馒头and花卷

摘要： [TOC] > [Liu H., Wei Y., Yin J. and Nie L. HS-GCN: Hamming spatial graph convolutional networks for recommendation. IEEE TKDE.](https://arxiv.org/pdf/ 阅读全文

摘要： [TOC] > [Su J., Lu Y., Pan S., Murtadha A., Wen B. and Liu Y. RoFormer: Enhanced transformer with rotary position embedding. ](http://arxiv.org/abs/21 阅读全文

摘要： [TOC] > [Zhang B. and Sennrich R. Root mean square layer normalization. NIPS, 2019.](http://arxiv.org/abs/1910.07467) ## 概 RMSNorm 节省时间. ## RMSNorm - 阅读全文

摘要： [TOC] > [1] [Unigram](http://arxiv.org/abs/1804.10959) > [2] [SentencePiece](https://colabdoge.medium.com/understanding-sentencepiece-under-standing-s 阅读全文

摘要： [TOC] > [Kojima T., Gu S. S., Reid M., Matsuo Y. and Iwasawa Y. Large language models are zero-shot reasoners. NIPS, 2022.](http://arxiv.org/abs/2205. 阅读全文

摘要： [TOC] > [Press O., Zhang M., Min S., Schmidt L., Smith N. A. and Lewis M. Measuring and narrowing the compositionality gap in language models. arXiv p 阅读全文

摘要： [TOC] > [Wei J., Wang X., Schuurmans D., Bosma M., Ichter B., Xia F., Chi E. H., Le Q. V. and Zhou D. Chain-of-thought prompting elicits reasoning in 阅读全文

摘要： [TOC] > [Trivedi H., Balasubramanian N., Khot T., Sabharwal A. Interleaving retrieval with chain-of-thought reasoning for knowledge-intensive multi-st 阅读全文

摘要： [TOC] > [He H., Zhang H. and Roth D. Rethinking with retrieval: faithful large language model inference. arXiv preprint arXiv:2301.00303, 2023.](http: 阅读全文

摘要： [TOC] > [Guu K., Lee K., Tung Z., Pasupat P. and Chang M. REALM: Retrieval-augmented language model pre-training. ICML, 2020.](http://arxiv.org/abs/20 阅读全文

摘要： [TOC] > [Lewis P. and Perez E., et al. Retrieval-augmented generation for knowledge-intensive nlp tasks. NIPS, 2020.](http://arxiv.org/abs/2005.11401) 阅读全文

摘要： [TOC] > [Ren H., Hu W. and Leskovec J. Query2box: Reasoning over knowledge graphs in vector space using box embeddings. ICLR, 2020.](http://arxiv.org/ 阅读全文

摘要： [TOC] > [Cho S., Park E. and Yoo S. MEANTIME: Mixture of attention mechanisms with multi-temporal embeddings for sequential recommendation. RecSys, 20 阅读全文

摘要： [TOC] > [Ma C., Ma L., Zhang Y., Sun J., Liu X. and Coates M. Memory augmented graph neural networks for sequential recommendation. AAAI, 2021.](http: 阅读全文

摘要： [TOC] > [Ruiz N., Li Y., Jampani V., Pritch Y., Rubinstein M. and Aberman K. DreamBooth: Fine tuning text-to-image diffusion models for subject-driven 阅读全文

摘要： [TOC] > [Xu D., Ruan C., Kumar S., Korpeoglu E. and Achan K. Self-attention with functional time representation learning. NIPS, 2019.](http://arxiv.or 阅读全文

摘要： [TOC] > [Ye Y., Xia L. and Huang C. Graph masked autoencoder for sequential recommendation. SIGIR, 2023.](http://arxiv.org/abs/2305.04619) ## 概 图 + MA 阅读全文

摘要： [TOC] > [Li J., Wang Y., McAuley J. Time interval aware self-attention for sequential recommendation. WSDM, 2020.](https://dl.acm.org/doi/10.1145/3336 阅读全文

摘要： [TOC] > [Tian Z., Bai T., Zhao W., Wen J. and Cao Z. Eulernet: Adaptive feature interaction learning via euler’s formula for ctr prediction. SIGIR, 20 阅读全文

摘要： [TOC] > [Kumar R., Vassilvitskii S. Generalized distances between rankings. WWW, 2010.](https://dl.acm.org/doi/10.1145/1772690.1772749) ## 概 有些时候, 我们会 阅读全文