Tag: large vision-language models
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DUDE Framework: Teaching Web Agents to Resist Deceptive UIs
Discover DUDE, a novel framework that trains web agents to detect and resist deceptive interfaces, improving AI reliability by 53.8%.
Can Vision-Language Models Recognize Themselves in Mirrors?
Explore how advanced vision-language models demonstrate self-recognition using mirror tests, revealing new insights into AI self-awareness and cognition.
Reliability in Vision-Language Models: Study of Attention & Causality
Explore how attention, hidden states, and causal circuits impact reliability in vision-language models for improved AI performance and trustworthiness.
Visual Text Compression for Efficient NLP Processing
Discover how Visual Text Compression reduces tokens and boosts NLP efficiency using measure transport and vision-language models.
Consensus Entropy: Boost OCR Accuracy with Multi-VLM Agreement
Enhance OCR reliability using Consensus Entropy, a training-free method leveraging multi-VLM agreement for self-verifying, self-improving text recognition.