What Is Generative Models for Scientific Data? A Complete Guide Imagine if a computer could watch a video of cells dividing, listen to the patterns in biological recordings, and then generate entirely new, realistic versions of those phenomena that have never existed before. This is not science fiction—it is happening right now in laboratories around … Read more
arXiv:2604.26841v2 Announce Type: replace-cross
Abstract: When do language diffusion models memorize their training data, and how to quantitatively assess their true generative regime? We address…
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Abstract: Text-to-image (T2I) models remain vulnerable to jailbreak attacks that elicit Not-Safe-For-Work (NSFW) content, despite increasingly being guarded…
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Abstract: Recent surges in LLM-driven intelligent systems largely overlook decades of foundational multi-agent systems (MAS) research, resulting in…
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Abstract: We introduce Cost-Aware (CA) Sequential Hypothesis Testing (CASHT), in which an active decision-maker selects sensing actions with…
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Abstract: We study a self-supervised generation task for single-cell gene expression vectors: given a set of vectors from a cell type, we aim to generate…
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Abstract: Thompson sampling (TS) is one of the most popular and earliest algorithms to solve stochastic multi-armed bandit problems. We consider a…
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Abstract: Self-evolving agents advance toward autonomy by optimizing their harness—prompts, skills, tools, and execution logic—based on environmental…
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Abstract: Using a large language model to play the user is now standard in scalable evaluation. It has a repeatedly diagnosed failure: the simulated user is…
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Abstract: Neural audio codecs optimized for mel-spectrogram reconstruction often fail to preserve intelligibility. While semantic encoder distillation…