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 1276–1300 of 10817 papers

TitleStatusHype
Evidence Contextualization and Counterfactual Attribution for Conversational QA over Heterogeneous Data with RAG Systems—0
Benchmarking Table Comprehension In The Wild—0
LLM Distillation for Efficient Few-Shot Multiple Choice Question Answering—0
Lost in the Middle, and In-Between: Enhancing Language Models' Ability to Reason Over Long Contexts in Multi-Hop QACode0
VLR-Bench: Multilingual Benchmark Dataset for Vision-Language Retrieval Augmented Generation—0
IQViC: In-context, Question Adaptive Vision Compressor for Long-term Video Understanding LMMs—0
DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal UnderstandingCode9
RETQA: A Large-Scale Open-Domain Tabular Question Answering Dataset for Real Estate SectorCode1
OG-RAG: Ontology-Grounded Retrieval-Augmented Generation For Large Language Models—0
ViCaS: A Dataset for Combining Holistic and Pixel-level Video Understanding using Captions with Grounded Segmentation—0
ViUniT: Visual Unit Tests for More Robust Visual Programming—0
Unifying AI Tutor Evaluation: An Evaluation Taxonomy for Pedagogical Ability Assessment of LLM-Powered AI TutorsCode1
Multi-Scale Heterogeneous Text-Attributed Graph Datasets From Diverse DomainsCode0
Assessing the Robustness of Retrieval-Augmented Generation Systems in K-12 Educational Question Answering with Knowledge Discrepancies—0
Neptune: The Long Orbit to Benchmarking Long Video UnderstandingCode2
Foundation Models and Adaptive Feature Selection: A Synergistic Approach to Video Question Answering—0
Towards a Multimodal Large Language Model with Pixel-Level Insight for BiomedicineCode2
Doe-1: Closed-Loop Autonomous Driving with Large World ModelCode2
A Multimodal Social Agent—0
DialogAgent: An Auto-engagement Agent for Code Question Answering Data Production—0
Can We Generate Visual Programs Without Prompting LLMs?—0
Progressive Multi-granular Alignments for Grounded Reasoning in Large Vision-Language ModelsCode0
In-Context Learning with Topological Information for Knowledge Graph Completion—0
Illusory VQA: Benchmarking and Enhancing Multimodal Models on Visual IllusionsCode0
Discrete Subgraph Sampling for Interpretable Graph based Visual Question AnsweringCode0
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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