Enabling privacy-preserving AI training on everyday devices
A new method could bring more accurate and efficient AI models to high-stakes applications like health care and finance, even in under-resourced settings.
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Improving Diversity in Black-box Few-shot Knowledge Distillation
arXiv:2604.25795v1 Announce Type: cross Abstract: Knowledge distillation (KD) is a well-known technique to effectively compress a large network (teacher) to a smaller network (student) with little sacrifice in performance. However, most KD methods require a large training set and internal…
Is the Modality Gap a Bug or a Feature? A Robustness Perspective
arXiv:2603.29080v2 Announce Type: replace-cross Abstract: Many modern multi-modal models (e.g. CLIP) seek an embedding space in which the two modalities are aligned. Somewhat surprisingly, almost all existing models show a strong modality gap: the distribution of images is well-separated from…
Egocentric Tactile and Proximity Sensors as Observation Priors for Humanoid Collision Avoidance
arXiv:2604.25554v1 Announce Type: cross Abstract: Collision-free motion is often aided by tactile and proximity sensors distributed on the body of the robot due to their resistance to occlusion as opposed to external cameras. However, how to shape the sensor’s properties,…
Enabling privacy-preserving AI training on everyday devices
A new method could bring more accurate and efficient AI models to high-stakes applications like health care and finance, even in under-resourced settings.
Improving Diversity in Black-box Few-shot Knowledge Distillation
arXiv:2604.25795v1 Announce Type: cross Abstract: Knowledge distillation (KD) is a well-known technique to effectively compress a large network (teacher) to a smaller network (student) with little sacrifice in performance. However, most KD methods require a large training set and internal…
Enabling privacy-preserving AI training on everyday devices
A new method could bring more accurate and efficient AI models to high-stakes applications like health care and finance, even in under-resourced settings.
Improving Diversity in Black-box Few-shot Knowledge Distillation
arXiv:2604.25795v1 Announce Type: cross Abstract: Knowledge distillation (KD) is a well-known technique to effectively compress a large network (teacher) to a smaller network (student) with little sacrifice in performance. However, most KD methods require a large training set and internal…
Is the Modality Gap a Bug or a Feature? A Robustness Perspective
arXiv:2603.29080v2 Announce Type: replace-cross Abstract: Many modern multi-modal models (e.g. CLIP) seek an embedding space in which the two modalities are aligned. Somewhat surprisingly, almost all existing models show a strong modality gap: the distribution of images is well-separated from…
Egocentric Tactile and Proximity Sensors as Observation Priors for Humanoid Collision Avoidance
arXiv:2604.25554v1 Announce Type: cross Abstract: Collision-free motion is often aided by tactile and proximity sensors distributed on the body of the robot due to their resistance to occlusion as opposed to external cameras. However, how to shape the sensor’s properties,…