A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Xiaoyuan Su, Taghi M. Khoshgoftaar
A comprehensive survey of collaborative filtering techniques, categorizing them into memory-based, model-based, and hybrid approaches while addressing key challenges like data sparsity and scalability.
Shuo Yang, Ying Sheng, Joseph E. Gonzalez, et al.
Double Sparsity reduces KV cache access in LLMs via post-training sparse attention combining token and channel sparsity.
Yizhao Gao, Zhichen Zeng, Dayou Du, et al.
Seerattention introduces a block-sparse attention kernel that achieves a 7.3× speedup at 90% sparsity on 128k sequences, enabling efficient long-context LLMs.