LeonLixyz/LCLM

LLM KV cache compression made easy

Unified KV Cache Compression Methods for Auto-Regressive Models

Code and documents of LongLoRA and LongAlpaca (ICLR 2024 Oral)

14-stage Fusion Pipeline for LLM token compression — reversible compression, AST-aware code analysis, intelligent content routing. Zero LLM inference cost. MIT licensed.

[EMNLP'23, ACL'24] To speed up LLMs' inference and enhance LLM's perceive of key information, compress the prompt and KV-Cache, which achieves up to 20x compression with minimal performance loss.

Awesome LLM compression research papers and tools.

[CoLM'25] The official implementation of the paper <MoA: Mixture of Sparse Attention for Automatic Large Language Model Compression>

Recursive Language Models for efficient long-context processing. Analyze 1M+ tokens by storing context in a Python REPL while reducing LLM token usage.

Official repository for "Context Language Models"