U2Diffine augments diffusion denoising with negative log-likelihood loss and first-order uncertainty propagation to jointly perform trajectory completion and provide per-state heteroscedastic uncertainty for multi-agent paths.
Denoising diffusion probabilistic models
6 Pith papers cite this work. Polarity classification is still indexing.
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EditTransfer++ delivers state-of-the-art faithfulness to visual editing examples and faster inference by removing text conditioning during fine-tuning and applying best-worst contrastive refinement plus condition compression.
SafeRedir achieves robust unlearning of unsafe concepts in image generation models by adaptively redirecting prompt embeddings toward safe semantic regions at inference time via a multi-modal classifier and token delta generator.
SAS adds semantic scoring with CLIP and a two-stage filter-then-diversity selection process to make generative dataset distillation produce more class-discriminative and diverse compact datasets.
Predict-then-Diffuse predicts response length for diffusion LLMs before inference, cutting FLOPs with a data-driven safety buffer while preserving output quality.
citing papers explorer
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Heteroscedastic Diffusion for Multi-Agent Trajectory Modeling
U2Diffine augments diffusion denoising with negative log-likelihood loss and first-order uncertainty propagation to jointly perform trajectory completion and provide per-state heteroscedastic uncertainty for multi-agent paths.
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EditTransfer++: Toward Faithful and Efficient Visual-Prompt-Guided Image Editing
EditTransfer++ delivers state-of-the-art faithfulness to visual editing examples and faster inference by removing text conditioning during fine-tuning and applying best-worst contrastive refinement plus condition compression.
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SafeRedir: Prompt Embedding Redirection for Robust Unlearning in Image Generation Models
SafeRedir achieves robust unlearning of unsafe concepts in image generation models by adaptively redirecting prompt embeddings toward safe semantic regions at inference time via a multi-modal classifier and token delta generator.
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SAS: Semantic-aware Sampling for Generative Dataset Distillation
SAS adds semantic scoring with CLIP and a two-stage filter-then-diversity selection process to make generative dataset distillation produce more class-discriminative and diverse compact datasets.
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Predict-then-Diffuse: Adaptive Response Length for Compute-Budgeted Inference in Diffusion LLMs
Predict-then-Diffuse predicts response length for diffusion LLMs before inference, cutting FLOPs with a data-driven safety buffer while preserving output quality.
- SRC-Flow: Compact Semantic Representations Enable Normalizing Flows for Image Generation