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Hallucination

Papers

Showing 501525 of 1816 papers

TitleStatusHype
HalluCana: Fixing LLM Hallucination with A Canary Lookahead0
Hallucination Elimination and Semantic Enhancement Framework for Vision-Language Models in Traffic ScenariosCode0
Granite GuardianCode2
Delve into Visual Contrastive Decoding for Hallucination Mitigation of Large Vision-Language ModelsCode0
Methods for Legal Citation Prediction in the Age of LLMs: An Australian Law Case Study0
Evaluating Hallucination in Text-to-Image Diffusion Models with Scene-Graph based Question-Answering Agent0
Multi-Objective Alignment of Large Language Models Through Hypervolume Maximization0
Steps are all you need: Rethinking STEM Education with Prompt Engineering0
TOBUGraph: Knowledge Graph-Based Retrieval for Enhanced LLM Performance Beyond RAG0
100% Elimination of Hallucinations on RAGTruth for GPT-4 and GPT-3.5 Turbo0
Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling0
Verb Mirage: Unveiling and Assessing Verb Concept Hallucinations in Multimodal Large Language Models0
LLM-Align: Utilizing Large Language Models for Entity Alignment in Knowledge Graphs0
Reducing Tool Hallucination via Reliability Alignment0
GenMAC: Compositional Text-to-Video Generation with Multi-Agent Collaboration0
Florence-VL: Enhancing Vision-Language Models with Generative Vision Encoder and Depth-Breadth FusionCode3
Deep priors for satellite image restoration with accurate uncertainties0
Who Brings the Frisbee: Probing Hidden Hallucination Factors in Large Vision-Language Model via Causality Analysis0
VidHalluc: Evaluating Temporal Hallucinations in Multimodal Large Language Models for Video Understanding0
An Evolutionary Large Language Model for Hallucination Mitigation0
CC-OCR: A Comprehensive and Challenging OCR Benchmark for Evaluating Large Multimodal Models in Literacy0
AI Benchmarks and Datasets for LLM Evaluation0
Automating Feedback Analysis in Surgical Training: Detection, Categorization, and AssessmentCode0
Beyond Logit Lens: Contextual Embeddings for Robust Hallucination Detection & Grounding in VLMs0
OPCap:Object-aware Prompting Captioning0
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