What if your AI could explain exactly why it thinks you sound frustrated or happy? Researchers from The Chinese University of Hong Kong and Microsoft present EmotionThinker to solve this. They shifted speech emotion recognition from simple labels to deep reasoning. By using a
@jiqizhixin
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ArcFlow: two-step high-fidelity AI image generation
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Cool, now it's possible to generate high-fidelity AI images in just two steps! Enter ArcFlow from Fudan University and Microsoft Research Asia. While most tools use straight-line shortcuts that sacrifice quality, ArcFlow uses a non-linear approach that follows the natural,
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Google/Harvard/CMU neuro-symbolic agent uses Gemini to discover proofs
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Google just solved a theoretical physics problem using Gemini! Google, Harvard, and CMU built a neuro-symbolic system using the Gemini Deep Think model and a tree-search framework to autonomously discover complex mathematical proofs. The agent functions like a digital
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AI-assisted discovery solves open theoretical physics problem
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Solving an Open Problem in Theoretical Physics using AI-Assisted Discovery Paper:
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NEO-unify: Building Native Multimodal Unified Models End to End
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NEO-unify: Building Native Multimodal Unified Models End to End Blog: https://
huggingface.co/blog/sensenova
/neo-unify
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SenseTime/NTU introduce NEO-unify unified multimodal AI paradigm
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Huge! We are finally moving past the era of using separate vision encoders and generative models to build multimodal AI! SenseTime and NTU just introduced NEO-unify，a native, unified, end-to-end paradigm. Instead of using middleman tools to translate images, this model https://
x.com/SenseTime_AI/s
/SenseTime_AI/status/2029585218819199108
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Yuan3.0 Ultra introduces Layer-Adaptive Expert Pruning for large models
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How do you train a trillion-parameter AI model while dramatically improving efficiency? http://
YuanLab.ai @YuanAI_Lab presents Yuan3.0 Ultra to tackle exactly that. They introduced Layer-Adaptive Expert Pruning (LAEP) for pre-training — a system that monitors how much -
LightRetriever promises LLM-level search with 1000x faster queries
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What if you could get LLM-level search accuracy with 1000x faster query speeds? CAS and Langboat Technology present LightRetriever to do just that. The architecture keeps a powerful LLM for heavy document processing offline but replaces slow real-time query encoding with a
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Tiny AI Outthinks Giant Models Through Looped Reasoning
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What if a tiny AI could out-think a giant one by reasoning in loops instead of just getting bigger? Researchers from HKUST, CASIA, and UC Santa Cruz present LoopViT just for that! They built a "looped" transformer that reuses the same small set of weights over and over,
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SwingArena: AI Models Evaluated on Real Software Engineering Tasks
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Can AI models handle the complexity of real-world software engineering beyond simple code snippets? Researchers from HKU, UCLA, LMSYS Org, and several global institutions just released SwingArena. It is a competitive evaluation framework that mimics a professional development