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LG - 机器学习 CV - 计算机视觉 CL - 计算与语言 1、[LG] Exploring Neural Granger Causality with xLSTMs：Unveiling Temporal Dependencies in Complex Data 2、[CL] Large Language Diffusion Models 3、[LG] Solving Empirical Bayes via Transformers 4、[LG] Solvable Dynamics of Self-Supervised Word Embeddings and the Emergence of Analogical Reasoning 5、[LG] Balancing the Scales：A Theoretical and Algorithmic Framework for Learning from Imbalanced Data 摘要：利用 xLSTM 探索神经格兰杰因果关系、大型语言扩散模型、用Transformer解决经验贝叶斯问题、自监督词嵌入的可解动态与类比推理的涌现、不平衡数据学习的理论和算法框架 1、[LG] Exploring Neural Granger Causality with xLSTMs: Unveiling Temporal Dependencies in Complex Data H Poonia, F Divo, K Kersting, D S Dhami [Indian Institute of Technology Bombay & echnische Universität Darmstadt] 利用 xLSTM 探索神经格兰杰因果关系：揭示复杂数据中的时
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