Manabu Okumura

Experimental results and analyses show that IMFD improves multi-face forgery detection by integrating face bounding boxes into the instruction, and consistently outperforms various state-of-the-art methods.

Instead of stuffing raw context with dialogue history or brittle retrieval vectors, treating user personalization as particle-filtered hypothesis tracing over natural language resolves the tension between fleeting intent and long-term preferences.

Text-to-image models consistently misinterpret similes, revealing a critical gap in their understanding of figurative language that could undermine their effectiveness in creative applications.