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Xolver: Multi-Agent Reasoning with Holistic Experience Learning Just Like an Olympiad Team
Paper • 2506.14234 • Published • 41 -
MoTE: Mixture of Ternary Experts for Memory-efficient Large Multimodal Models
Paper • 2506.14435 • Published • 7 -
Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory
Paper • 2504.19413 • Published • 34 -
MemOS: A Memory OS for AI System
Paper • 2507.03724 • Published • 157
Collections
Discover the best community collections!
Collections including paper arxiv:2511.18423
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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 29 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 14 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 44 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 23
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Xolver: Multi-Agent Reasoning with Holistic Experience Learning Just Like an Olympiad Team
Paper • 2506.14234 • Published • 41 -
MoTE: Mixture of Ternary Experts for Memory-efficient Large Multimodal Models
Paper • 2506.14435 • Published • 7 -
Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory
Paper • 2504.19413 • Published • 34 -
MemOS: A Memory OS for AI System
Paper • 2507.03724 • Published • 157
-
EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 29 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 14 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 44 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 23