Abstract: In this paper, we consider the model merging process for large language models (LLMs) under a two-stage optimization framework. Traditional merging methods usually apply fixed blending rates ...
Abstract: Recent neural network models, particularly those based on reinforcement learning (RL) and supervised learning, have shown great success in solving various combinatorial problems such as the ...
cuADMM solves multi-block SDP problems of the form: $$\min_X \left\langle C,X\right\rangle \quad\text{s.t.}\quad \begin{cases} \left\langle A_i,X\right\rangle = b_i ...
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