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 151–200 of 10817 papers

TitleStatusHype
VideoCAD: A Large-Scale Video Dataset for Learning UI Interactions and 3D Reasoning from CAD SoftwareCode1
Exploring the Impact of Occupational Personas on Domain-Specific QA—0
Grid-LOGAT: Grid Based Local and Global Area Transcription for Video Question Answering—0
Light as Deception: GPT-driven Natural Relighting Against Vision-Language Pre-training Models—0
A Simple Linear Patch Revives Layer-Pruned Large Language Models—0
Vision LLMs Are Bad at Hierarchical Visual Understanding, and LLMs Are the Bottleneck—0
Drop Dropout on Single-Epoch Language Model PretrainingCode0
LGAR: Zero-Shot LLM-Guided Neural Ranking for Abstract Screening in Systematic Literature ReviewsCode0
Improving Reliability and Explainability of Medical Question Answering through Atomic Fact Checking in Retrieval-Augmented LLMs—0
Revisiting Epistemic Markers in Confidence Estimation: Can Markers Accurately Reflect Large Language Models' Uncertainty?Code0
Reinforcement Learning for Better Verbalized Confidence in Long-Form Generation—0
mRAG: Elucidating the Design Space of Multi-modal Retrieval-Augmented Generation—0
TCM-Ladder: A Benchmark for Multimodal Question Answering on Traditional Chinese Medicine—0
MedPAIR: Measuring Physicians and AI Relevance Alignment in Medical Question Answering—0
VF-Eval: Evaluating Multimodal LLMs for Generating Feedback on AIGC VideosCode0
Fortune: Formula-Driven Reinforcement Learning for Symbolic Table Reasoning in Language Models—0
Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action ModelsCode3
Diagnosing and Addressing Pitfalls in KG-RAG Datasets: Toward More Reliable Benchmarking—0
VAU-R1: Advancing Video Anomaly Understanding via Reinforcement Fine-TuningCode2
Data-efficient Meta-models for Evaluation of Context-based Questions and Answers in LLMs—0
From Chat Logs to Collective Insights: Aggregative Question Answering—0
ChartMind: A Comprehensive Benchmark for Complex Real-world Multimodal Chart Question Answering—0
Puzzled by Puzzles: When Vision-Language Models Can't Take a HintCode1
Let's Reason Formally: Natural-Formal Hybrid Reasoning Enhances LLM's Math Capability—0
QLIP: A Dynamic Quadtree Vision Prior Enhances MLLM Performance Without RetrainingCode0
Differential Information: An Information-Theoretic Perspective on Preference Optimization—0
Spoken question answering for visual queries—0
Multi-Sourced Compositional Generalization in Visual Question AnsweringCode0
Interpreting Chest X-rays Like a Radiologist: A Benchmark with Clinical ReasoningCode1
KVzip: Query-Agnostic KV Cache Compression with Context ReconstructionCode3
Synthetic Document Question Answering in HungarianCode0
3DLLM-Mem: Long-Term Spatial-Temporal Memory for Embodied 3D Large Language Model—0
EvolveSearch: An Iterative Self-Evolving Search Agent—0
Enhancing Paraphrase Type Generation: The Impact of DPO and RLHF Evaluated with Human-Ranked DataCode0
Read Your Own Mind: Reasoning Helps Surface Self-Confidence Signals in LLMs—0
Improving QA Efficiency with DistilBERT: Fine-Tuning and Inference on mobile Intel CPUs—0
Climate Finance BenchCode0
ER-REASON: A Benchmark Dataset for LLM-Based Clinical Reasoning in the Emergency Room—0
Structured Memory Mechanisms for Stable Context Representation in Large Language Models—0
NegVQA: Can Vision Language Models Understand Negation?—0
StressTest: Can YOUR Speech LM Handle the Stress?—0
VIGNETTE: Socially Grounded Bias Evaluation for Vision-Language ModelsCode0
Agent-UniRAG: A Trainable Open-Source LLM Agent Framework for Unified Retrieval-Augmented Generation Systems—0
DriveRX: A Vision-Language Reasoning Model for Cross-Task Autonomous Driving—0
FRAMES-VQA: Benchmarking Fine-Tuning Robustness across Multi-Modal Shifts in Visual Question AnsweringCode0
Rethinking Information Synthesis in Multimodal Question Answering A Multi-Agent Perspective—0
DynamicVL: Benchmarking Multimodal Large Language Models for Dynamic City Understanding—0
Silence is Not Consensus: Disrupting Agreement Bias in Multi-Agent LLMs via Catfish Agent for Clinical Decision Making—0
Understand, Think, and Answer: Advancing Visual Reasoning with Large Multimodal Models—0
SOSBENCH: Benchmarking Safety Alignment on Scientific Knowledge—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