The research by Zhan et al. explores the vulnerability of large language models (LLMs), particularly GPT-4, due to fine-tuning. The researchers demonstrate that fine-tuning can be used to remove RLHF…
Continue readingThe paper presents PAC-tuning, a method for fine-tuning pretrained language models (PLMs) to enhance their generalization performance. The method uses PAC-Bayes training to directly minimize the PAC-Bayes generalization bound, resulting…
Continue readingThe paper introduces ROBOFUME, a system that allows robots to learn new tasks autonomously with minimal human intervention. The system pre-trains a multi-task manipulation policy using diverse datasets, and then…
Continue readingThe article presents a new technique called ‘Emulated Fine-Tuning’ (EFT) for large language models. The authors explore the two-stage training pipeline of language models – pre-training and fine-tuning – and…
Continue readingThe research proposes Adaptive Bayesian Domain Randomization via Strategic Fine-tuning (BayRnTune), a method to significantly speed up the learning processes in domain randomization by fine-tuning from previously learned policy. The…
Continue readingThe study focuses on improving Speech Emotion Recognition (SER) which is crucial in human-machine interaction. Existing SER methods overlook the information gap between the pre-training speech recognition task and the…
Continue readingThe article is about AUDIO CONFIT, a two-stage contrastive learning-based approach for fine-tuning pre-trained audio models. AUDIO CONFIT aims to strike a balance between fitting the model to the training…
Continue readingThe research by Zhou Mingjun, Daiqing Zhuoma, Qun Nuo, and Nyima Tashi from Tibet University focuses on the efficient fine-tuning of Tibetan pre-trained language models (PLMs). The study fills a…
Continue readingThe article discusses the development of MetaMath, a fine-tuned language model for mathematical reasoning. Despite the success of Large Language Models (LLMs), they often fall short in solving complex mathematical…
Continue readingThis research introduces a new framework named PromptSRC, aiming to improve the way prompts are used to fine-tune foundational models like CLIP for various tasks. The new approach aims to…
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