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Hallucination

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Showing 1451–1500 of 1816 papers

TitleStatusHype
Dual-View Data Hallucination with Semantic Relation Guidance for Few-Shot Image Recognition—0
Fine-grained Hallucination Detection and Editing for Language Models—0
SH2: Self-Highlighted Hesitation Helps You Decode More TruthfullyCode0
Hallucination Benchmark in Medical Visual Question AnsweringCode0
Evidence to Generate (E2G): A Single-agent Two-step Prompting for Context Grounded and Retrieval Augmented Reasoning—0
AI Hallucinations: A Misnomer Worth Clarifying—0
LightHouse: A Survey of AGI HallucinationCode0
Navigating Uncertainty: Optimizing API Dependency for Hallucination Reduction in Closed-Book Question Answering—0
Question-Answering Based Summarization of Electronic Health Records using Retrieval Augmented Generation—0
Hallucinations in Neural Automatic Speech Recognition: Identifying Errors and Hallucinatory Models—0
A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language ModelsCode0
VISTA-LLAMA: Reducing Hallucination in Video Language Models via Equal Distance to Visual Tokens—0
Do Androids Know They're Only Dreaming of Electric Sheep?—0
KnowledgeNavigator: Leveraging Large Language Models for Enhanced Reasoning over Knowledge Graph—0
Dynamic In-Context Learning from Nearest Neighbors for Bundle Generation—0
Don't Believe Everything You Read: Enhancing Summarization Interpretability through Automatic Identification of Hallucinations in Large Language Models—0
Theory of Hallucinations based on Equivariance—0
Reducing Hallucinations: Enhancing VQA for Flood Disaster Damage Assessment with Visual Contexts—0
Experimenting with Large Language Models and vector embeddings in NASA SciX—0
Quantifying Bias in Text-to-Image Generative Models—0
MELO: Enhancing Model Editing with Neuron-Indexed Dynamic LoRACode0
Silkie: Preference Distillation for Large Visual Language Models—0
Towards Verifiable Text Generation with Evolving Memory and Self-Reflection—0
Improving Factual Error Correction by Learning to Inject Factual ErrorsCode0
Vista-LLaMA: Reliable Video Narrator via Equal Distance to Visual Tokens—0
Evaluating ChatGPT as a Question Answering System: A Comprehensive Analysis and Comparison with Existing Models—0
Context Tuning for Retrieval Augmented Generation—0
DelucionQA: Detecting Hallucinations in Domain-specific Question Answering—0
HALO: An Ontology for Representing and Categorizing Hallucinations in Large Language Models—0
Behind the Magic, MERLIM: Multi-modal Evaluation Benchmark for Large Image-Language ModelsCode0
On Exploring the Reasoning Capability of Large Language Models with Knowledge Graphs—0
How to Build an AI Tutor That Can Adapt to Any Course Using Knowledge Graph-Enhanced Retrieval-Augmented Generation (KG-RAG)—0
Understanding Your Agent: Leveraging Large Language Models for Behavior Explanation—0
Combating the "Sameness" in AI Art: Reflections on the Interactive AI Installation Fencing Hallucination—0
Mitigating Hallucination in Visual Language Models with Visual Supervision—0
Deficiency of Large Language Models in Finance: An Empirical Examination of Hallucination—0
Calibrated Language Models Must Hallucinate—0
Controlling Large Language Model-based Agents for Large-Scale Decision-Making: An Actor-Critic Approach—0
Challenges of Large Language Models for Mental Health Counseling—0
Minimizing Factual Inconsistency and Hallucination in Large Language Models—0
Mitigating Large Language Model Hallucinations via Autonomous Knowledge Graph-based Retrofitting—0
KNVQA: A Benchmark for evaluation knowledge-based VQA—0
Adapting LLMs for Efficient, Personalized Information Retrieval: Methods and Implications—0
Control in Hybrid Chatbots—0
GPT-4V(ision) for Robotics: Multimodal Task Planning from Human Demonstration—0
Chain of Visual Perception: Harnessing Multimodal Large Language Models for Zero-shot Camouflaged Object DetectionCode0
Journey of Hallucination-minimized Generative AI Solutions for Financial Decision Makers—0
Crafting In-context Examples according to LMs' Parametric KnowledgeCode0
Deceptive Semantic Shortcuts on Reasoning Chains: How Far Can Models Go without Hallucination?Code0
How Trustworthy are Open-Source LLMs? An Assessment under Malicious Demonstrations Shows their VulnerabilitiesCode0
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