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 1726–1750 of 10817 papers

TitleStatusHype
TEOChat: A Large Vision-Language Assistant for Temporal Earth Observation DataCode2
ActionAtlas: A VideoQA Benchmark for Domain-specialized Action Recognition—0
PDF-WuKong: A Large Multimodal Model for Efficient Long PDF Reading with End-to-End Sparse SamplingCode2
Beyond Captioning: Task-Specific Prompting for Improved VLM Performance in Mathematical Reasoning—0
Temporal Reasoning Transfer from Text to Video—0
Enhancing Temporal Modeling of Video LLMs via Time GatingCode0
ERVQA: A Dataset to Benchmark the Readiness of Large Vision Language Models in Hospital EnvironmentsCode0
Multimodal Large Language Models and Tunings: Vision, Language, Sensors, Audio, and BeyondCode0
Information Discovery in e-Commerce—0
Core Tokensets for Data-efficient Sequential Training of TransformersCode0
Document-level Causal Relation Extraction with Knowledge-guided Binary Question Answering—0
Differential TransformerCode2
Mitigating the Risk of Health Inequity Exacerbated by Large Language Models—0
ZEBRA: Zero-Shot Example-Based Retrieval Augmentation for Commonsense Question AnsweringCode1
MM-R^3: On (In-)Consistency of Multi-modal Large Language Models (MLLMs)—0
ActiView: Evaluating Active Perception Ability for Multimodal Large Language ModelsCode1
CasiMedicos-Arg: A Medical Question Answering Dataset Annotated with Explanatory Argumentative StructuresCode0
Precise Model Benchmarking with Only a Few Observations—0
VLM2Vec: Training Vision-Language Models for Massive Multimodal Embedding Tasks—0
FAMMA: A Benchmark for Financial Domain Multilingual Multimodal Question AnsweringCode0
MC-CoT: A Modular Collaborative CoT Framework for Zero-shot Medical-VQA with LLM and MLLM IntegrationCode1
Optimizing AI Reasoning: A Hamiltonian Dynamics Approach to Multi-Hop Question AnsweringCode0
Adaptive Question Answering: Enhancing Language Model Proficiency for Addressing Knowledge Conflicts with Source Citations—0
Overview of Factify5WQA: Fact Verification through 5W Question-Answering—0
Beyond Forecasting: Compositional Time Series Reasoning for End-to-End Task Execution—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