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论文题目:Towards Better Instruction Following Language Models for Chinese: Investigating the Impact of Training Data and Evaluation 期刊:arXiv.org e-Print archive 作者:Yunjie Ji、Yan Gong、Yong D…
2. Related Work (1)Instruction-following Language Models大型语言模型 (LLM) 使用自回归 Transformer 模型在广泛的文本语料库上进行预训练以预测后续标记。他们在自我监督 [53]、多任务 [54] 和少样本学习者 [4] 方面表现出了强大的能力。最近,InstructGPT [48] 和 FLAN [8, 66] 表明,LLM 可以通过在教学...
Large language models (LLMs) have achieved impressive success across several fields, but their proficiency in understanding and resolving complex graph problems is less explored. To bridge this gap, we introduce GraphInstruct, a novel and comprehensive instruction-tuning dataset designed to equip languag...
Recommendation as instruction following: a large language model empowered recommendation approach. 2023. 概 通过指令跟随来利用大模型进行推荐, 本文介绍了不同的指令的模板, 覆盖多种任务场景. InstructRec 首先作者对用户的偏好, 意图, 和推荐的任务类型进行了分类: Preference: None (P0P0): 即我们对用户没...
LLMs:《Instruction Tuning for Large Language Models: A Survey—大型语言模型的指令调优的综述》翻译与解读之Datasets数据集 导读:该综述全面系统地梳理了指令微调的方法论、数据集、模型、应用、优缺点和未来发展方向。 1、引言:介绍了指令微调的动机和作用,以解决LLMs与用户目标的不匹配问题。LLMs在自然语言处理...
Recent end-to-end speech language models (SLMs) have expanded upon the capabilities of large language models (LLMs) by incorporating pre-trained speech models. However, these SLMs often undergo extensive speech instruction-tuning to bridge the gap between speech and text modalities. This requires...
Paper:《Instruction Tuning for Large Language Models: A Survey—大型语言模型的指令调优的综述》翻译与解读 导读:2023年8月21日,浙江大学等团队,发布了《Instruction Tuning for Large Language Models: A Survey》。指令微调是在大规模语言模型的基础上,使用包含(指令,输出)的监督数据进行进一步训练,以减小模型原...
To overcome these issues, we introduce Instruction-Following Eval (IFEval) for large language models. IFEval is a straightforward and easy-to-reproduce evaluation benchmark. It focuses on a set of “verifiable instructions” such as “write in more than 400 words” and “mention the keyword ...
An Instruction-Following Large Language Model For E-commerce Repo forEcomGPT: Instruction-tuning Large Language Models with Chain-of-Task Tasks for E-commerce we proposed the first E-commerce instruction dataset EcomInstruct, with a total of 2.5 million instruction data....