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 3001–3050 of 10817 papers

TitleStatusHype
The Rotary Position Embedding May Cause Dimension Inefficiency in Attention Heads for Long-Distance Retrieval—0
K-Edit: Language Model Editing with Contextual Knowledge Awareness—0
NitiBench: A Comprehensive Studies of LLM Frameworks Capabilities for Thai Legal Question AnsweringCode0
Evaluating the Meta- and Object-Level Reasoning of Large Language Models for Question Answering—0
Post-training an LLM for RAG? Train on Self-Generated Demonstrations—0
Insect-Foundation: A Foundation Model and Large Multimodal Dataset for Vision-Language Insect Understanding—0
V2V-LLM: Vehicle-to-Vehicle Cooperative Autonomous Driving with Multi-Modal Large Language Models—0
SelfCite: Self-Supervised Alignment for Context Attribution in Large Language ModelsCode0
Visual Graph Question Answering with ASP and LLMs for Language Parsing—0
Improving TCM Question Answering through Tree-Organized Self-Reflective Retrieval with LLMs—0
Abduction of Domain Relationships from Data for VQA—0
EmoAssist: Emotional Assistant for Visual Impairment Community—0
Beyond English: The Impact of Prompt Translation Strategies across Languages and Tasks in Multilingual LLMs—0
Diversity Enhances an LLM's Performance in RAG and Long-context Task—0
LP-LM: No Hallucinations in Question Answering with Logic ProgrammingCode0
On Mechanistic Circuits for Extractive Question-Answering—0
FoQA: A Faroese Question-Answering Dataset—0
Making Language Models Robust Against Negation—0
Elevating Legal LLM Responses: Harnessing Trainable Logical Structures and Semantic Knowledge with Legal ReasoningCode0
ReTreever: Tree-based Coarse-to-Fine Representations for Retrieval—0
Vision-Language Models for Edge Networks: A Comprehensive Survey—0
Who Taught You That? Tracing Teachers in Model Distillation—0
Generative Distribution Prediction: A Unified Approach to Multimodal Learning—0
RoToR: Towards More Reliable Responses for Order-Invariant InputsCode0
Learning Musical Representations for Music Performance Question AnsweringCode0
Performance Analysis of Traditional VQA Models Under Limited Computational Resources—0
ClinKD: Cross-Modal Clinical Knowledge Distiller For Multi-Task Medical ImagesCode0
Self-Training Large Language Models for Tool-Use Without Demonstrations—0
Investigating the Shortcomings of LLMs in Step-by-Step Legal ReasoningCode0
Evolving LLMs' Self-Refinement Capability via Iterative Preference Optimization—0
Uncertainty Quantification for LLMs through Minimum Bayes Risk: Bridging Confidence and Consistency—0
ARR: Question Answering with Large Language Models via Analyzing, Retrieving, and ReasoningCode0
Hummingbird: High Fidelity Image Generation via Multimodal Context Alignment—0
Efficient Knowledge Feeding to Language Models: A Novel Integrated Encoder-Decoder Architecture—0
Éclair -- Extracting Content and Layout with Integrated Reading Order for Documents—0
No Images, No Problem: Retaining Knowledge in Continual VQA with Questions-Only MemoryCode0
DocMIA: Document-Level Membership Inference Attacks against DocVQA ModelsCode0
TerraQ: Spatiotemporal Question-Answering on Satellite Image Archives—0
Efficient Few-Shot Continual Learning in Vision-Language Models—0
SMI: An Information-Theoretic Metric for Predicting Model Knowledge Solely from Pre-Training SignalsCode0
Ontology-Guided, Hybrid Prompt Learning for Generalization in Knowledge Graph Question AnsweringCode0
LLMs to Support a Domain Specific Knowledge Assistant—0
SensorChat: Answering Qualitative and Quantitative Questions during Long-Term Multimodal Sensor Interactions—0
LLMs can be easily Confused by Instructional Distractions—0
Spatial-RAG: Spatial Retrieval Augmented Generation for Real-World Geospatial Reasoning Questions—0
Exploring Spatial Language Grounding Through Referring Expressions—0
AmaSQuAD: A Benchmark for Amharic Extractive Question Answering—0
ChartCitor: Multi-Agent Framework for Fine-Grained Chart Visual Attribution—0
Memento No More: Coaching AI Agents to Master Multiple Tasks via Hints Internalization—0
Topic-FlipRAG: Topic-Orientated Adversarial Opinion Manipulation Attacks to Retrieval-Augmented Generation Models—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