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Hallucination

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Showing 701–750 of 1816 papers

TitleStatusHype
BordIRlines: A Dataset for Evaluating Cross-lingual Retrieval-Augmented GenerationCode0
Enhancing Training Data Attribution for Large Language Models with Fitting Error Consideration—0
The Labyrinth of Links: Navigating the Associative Maze of Multi-modal LLMs—0
FactAlign: Long-form Factuality Alignment of Large Language ModelsCode1
LMOD: A Large Multimodal Ophthalmology Dataset and Benchmark for Large Vision-Language Models—0
ScVLM: Enhancing Vision-Language Model for Safety-Critical Event UnderstandingCode0
VideoCLIP-XL: Advancing Long Description Understanding for Video CLIP Models—0
Ingest-And-Ground: Dispelling Hallucinations from Continually-Pretrained LLMs with RAG—0
FaithEval: Can Your Language Model Stay Faithful to Context, Even If "The Moon is Made of Marshmallows"Code2
Contrastive Token Learning with Similarity Decay for Repetition Suppression in Machine Translation—0
HELPD: Mitigating Hallucination of LVLMs by Hierarchical Feedback Learning with Vision-enhanced Penalty DecodingCode0
LLM Hallucinations in Practical Code Generation: Phenomena, Mechanism, and MitigationCode0
MedHalu: Hallucinations in Responses to Healthcare Queries by Large Language Models—0
DENEB: A Hallucination-Robust Automatic Evaluation Metric for Image Captioning—0
HaloScope: Harnessing Unlabeled LLM Generations for Hallucination DetectionCode0
Enhancing Guardrails for Safe and Secure Healthcare AI—0
RoleBreak: Character Hallucination as a Jailbreak Attack in Role-Playing Systems—0
Pre-trained Language Models Return Distinguishable Probability Distributions to Unfaithfully Hallucinated TextsCode0
EventHallusion: Diagnosing Event Hallucinations in Video LLMsCode1
XTRUST: On the Multilingual Trustworthiness of Large Language ModelsCode1
A Unified Hallucination Mitigation Framework for Large Vision-Language ModelsCode0
Controlling Risk of Retrieval-augmented Generation: A Counterfactual Prompting FrameworkCode0
Long-horizon Embodied Planning with Implicit Logical Inference and Hallucination Mitigation—0
Planning in the Dark: LLM-Symbolic Planning Pipeline without Experts—0
AsthmaBot: Multi-modal, Multi-Lingual Retrieval Augmented Generation For Asthma Patient Support—0
Enhancing Text-to-SQL Capabilities of Large Language Models via Domain Database Knowledge Injection—0
Parse Trees Guided LLM Prompt CompressionCode0
A Preliminary Study of o1 in Medicine: Are We Closer to an AI Doctor?—0
Enhancing Scientific Reproducibility Through Automated BioCompute Object Creation Using Retrieval-Augmented Generation from Publications—0
Effectively Enhancing Vision Language Large Models by Prompt Augmentation and Caption UtilizationCode0
Contrastive Learning for Knowledge-Based Question Generation in Large Language Models—0
FAIR GPT: A virtual consultant for research data management in ChatGPTCode1
A Multiple-Fill-in-the-Blank Exam Approach for Enhancing Zero-Resource Hallucination Detection in Large Language Models—0
FIHA: Autonomous Hallucination Evaluation in Vision-Language Models with Davidson Scene Graphs—0
JourneyBench: A Challenging One-Stop Vision-Language Understanding Benchmark of Generated ImagesCode0
Textualized Agent-Style Reasoning for Complex Tasks by Multiple Round LLM Generation—0
LLMs Can Check Their Own Results to Mitigate Hallucinations in Traffic Understanding Tasks—0
Evaluating Image Hallucination in Text-to-Image Generation with Question-AnsweringCode1
Depth-based Privileged Information for Boosting 3D Human Pose Estimation on RGB—0
Zero-resource Hallucination Detection for Text Generation via Graph-based Contextual Knowledge Triples Modeling—0
Exploring the Trade-Offs: Quantization Methods, Task Difficulty, and Model Size in Large Language Models From Edge to GiantCode0
THaMES: An End-to-End Tool for Hallucination Mitigation and Evaluation in Large Language ModelsCode0
Optimizing Resource Consumption in Diffusion Models through Hallucination Early Detection—0
SFR-RAG: Towards Contextually Faithful LLMs—0
Trustworthiness in Retrieval-Augmented Generation Systems: A SurveyCode1
HALO: Hallucination Analysis and Learning Optimization to Empower LLMs with Retrieval-Augmented Context for Guided Clinical Decision MakingCode0
Confidence Estimation for LLM-Based Dialogue State TrackingCode0
Explore the Hallucination on Low-level Perception for MLLMs—0
ODE: Open-Set Evaluation of Hallucinations in Multimodal Large Language Models—0
Winning Solution For Meta KDD Cup' 24—0
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