【月末特辑】10月最火AI论文 | 幼龙BDH稀疏可解释;迷你递归7兆碾压大模型
Description
本期的 10 篇论文如下:
[00:30 ] TOP1(🔥522) | 🐣 The Dragon Hatchling: The Missing Link between the Transformer and Models of the Brain(幼龙破壳: Transformer 与大脑模型之间缺失的环节)
[02:31 ] TOP2(🔥462) | 🧠 Less is More: Recursive Reasoning with Tiny Networks(小而精:用微型网络递归推理)
[04:48 ] TOP3(🔥255) | 🌱 Agent Learning via Early Experience(基于早期经验的主体学习)
[07:04 ] TOP4(🔥182) | 🔄 Scaling Latent Reasoning via Looped Language Models(通过循环语言模型扩展潜在推理能力)
[09:11 ] TOP5(🔥170) | 🔥 MCPMark: A Benchmark for Stress-Testing Realistic and Comprehensive MCP Use(MCPMark:面向真实且全面的MCP应用场景的压力测试基准)
[11:18 ] TOP6(🔥169) | 🚀 QeRL: Beyond Efficiency -- Quantization-enhanced Reinforcement Learning for LLMs(QeRL:超越效率——面向大语言模型的量化增强强化学习)
[13:10 ] TOP7(🔥167) | 🎼 Concerto: Joint 2D-3D Self-Supervised Learning Emerges Spatial Representations(Concerto:2D-3D联合自监督学习涌现空间表征)
[15:38 ] TOP8(🔥160) | 🧠 Diffusion Transformers with Representation Autoencoders(基于表示自编码器的扩散Transformer)
[17:59 ] TOP9(🔥144) | 🧠 A Theoretical Study on Bridging Internal Probability and Self-Consistency for LLM Reasoning(大模型推理中内部概率与自洽性桥接的理论研究)
[20:09 ] TOP10(🔥142) | 🎯 Spatial Forcing: Implicit Spatial Representation Alignment for Vision-language-action Model(空间强迫:面向视觉-语言-动作模型的隐式空间表征对齐)
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