3 papers
quant-ph2026
Quantum Parity Representations: Learnable Basis Discovery, Encoders, and Shadow Deployment
Sang Hyub Kim, Oliver Knitter, Jonathan Mei +4
We study parity features as representations that can be evaluated entirely classically once the binary or quantized input representation and parity words are fixed, particularly wh…
cs.LG2025
MiniCPM-V 4.5: Cooking Efficient MLLMs via Architecture, Data, and Training Recipe
Tianyu Yu, Zefan Wang, Chongyi Wang +31
Multimodal Large Language Models (MLLMs) are undergoing rapid progress and represent the frontier of AI development. However, their training and inference efficiency have emerged a…
cs.CL2025
ChartEdit: How Far Are MLLMs From Automating Chart Analysis? Evaluating MLLMs' Capability via Chart Editing
Xuanle Zhao, Xuexin Liu, Haoyue Yang +5
Although multimodal large language models (MLLMs) show promise in generating chart rendering code, editing charts via code presents a greater challenge. This task demands MLLMs to…