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 701–725 of 10817 papers

TitleStatusHype
Knowledge-Aware Iterative Retrieval for Multi-Agent Systems—0
Logic-in-Frames: Dynamic Keyframe Search via Visual Semantic-Logical Verification for Long Video Understanding—0
From Head to Tail: Towards Balanced Representation in Large Vision-Language Models through Adaptive Data Calibration—0
Omnia de EgoTempo: Benchmarking Temporal Understanding of Multi-Modal LLMs in Egocentric VideosCode1
MicroVQA: A Multimodal Reasoning Benchmark for Microscopy-Based Scientific ResearchCode1
Long-VMNet: Accelerating Long-Form Video Understanding via Fixed Memory—0
Task-Oriented Feature Compression for Multimodal Understanding via Device-Edge Co-Inference—0
MAP: Evaluation and Multi-Agent Enhancement of Large Language Models for Inpatient Pathways—0
Sightation Counts: Leveraging Sighted User Feedback in Building a BLV-aligned Dataset of Diagram Descriptions—0
General Table Question Answering via Answer-Formula Joint Generation—0
GeoRSMLLM: A Multimodal Large Language Model for Vision-Language Tasks in Geoscience and Remote Sensing—0
PEBench: A Fictitious Dataset to Benchmark Machine Unlearning for Multimodal Large Language Models—0
DynRsl-VLM: Enhancing Autonomous Driving Perception with Dynamic Resolution Vision-Language Models—0
Beyond the Destination: A Novel Benchmark for Exploration-Aware Embodied Question Answering—0
UMB@PerAnsSumm 2025: Enhancing Perspective-Aware Summarization with Prompt Optimization and Supervised Fine-Tuning—0
T2I-FineEval: Fine-Grained Compositional Metric for Text-to-Image EvaluationCode0
MUSS: Multilevel Subset Selection for Relevance and Diversity—0
Reinforcement Learning Outperforms Supervised Fine-Tuning: A Case Study on Audio Question AnsweringCode3
Learning to Inference Adaptively for Multimodal Large Language Models—0
KV-Distill: Nearly Lossless Learnable Context Compression for LLMs—0
TIME: Temporal-sensitive Multi-dimensional Instruction Tuning and Benchmarking for Video-LLMs—0
How Do Multimodal Large Language Models Handle Complex Multimodal Reasoning? Placing Them in An Extensible Escape GameCode1
Unlock the Power of Unlabeled Data in Language Driving Model—0
DriveLMM-o1: A Step-by-Step Reasoning Dataset and Large Multimodal Model for Driving Scenario UnderstandingCode2
Retrieval-Augmented Generation with Hierarchical KnowledgeCode4
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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