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 2901–2950 of 10817 papers

TitleStatusHype
ER-RAG: Enhance RAG with ER-Based Unified Modeling of Heterogeneous Data Sources—0
CL-MoE: Enhancing Multimodal Large Language Model with Dual Momentum Mixture-of-Experts for Continual Visual Question Answering—0
AILS-NTUA at SemEval-2025 Task 8: Language-to-Code prompting and Error Fixing for Tabular Question AnsweringCode0
GlossGPT: GPT for Word Sense Disambiguation using Few-shot Chain-of-Thought PromptingCode0
PreMind: Multi-Agent Video Understanding for Advanced Indexing of Presentation-style Videos—0
TempRetriever: Fusion-based Temporal Dense Passage Retrieval for Time-Sensitive Questions—0
MedHallTune: An Instruction-Tuning Benchmark for Mitigating Medical Hallucination in Vision-Language ModelsCode0
Fine-Grained Retrieval-Augmented Generation for Visual Question Answering—0
WebFAQ: A Multilingual Collection of Natural Q&A Datasets for Dense Retrieval—0
Can Large Language Models Unveil the Mysteries? An Exploration of Their Ability to Unlock Information in Complex Scenarios—0
Bisecting K-Means in RAG for Enhancing Question-Answering Tasks Performance in Telecommunications—0
M-LLM Based Video Frame Selection for Efficient Video Understanding—0
Med-RLVR: Emerging Medical Reasoning from a 3B base model via reinforcement Learning—0
From Retrieval to Generation: Comparing Different Approaches—0
Few-Shot Multilingual Open-Domain QA from 5 ExamplesCode0
Protecting multimodal large language models against misleading visualizationsCode0
Nexus: An Omni-Perceptive And -Interactive Model for Language, Audio, And Vision—0
MEBench: Benchmarking Large Language Models for Cross-Document Multi-Entity Question Answering—0
MedVLM-R1: Incentivizing Medical Reasoning Capability of Vision-Language Models (VLMs) via Reinforcement Learning—0
Winning Big with Small Models: Knowledge Distillation vs. Self-Training for Reducing Hallucination in QA Agents—0
Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement—0
Talking to the brain: Using Large Language Models as Proxies to Model Brain Semantic Representation—0
END: Early Noise Dropping for Efficient and Effective Context Denoising—0
Uncertainty Quantification in Retrieval Augmented Question AnsweringCode0
Tip of the Tongue Query Elicitation for Simulated EvaluationCode0
Say Less, Mean More: Leveraging Pragmatics in Retrieval-Augmented Generation—0
Detecting Knowledge Boundary of Vision Large Language Models by Sampling-Based InferenceCode0
FilterRAG: Zero-Shot Informed Retrieval-Augmented Generation to Mitigate Hallucinations in VQA—0
SECURA: Sigmoid-Enhanced CUR Decomposition with Uninterrupted Retention and Low-Rank Adaptation in Large Language Models—0
KiRAG: Knowledge-Driven Iterative Retriever for Enhancing Retrieval-Augmented Generation—0
All-in-one: Understanding and Generation in Multimodal Reasoning with the MAIA Benchmark—0
Evaluating the Effect of Retrieval Augmentation on Social Biases—0
AAD-LLM: Neural Attention-Driven Auditory Scene Understanding—0
MULTITAT: Benchmarking Multilingual Table-and-Text Question AnsweringCode0
MultiOCR-QA: Dataset for Evaluating Robustness of LLMs in Question Answering on Multilingual OCR TextsCode0
Retrieval-Augmented Visual Question Answering via Built-in Autoregressive Search Engines—0
Tracking the Copyright of Large Vision-Language Models through Parameter Learning Adversarial Images—0
Visual-RAG: Benchmarking Text-to-Image Retrieval Augmented Generation for Visual Knowledge Intensive QueriesCode0
MQADet: A Plug-and-Play Paradigm for Enhancing Open-Vocabulary Object Detection via Multimodal Question Answering—0
Wrong Answers Can Also Be Useful: PlausibleQA -- A Large-Scale QA Dataset with Answer Plausibility ScoresCode0
Uncertainty-Aware Fusion: An Ensemble Framework for Mitigating Hallucinations in Large Language Models—0
EPERM: An Evidence Path Enhanced Reasoning Model for Knowledge Graph Question and Answering—0
Echo: A Large Language Model with Temporal Episodic Memory—0
MHQA: A Diverse, Knowledge Intensive Mental Health Question Answering Challenge for Language Models—0
Superintelligent Agents Pose Catastrophic Risks: Can Scientist AI Offer a Safer Path?—0
Chats-Grid: An Iterative Retrieval Q&A Optimization Scheme Leveraging Large Model and Retrieval Enhancement Generation in smart grid—0
Empowering LLMs with Logical Reasoning: A Comprehensive Survey—0
TransMamba: Fast Universal Architecture Adaption from Transformers to Mamba—0
Improving Consistency in Large Language Models through Chain of GuidanceCode0
Directional Gradient Projection for Robust Fine-Tuning of Foundation Models—0
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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