A Multilingual Benchmark to Cross-Market Question AnsweringCode0
Konstruktor: A Strong Baseline for Simple Knowledge Graph Question AnsweringCode0
Lighter And Better: Towards Flexible Context Adaptation For Retrieval Augmented Generation—0
Expert-level vision-language foundation model for real-world radiology and comprehensive evaluation—0
A Unified Hallucination Mitigation Framework for Large Vision-Language ModelsCode0
Exploring Hint Generation Approaches in Open-Domain Question AnsweringCode1
From Pixels to Words: Leveraging Explainability in Face Recognition through Interactive Natural Language Processing—0
A Zero-Shot Open-Vocabulary Pipeline for Dialogue UnderstandingCode0
60 Data Points are Sufficient to Fine-Tune LLMs for Question-Answering—0
AsthmaBot: Multi-modal, Multi-Lingual Retrieval Augmented Generation For Asthma Patient Support—0
MediConfusion: Can you trust your AI radiologist? Probing the reliability of multimodal medical foundation modelsCode1
Learning When to Retrieve, What to Rewrite, and How to Respond in Conversational QA—0
Detect, Describe, Discriminate: Moving Beyond VQA for MLLM Evaluation—0
GEM-RAG: Graphical Eigen Memories For Retrieval Augmented Generation—0
Boosting Healthcare LLMs Through Retrieved ContextCode1
Using Similarity to Evaluate Factual Consistency in Summaries—0
Towards Efficient and Robust VQA-NLE Data Generation with Large Vision-Language ModelsCode0
A Preliminary Study of o1 in Medicine: Are We Closer to an AI Doctor?—0
Can CLIP Count Stars? An Empirical Study on Quantity Bias in CLIP—0
LINKAGE: Listwise Ranking among Varied-Quality References for Non-Factoid QA Evaluation via LLMs—0
Scene-Text Grounding for Text-Based Video Question AnsweringCode1
Evaluating the Performance and Robustness of LLMs in Materials Science Q&A and Property Predictions—0
Show:102550
← PrevPage 37 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