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cs.CV2026
Learning to Focus and Precise Cropping: A Reinforcement Learning Framework with Information Gaps and Grounding Loss for MLLMs
Xuanpu Zhao, Zhentao Tan, Dianmo Sheng +6
To enhance the perception and reasoning capabilities of multimodal large language models in complex visual scenes, recent research has introduced agent-based workflows. In these wo…
cs.CV2026
SoulX-FlashHead: Oracle-guided Generation of Infinite Real-time Streaming Talking Heads
Tan Yu, Qian Qiao, Le Shen +9
Achieving a balance between high-fidelity visual quality and low-latency streaming remains a formidable challenge in audio-driven portrait generation. Existing large-scale models o…
cs.CV2026
SAPL: Semantic-Agnostic Prompt Learning in CLIP for Weakly Supervised Image Manipulation Localization
Xinghao Wang, Changtao Miao, Dianmo Sheng +6
Malicious image manipulation threatens public safety and requires efficient localization methods. Existing approaches depend on costly pixel-level annotations which make training e…