Arbor separates strategy from execution using isolated git worktrees, so engineering teams can finally trace which ...
With LLMs increasingly working multimodally, there are exciting developments for more performance and leaner sizes.
Abstract: Deep hashing has been intensively studied and successfully applied in large-scale image retrieval systems due to its efficiency and effectiveness. Recent studies have recognized that the ...
Good day, ladies and gentlemen. Thank you for standing by. Welcome to the MiniMax 2025 Full Year Financial Results Conference Call. Please note that English simultaneous interpretation will be ...
Having built a business by remixing content created by others, Anthropic worries that Chinese AI labs are stealing its data. The US-based maker of Claude models on Monday accused China-based DeepSeek, ...
MiniMax, an AI company based in Shanghai, China, has announced the MiniMax M2.5, a frontier model designed to dramatically improve real-world productivity. M2.5 uses reinforcement learning in complex ...
We introduce MiniMax-M1, the world's first open-weight, large-scale hybrid-attention reasoning model. MiniMax-M1 is powered by a hybrid Mixture-of-Experts (MoE) architecture combined with a lightning ...
Unsupervised Environment Design (UED) is a promising approach to generating autocurricula for training robust deep reinforcement learning (RL) agents. However, existing implementations of common ...
Identifying communities within networks is a crucial and challenging problem with practical implications across various scientific fields. Existing methods often overlook the heterogeneous ...
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