Summary of Evaluating the Generalization Ability Of Quantized Llms: Benchmark, Analysis, and Toolbox, by Yijun Liu et al.
Evaluating the Generalization Ability of Quantized LLMs: Benchmark, Analysis, and Toolboxby Yijun Liu, Yuan Meng,…
Evaluating the Generalization Ability of Quantized LLMs: Benchmark, Analysis, and Toolboxby Yijun Liu, Yuan Meng,…
Tender: Accelerating Large Language Models via Tensor Decomposition and Runtime Requantizationby Jungi Lee, Wonbeom Lee,…
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Dissecting Adversarial Robustness of Multimodal LM Agentsby Chen Henry Wu, Rishi Shah, Jing Yu Koh,…
LayerMerge: Neural Network Depth Compression through Layer Pruning and Mergingby Jinuk Kim, Marwa El Halabi,…
TREE: Tree Regularization for Efficient Executionby Lena Schmid, Daniel Biebert, Christian Hakert, Kuan-Hsun Chen, Michel…
Variational Distillation of Diffusion Policies into Mixture of Expertsby Hongyi Zhou, Denis Blessing, Ge Li,…
MOYU: A Theoretical Study on Massive Over-activation Yielded Uplifts in LLMsby Chi Ma, Mincong Huang,…
UIFV: Data Reconstruction Attack in Vertical Federated Learningby Jirui Yang, Peng Chen, Zhihui Lu, Qiang…
Top-Down Bayesian Posterior Sampling for Sum-Product Networksby Soma Yokoi, Issei SatoFirst submitted to arxiv on:…