ROT: Rotating Hidden States towards Contextual Vectors for Hallucination Mitigation in LVLMs
cs.CV, cs.AI, cs.CL
Submitted: 2026-10-05
Updated: 2026-10-05
Terminology
Sources
- Qwen2.5-VL Technical Report
- Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic
- HALC: Object Hallucination Reduction via Adaptive Focal-Contrast Decoding
- Enhancing Vision-Language Model Reliability with Uncertainty-Guided Dropout Decoding
- Self-Introspective Decoding: Alleviating Hallucinations for Large Vision-Language Models
- See What You Are Told: Visual Attention Sink in Large Multimodal Models
- VisualBERT: A Simple and Performant Baseline for Vision and Language
- Correcting Visual Blur Induced by Attention Distraction to Reduce Hallucinations: Algorithm and Theory
- A Survey on Hallucination in Large Vision-Language Models
- Do All Individual Layers Help? An Empirical Study of Task-Interfering Layers in Vision-Language Models
- Evaluation and Analysis of Hallucination in Large Vision-Language Models
- Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
- Seeing Clearly by Layer Two: Enhancing Attention Heads to Alleviate Hallucination in LVLMs
- Hallucination Begins Where Saliency Drops
- Mitigating Object Hallucination in Large Vision-Language Models via Image-Grounded Guidance
- Analyzing and Mitigating Object Hallucination in Large Vision-Language Models
- Look Twice Before You Answer: Memory-Space Visual Retracing for Hallucination Mitigation in Multimodal Large Language Models
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