AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
We have 2 of 2 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
Real-Q (Real-time E2E-loss Aligned LLM Quantization), a novel PTQ paradigm that breaks this compromise: instead of diluting the objective for the sake of analytic tractability, REAL-Q targets an end-to-end-aligned surrogate of the global loss and refines it via fine-grained, dynamic Block-wise Gradient Descent applied...
ReQuant is introduced, a backpropagation-free fixed-grid refinement procedure that takes an existing quantized model as a feasible starting point and iteratively revisits its discrete weight assignments on the fixed quantization grid, and turns the initially fixed PTQ output into an iteratively optimizable discrete sol...
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.