paper-conference

Harnessing Hyperbolic Geometry for Harmful Prompt Detection and Sanitization
Vision–Language Models (VLMs) have become essential for tasks such as image synthesis, captioning, and retrieval by aligning textual …
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Harnessing Hyperbolic Geometry for Harmful Prompt Detection and Sanitization
Implicit Inversion turns CLIP into a Decoder
CLIP is a discriminative model trained to align images and text in a shared embedding space. Due to its multimodal structure, it serves …
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Implicit Inversion turns CLIP into a Decoder
Spilled Energy in Large Language Models
We reinterpret the final softmax classifier over the vocabulary of Large Language Models (LLM) as an Energy-based Model (EBM). This …
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Spilled Energy in Large Language Models
Why Adversarially Train Diffusion Models?
We answer the question in the title showing that adversarial training (AT) for diffusion models (DMs) fundamentally differs from …
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Why Adversarially Train Diffusion Models?
MASS : MoErging through Adaptive Subspace Selection
Model merging has recently emerged as a lightweight alternative to ensembling, combining multiple fine-tuned models into a single set …
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MASS : MoErging through Adaptive Subspace Selection
Inverse Language Modeling for Robust and Grounded LLMs
The current landscape of defensive mechanisms for LLMs is fragmented and underdeveloped, unlike prior work on classifiers. To further …
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Inverse Language Modeling for Robust and Grounded LLMs
Environment Maps Editing using Inverse Rendering and Adversarial Implicit Functions
Editing High Dynamic Range (HDR) environment maps using an inverse differentiable rendering architecture is a complex inverse problem …
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Environment Maps Editing using Inverse Rendering and Adversarial Implicit Functions
Shedding More Light on Robust Classifiers Under the Lens of Energy-Based Models
By reinterpreting a robust discriminative classifier as Energy-based Model (EBM), we offer a new take on the dynamics of adversarial …
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Shedding More Light on Robust Classifiers Under the Lens of Energy-Based Models
Exploring the Connection between Robust and Generative Models
We offer a study that connects robust discriminative classifiers trained with adversarial training (AT) with generative modeling in the …
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Exploring the Connection between Robust and Generative Models
Hierarchical Fine-grained Image Forgery Detection and Localization
Differences in forgery attributes of images generated in CNN-synthesized and image-editing domains are large, and such differences make …
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Hierarchical Fine-grained Image Forgery Detection and Localization