04:00
2026-07-31
arxiv.org
machine-learning
Flat Score, Amplified Failures: How the Error Budget Masks Damage in Quantized LLM Agents
A new arXiv study (2607.27275v1) finds that 4-bit post-training quantization of large language models appears lossless on standard benchmarks but amplifies existing tool-calling failures by up to 2.5x…