A technique for controllable diversity in text-to-image generation by inducing structured semantic variations at the prompt level via VLM and agentic workflow.
ArcFace: Additive Angular Margin Loss for Deep Face Recognition , volume=
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FaceParts performs unsupervised segmentation of facial features in Gaussian Splatting avatars and supports precise editing and cross-avatar part transfer using feature disentanglement, density clustering, and FLAME anchoring.
PoLAR imposes radial structure on latent actions in hyperbolic space to factorize extent and mode, improving robot policy performance over baselines.
Sparse Concept Anchoring biases neural latent spaces toward targeted concepts using under 0.1% labels per concept, enabling reversible steering via projection and permanent removal via weight ablation with minimal side effects on other features.
Nanomind decomposes LMMs into modular bricks mapped to heterogeneous accelerators with TABM zero-copy transfers, fused low-bit kernels, and a battery-aware scheduler, cutting energy 42.3% and enabling 18.8-hour runtime on a 2000 mAh battery for LLaVA-OneVision-Qwen2-0.5B.
citing papers explorer
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Semantic Browsing: Controllable Diversity for Image Generation
A technique for controllable diversity in text-to-image generation by inducing structured semantic variations at the prompt level via VLM and agentic workflow.
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FaceParts: Segmentation and Editing of Gaussian Splatting
FaceParts performs unsupervised segmentation of facial features in Gaussian Splatting avatars and supports precise editing and cross-avatar part transfer using feature disentanglement, density clustering, and FLAME anchoring.
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PoLAR: Factorizing Extent and Mode in Latent Actions for Robot Policy Learning
PoLAR imposes radial structure on latent actions in hyperbolic space to factorize extent and mode, improving robot policy performance over baselines.
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Sparse Concept Anchoring for Interpretable and Controllable Neural Representations
Sparse Concept Anchoring biases neural latent spaces toward targeted concepts using under 0.1% labels per concept, enabling reversible steering via projection and permanent removal via weight ablation with minimal side effects on other features.
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Tiny but Mighty: A Software-Hardware Co-Design Approach for Efficient Multimodal Inference on Battery-Powered Small Devices
Nanomind decomposes LMMs into modular bricks mapped to heterogeneous accelerators with TABM zero-copy transfers, fused low-bit kernels, and a battery-aware scheduler, cutting energy 42.3% and enabling 18.8-hour runtime on a 2000 mAh battery for LLaVA-OneVision-Qwen2-0.5B.