AI可可AI生活

[LG] In-Context Learning Strategies Emerge Rationally [Stanford University & Harvard University] https://arxiv.org/abs/2506.17859 在小宇宙查看该单集文稿

[LG] Routing Mamba: Scaling State Space Models with Mixture-of-Experts Projection [Microsoft] https://arxiv.org/abs/2506.18145 在小宇宙查看该单集文稿

[LG] The 4th Dimension for Scaling Model Size [University of Illinois at Urbana-Champaign & University of Toronto] https://arxiv.org/abs/2506.18233 在小宇宙查看该单集文稿

[LG] These are Not All the Features You are Looking For: A Fundamental Bottleneck In Supervised Pretraining [Facebook AI Research (FAIR) at Meta & New York University] https://arxiv.org/abs/2506.18221 在小宇宙查看该单集文稿

当你给出“新答案”的瞬间，你会发现，那道反复折磨你的题，就这么烟消云散了。 在小宇宙查看该单集文稿

[LG] Robust Reward Modeling via Causal Rubrics [Google DeepMind] https://arxiv.org/abs/2506.16507 在小宇宙查看该单集文稿

[LG] Latent Concept Disentanglement in Transformer-based Language Models [Purdue University & University of Southern California] https://arxiv.org/abs/2506.16975 在小宇宙查看该单集文稿

[CL] When Does Divide and Conquer Work for Long Context LLM? A Noise Decomposition Framework [University of Chicago & Together AI] https://arxiv.org/abs/2506.16411 在小宇宙查看该单集文稿

[LG] On the Theoretical Understanding of Identifiable Sparse Autoencoders and Beyond [Peking University & MIT] https://arxiv.org/abs/2506.15963 在小宇宙查看该单集文稿

[CL] EvoLM: In Search of Lost Language Model Training Dynamics [Harvard & Stanford & EPFL] https://arxiv.org/abs/2506.16029 在小宇宙查看该单集文稿

真正的自由，是从不再解释开始。当你不再需要向世界证明什么时，你才真正开始拥有了自己的人生。 在小宇宙查看该单集文稿

[CV] Align Your Flow: Scaling Continuous-Time Flow Map Distillation   [NVIDIA]   https://arxiv.org/abs/2506.14603 在小宇宙查看该单集文稿

[LG] Taming Polysemanticity in LLMs: Provable Feature Recovery via Sparse Autoencoders   [Yale University & Shanghai Jiao Tong University]   https://arxiv.org/abs/2506.14002 在小宇宙查看该单集文稿

[LG] Flat Channels to Infinity in Neural Loss Landscapes   [EPFL & Flatiron Institute]   https://arxiv.org/abs/2506.14951 在小宇宙查看该单集文稿

[LG] GrokAlign: Geometric Characterisation and Acceleration of Grokking   [Rice University & Brown University]   https://arxiv.org/abs/2506.12284 在小宇宙查看该单集文稿

真正的自由，从来不是拥有无限的选择权。 在小宇宙查看该单集文稿

[CL] AceReason-Nemotron 1.1: Advancing Math and Code Reasoning through SFT and RL Synergy   [NVIDIA]   https://arxiv.org/abs/2506.13284 在小宇宙查看该单集文稿

[LG] Random Matrix Theory for Deep Learning: Beyond Eigenvalues of Linear Models   [Huazhong University of Science and Technolog & UC Berkeley]   https://arxiv.org/abs/2506.13139 在小宇宙查看该单集文稿

[LG] LiveCodeBench Pro: How Do Olympiad Medalists Judge LLMs in Competitive Programming?   [New York University & Princeton University]   https://arxiv.org/abs/2506.119 在小宇宙查看该单集文稿

[LG] Is your batch size the problem? Revisiting the Adam-SGD gap in language modeling   [Max Planck Institute for Intelligent Systems]   https://arxiv.org/abs/2506.12543 在小宇宙查看该单集文稿

你会发现，决定你五年、十年后成为一个什么样的人，根本不是你那些写在纸上、存在手机里的宏伟计划，而是你今天，此时此刻，选择拿起一本书，还是刷一个短视频；是选择穿上跑鞋，还是继续窝在沙发里…… 在小宇宙查看该单集文稿

[LG] Because we have LLMs, we Can and Should Pursue Agentic Interpretability [Google DeepMind] https://arxiv.org/abs/2506.12152 在小宇宙查看该单集文稿

[LG] Text-to-LoRA: Instant Transformer Adaption [Sakana AI] https://arxiv.org/abs/2506.06105 在小宇宙查看该单集文稿

[LG] On the Closed-Form of Flow Matching: Generalization Does Not Arise from Target Stochasticity [CNRS] https://arxiv.org/abs/2506.03719 在小宇宙查看该单集文稿

[CL] Don't Pay Attention [Avey AI] https://arxiv.org/abs/2506.11305 在小宇宙查看该单集文稿