most citedForgetMe: Evaluating Selective Forgetting in Generative Models

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cs.CV2026

DeCorStory: Gram-Schmidt Prompt Embedding Decorrelation for Consistent Storytelling

Ayushman Sarkar, Zhenyu Yu, Mohd Yamani Idna Idris

Maintaining visual and semantic consistency across frames is a key challenge in text-to-image storytelling. Existing training-free methods, such as One-Prompt-One-Story, concatenat…

cs.CV2026

StoryState: Agent-Based State Control for Consistent and Editable Storybooks

Ayushman Sarkar, Zhenyu Yu, Wei Tang +3

Large multimodal models have enabled one-click storybook generation, where users provide a short description and receive a multi-page illustrated story. However, the underlying sto…

cs.CV2026

ReDiStory: Region-Disentangled Diffusion for Consistent Visual Story Generation

Ayushman Sarkar, Zhenyu Yu, Chu Chen +3

Generating coherent visual stories requires maintaining subject identity across multiple images while preserving frame-specific semantics. Recent training-free methods concatenate…

cs.CV2025

Reasoning in Computer Vision: Taxonomy, Models, Tasks, and Methodologies

Ayushman Sarkar, Zhenyu Yu, Mohd Yamani Idna Idris

Visual reasoning matters for many computer vision tasks that go beyond surface-level object detection and classification. Despite progress in relational, symbolic, temporal, causal…

cs.CV2025

From Physics to Foundation Models: A Review of AI-Driven Quantitative Remote Sensing Inversion

Zhenyu Yu, Mohd Yamani Idna Idris, Hua Wang +3

Quantitative remote sensing inversion aims to estimate continuous surface variables-such as biomass, vegetation indices, and evapotranspiration-from satellite observations, support…

cs.CV2025

A Layered Self-Supervised Knowledge Distillation Framework for Efficient Multimodal Learning on the Edge

Tarique Dahri, Zulfiqar Ali Memon, Zhenyu Yu +6

We introduce Layered Self-Supervised Knowledge Distillation (LSSKD) framework for training compact deep learning models. Unlike traditional methods that rely on pre-trained teacher…