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Paper: PAINT: PAYING ATTENTION TO INFORMED TOKENS TO MITIGATE HALLUCINATION IN LARGE VISION-LANGUAGE MODEL
The main features of hasanar1f/paint are: Mitigation Methods.
Projects with overlapping indexed features include: anonymousanoy/fohe — In Stage 1, the Keyword Extraction Prompt instructs ChatGPT to generate verbs, nouns, and adjectives (highlighted in… billchan226/halc — [ICML 2024] Official implementation for "HALC: Object Hallucination Reduction via Adaptive Focal-Contrast Decoding". bradyfu/woodpecker — ✨✨Woodpecker: Hallucination Correction for Multimodal Large Language Models. damo-nlp-sg/vcd — [CVPR 2024 Highlight] Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive… fatemehpesaran310/lpoi — Official PyTorch implementation of "LPOI: Listwise Preference Optimization for Vision Language Models", (ACL 2025 Main). 1zhou-wang/memvr — [ICML 2025] Official implementation of paper 'Look Twice Before You Answer: Memory-Space Visual Retracing for…
In Stage 1, the Keyword Extraction Prompt instructs ChatGPT to generate verbs, nouns, and adjectives (highlighted in brown) from the original caption. In Stage 2, the Caption Generation Prompt guides ChatGPT to generate a rewritten caption. By iteratively applying this prompt, multiple rewritten…
ICML 2024 Official implementation for "HALC: Object Hallucination Reduction via Adaptive Focal-Contrast Decoding"
✨✨Woodpecker: Hallucination Correction for Multimodal Large Language Models
ICML 2025 Official implementation of paper 'Look Twice Before You Answer: Memory-Space Visual Retracing for Hallucination Mitigation in Multimodal Large Language Models'.