Graph representation learning plus iterative augmented Lagrangian optimization creates stronger, harder-to-detect model manipulation attacks on federated LLM fine-tuning, cutting global accuracy by up to 26%.
Parameter-efficient fine-tuning of large-scale pre-trained language models
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CreatiParser decomposes raster graphic designs into editable text, background, and sticker layers via a hybrid VLM-diffusion model with ParserReward and GRPO optimization, reporting 23.7% average metric gains on Parser-40K and Crello datasets.
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Graph Representation Learning Augmented Model Manipulation on Federated Fine-Tuning of LLMs
Graph representation learning plus iterative augmented Lagrangian optimization creates stronger, harder-to-detect model manipulation attacks on federated LLM fine-tuning, cutting global accuracy by up to 26%.
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CreatiParser: Generative Image Parsing of Raster Graphic Designs into Editable Layers
CreatiParser decomposes raster graphic designs into editable text, background, and sticker layers via a hybrid VLM-diffusion model with ParserReward and GRPO optimization, reporting 23.7% average metric gains on Parser-40K and Crello datasets.