[CL] From Bytes to Ideas: Language Modeling with Autoregressive U-Nets [FAIR at Meta] https://arxiv.org/abs/2506.14761

人生的智慧不在于追求一步到位的完美答案，而在于始终为自己保留更多的选择权和可能性。

[LG] Spectral Estimation with Free Decompression [UC Berkeley & University of Melbourne] https://arxiv.org/abs/2506.11994

[LG] TreeRL: LLM Reinforcement Learning with On-Policy Tree Search [Tsinghua University & California Institute of Technology] https://arxiv.org/abs/2506.11902

[CL] Large Language Models and Emergence: A Complex Systems Perspective [Santa Fe Institute] https://arxiv.org/abs/2506.11135

[LG] Tversky Neural Networks: Psychologically Plausible Deep Learning with Differentiable Tversky Similarity [Stanford University] https://arxiv.org/abs/2506.11035

[CL] You Only Fine-tune Once：Many-Shot In-Context Fine-Tuning for Large Language Model [Google & University of Florida] https://arxiv.org/abs/2506.11103

现代人的焦虑很大程度源于不断的比较。我们习惯用别人的成就来衡量自己，这种"比较"就像快乐的小偷，偷走了本该属于我们的幸福感。

[CL] Draft-based Approximate Inference for LLMs [FuriosaAI & UW-Madison] https://arxiv.org/abs/2506.08373

[LG] On the Similarities of Embeddings in Contrastive Learning [Yonsei University] https://arxiv.org/abs/2506.09781

[LG] Sequential-Parallel Duality in Prefix Scannable Models [MIT CSAIL & Technical University of Munich] https://arxiv.org/abs/2506.10918

[LG] Self-Adapting Language Models [MIT] https://arxiv.org/abs/2506.10943