Black-box prompt engineering [54] enables adjusting prompts without requiring access to the underlying model’s parameters and gradients, making it particularly valuable for closed-source models with superior performance [55]. This advancement allows for effective optimization of closed-source models, ove...
Language Models as Black-Box Optimizers for Vision-Language Models Shihong Liu, Samuel Yu, Zhiqiu Lin, Deepak Pathak, Deva Ramanan arXiv 2023. [Paper][Github] 12 Sep 2023 InstructZero: Efficient Instruction Optimization for Black-Box Large Language Models ...
In this work, we propose Optimization by PROmpting (OPRO), a simple and effective approach to leverage large language models (LLMs) as optimizers, where the optimization task is described in natural language. In each optimization step, the LLM generates new solutions from the prompt that ...
FedBPT: Efficient Federated Black-box Prompt Tuning for Large Language Models Jingwei Sun, Ziyue Xu, Hongxu Yin, Dong Yang, Daguang Xu, Yiran Chen, Holger R. Roth arXiv 2023. [Paper] 2 Oct 2023Language Models as Black-Box Optimizers for Vision-Language Models Shihong Liu, Samuel Yu...
structure in transformer based language models to make a simple model-parallel implementation that trains efficiently in PyTorch, with no custom C++ code or compiler required. This approach is orthogonal to pipeline-based model parallelism as advocated by approaches such as GPipe(Huang et al.,2018)...
NLP has developed as a field narrowly focused on English, a point highlighted by the recent emergence (and need for) the#BenderRule. The ability of NLP models to deal with English is important, due to its status as an international language of politics, commerce and culture, and indeed with...
Training LLMs efficiently at scale necessitates various system innovations, such as statesharding optimizers [79], meticulous model placement using data, pipeline, and tensor parallelisms [67, 68, 113]. 数据准备。初始阶段涉及收集和预处理训练数据,可分为两部分:(1) 预训练数据,包括从公共或私人...
[2] Towards Reasoning in Large Language Models: A Survey 2022 [3] A Survey of Deep Learning for Mathematical Reasoning 2022 [4] Template Filling for Controllable Commonsense Reasoning 2021 [5] Large Language Models are Zero-Shot Reasoners NeurIPS 2022 ...
2. Prepare Dataset TensorFlow models repo provides scripts and instructions to download, process and convert the ImageNet dataset to the TF records format.3. Prepare pre-trained model In this version, Intel Low Precision Optimization Tool just supports PB fil...
Language Models as Black-Box Optimizers for Vision-Language Models Shihong Liu, Samuel Yu, Zhiqiu Lin, Deepak Pathak, Deva Ramanan arXiv 2023. [Paper][Github] 12 Sep 2023InstructZero: Efficient Instruction Optimization for Black-Box Large Language Models Lichang Chen, Jiuhai Chen, Tom ...