3 papers
cs.CL2026
Reverse Constitutional AI: A Framework for Controllable Toxic Data Generation via Probability-Clamped RLAIF
Yuan Fang, Yiming Luo, Aimin Zhou +1
Ensuring the safety of large language models (LLMs) requires robust red teaming, yet the systematic synthesis of high-quality toxic data remains under-explored. We propose Reverse…
cs.CV2025
USO: Unified Style and Subject-Driven Generation via Disentangled and Reward Learning
Shaojin Wu, Mengqi Huang, Yufeng Cheng +5
Existing literature typically treats style-driven and subject-driven generation as two disjoint tasks: the former prioritizes stylistic similarity, whereas the latter insists on su…
cs.CV2025
DreamO: A Unified Framework for Image Customization
Chong Mou, Yanze Wu, Wenxu Wu +15
Recently, extensive research on image customization (e.g., identity, subject, style, background, etc.) demonstrates strong customization capabilities in large-scale generative mode…