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cs.CL2025
VeOmni: Scaling Any Modality Model Training with Model-Centric Distributed Recipe Zoo
Qianli Ma, Yaowei Zheng, Zhelun Shi +9
Recent advances in large language models (LLMs) have driven impressive progress in omni-modal understanding and generation. However, training omni-modal LLMs remains a significant…
cs.CL2025
T2ISafety: Benchmark for Assessing Fairness, Toxicity, and Privacy in Image Generation
Lijun Li, Zhelun Shi, Xuhao Hu +5
Text-to-image (T2I) models have rapidly advanced, enabling the generation of high-quality images from text prompts across various domains. However, these models present notable saf…
cs.CL2024★ 1 cited
Systematic Reward Gap Optimization for Mitigating VLM Hallucinations
Lehan He, Zeren Chen, Zhelun Shi +3
The success of Direct Preference Optimization (DPO) in mitigating hallucinations in Vision Language Models (VLMs) critically hinges on the true reward gaps within preference pairs.…