Papers propose new LLM compression and quantization methods

Multiple papers introduce techniques for LLM compression, including structured pruning, mixed-precision quantization (MixQuant), sparse attention for long contexts (RIS-Kernel), channel-wise sensitivity for MLLMs (C-PTQ), statistically-lossless quantization, spectral prompt compression (Spectral-LSH), and inference-time monitoring for quantized models.