…a lightweight pre-mask token mixing block that shares information across tokens before masking. View arXiv page View PDF Add to collection Community This comment has been hidden (marked as Resolved) This…
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…View arXiv page View PDF GitHub 0 Add to collection Community Training and scaling Large Language Models demand enormous computational resources, motivating both efficient sub-quadratic architectures and principled hyperparameter tuning methods…
…View arXiv page View PDF GitHub 2 Add to collection Community T2I models still struggle with complex prompts—like getting attribute binding, spatial relations, or counting wrong. To bridge this gap, we…
…View arXiv page View PDF Add to collection Community Revealing Algorithmic Deductive Circuits for Logical Reasoning This is an automated message from the Librarian Bot . I found the following papers similar to…
…A natural attempt at unification would collapse these sources into a shared space, but this erases the structural affordances (such as schemas, ontologies, compositional operators) that give each source its expressive power…
…View arXiv page View PDF GitHub 29 Add to collection Community We are excited to share T²PO, an uncertainty-guided exploration control method for stable multi-turn agentic reinforcement learning. T²PO improves…
…factor-share consequences . The conclusion is concise: the price-setter for cognitive labor is no longer the labor market. View arXiv page View PDF Project page Add to collection Community This paper…
…View arXiv page View PDF Add to collection Community Bringing SAEs to text-to-speech models! Currently, control over TTS models such as CosyVoice3 is limited to prompts or predefined tags. We…
…AI-generated summary Large Language Models (LLMs) are known to acquire reasoning capabilities through shared inference patterns in pre-training data, which are further elicited via Chain-of-Thought (CoT) practices. However…