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 3301–3350 of 10817 papers

TitleStatusHype
Progressive Multi-granular Alignments for Grounded Reasoning in Large Vision-Language ModelsCode0
Discrete Subgraph Sampling for Interpretable Graph based Visual Question AnsweringCode0
DialogAgent: An Auto-engagement Agent for Code Question Answering Data Production—0
Barking Up The Syntactic Tree: Enhancing VLM Training with Syntactic Losses—0
In-Context Learning with Topological Information for Knowledge Graph Completion—0
A Multimodal Social Agent—0
How Vision-Language Tasks Benefit from Large Pre-trained Models: A Survey—0
AutoPrep: Natural Language Question-Aware Data Preparation with a Multi-Agent Framework—0
RAG-based Question Answering over Heterogeneous Data and Text—0
Piece of Table: A Divide-and-Conquer Approach for Selecting Sub-Tables in Table Question Answering—0
Ontology-Aware RAG for Improved Question-Answering in Cybersecurity Education—0
MM-PoE: Multiple Choice Reasoning via. Process of Elimination using Multi-Modal ModelsCode0
PediaBench: A Comprehensive Chinese Pediatric Dataset for Benchmarking Large Language ModelsCode0
FM2DS: Few-Shot Multimodal Multihop Data Synthesis with Knowledge Distillation for Question AnsweringCode0
3D Spatial Understanding in MLLMs: Disambiguation and Evaluation—0
Ranked from Within: Ranking Large Multimodal Models for Visual Question Answering Without Labels—0
1-800-SHARED-TASKS at RegNLP: Lexical Reranking of Semantic Retrieval (LeSeR) for Regulatory Question Answering—0
An Entailment Tree Generation Approach for Multimodal Multi-Hop Question Answering with Mixture-of-Experts and Iterative Feedback Mechanism—0
Accelerating Manufacturing Scale-Up from Material Discovery Using Agentic Web Navigation and Retrieval-Augmented AI for Process Engineering Schematics Design—0
SplaXBERT: Leveraging Mixed Precision Training and Context Splitting for Question Answering—0
PromptRefine: Enhancing Few-Shot Performance on Low-Resource Indic Languages with Example Selection from Related Example Banks—0
Evaluating Hallucination in Text-to-Image Diffusion Models with Scene-Graph based Question-Answering Agent—0
SLA Management in Reconfigurable Multi-Agent RAG: A Systems Approach to Question Answering—0
Question Answering for Decisionmaking in Green Building Design: A Multimodal Data Reasoning Method Driven by Large Language Models—0
EACO: Enhancing Alignment in Multimodal LLMs via Critical Observation—0
Knowledge Graphs are all you need: Leveraging KGs in Physics Question Answering—0
Steps are all you need: Rethinking STEM Education with Prompt Engineering—0
Findings of the Second BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora—0
KaLM: Knowledge-aligned Autoregressive Language Modeling via Dual-view Knowledge Graph Contrastive Learning—0
Synergizing LLMs and Knowledge Graphs: A Novel Approach to Software Repository-Related Question Answering—0
SynFinTabs: A Dataset of Synthetic Financial Tables for Information and Table ExtractionCode0
Uniform Discretized Integrated Gradients: An effective attribution based method for explaining large language models—0
GRAF: Graph Retrieval Augmented by Facts for Romanian Legal Multi-Choice Question Answering—0
TANGO: Training-free Embodied AI Agents for Open-world Tasks—0
Addressing Hallucinations with RAG and NMISS in Italian Healthcare LLM Chatbots—0
Give me Some Hard Questions: Synthetic Data Generation for Clinical QACode0
T2I-FactualBench: Benchmarking the Factuality of Text-to-Image Models with Knowledge-Intensive Concepts—0
Comprehensive Audio Query Handling System with Integrated Expert Models and Contextual Understanding—0
RedStone: Curating General, Code, Math, and QA Data for Large Language Models—0
Survey of different Large Language Model Architectures: Trends, Benchmarks, and Challenges—0
Domain-specific Question Answering with Hybrid Search—0
CEGI: Measuring the trade-off between efficiency and carbon emissions for SLMs and VLMs—0
Semantic Tokens in Retrieval Augmented Generation—0
Enhancing Trust in Large Language Models with Uncertainty-Aware Fine-Tuning—0
An Evolutionary Large Language Model for Hallucination Mitigation—0
QA-TOOLBOX: Conversational Question-Answering for process task guidance in manufacturing—0
Hybrid-SQuAD: Hybrid Scholarly Question Answering Dataset—0
Explainable and Interpretable Multimodal Large Language Models: A Comprehensive Survey—0
Copy-Move Forgery Detection and Question Answering for Remote Sensing ImageCode0
MLD-EA: Check and Complete Narrative Coherence by Introducing Emotions and Actions—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