📖A curated list of Awesome LLM/VLM Inference Papers with codes: WINT8/4, FlashAttention, PagedAttention, MLA, Parallelism etc. 🎉🎉
Light-field imaging application for plenoptic cameras
[ICLR 2025] Palu: Compressing KV-Cache with Low-Rank Projection
Light field geometry estimator for plenoptic cameras
xKV: Cross-Layer SVD for KV-Cache Compression
An efficient and scalable attention module designed to reduce memory usage and improve inference speed in large language models. Designed and implemented the Multi-Head Latent Attention (MLA) module as a drop-in replacement for traditional multi-head attention (MHA) in large language models.
Latentformer is a transformer model with latent attention designed for efficient training. It features learnable positional embeddings, rotary position encoding, and MLA to optimize speed and performance while maintaining model quality.
最小Transformer架构，能够快速搭建现在各种Transformer架构模型
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