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math.CO2026
Graph Sensitivity of Cartesian Products with Matched Bridges
Zhen-Mu Hong, Zi-Yi Wu, Zheng-Jiang Xia
For a graph , let denote the minimum of the maximum degree of an induced subgraph with vertices, where is the independence number, and write $f(G)=f_1(G…
cs.AI2026
Sharpening Tax in Post-Training
Changdae Oh, Qi Zeng, Qi Qi +7
An emerging hypothesis about reinforcement learning (RL) post-training of large language models (LLMs) is that it merely sharpens existing behaviors of a base model, improving sing…
cs.LG2026
LoRA-generating hypernetworks for efficient on-device LLM generative personalization
Sean Augenstein, Li Ding, Jihwan Lee +2
On-device large language models (`LLMs'), e.g. running on mobile phones, are ripe for improvement via personalization. The limited compute resources of mobile devices impose limits…