使用了一个专用的大模型,让LLM为93种语言的各种embedding tasks生成了大量数据 具体来说,设计了一个two-step prompting strategy让大模型自己brainstorm一些任务,并根据生成的任务去自己再生成数据,生成的数据使用不同的prompt模版来增强多样性 使用类似Mistral-7B的大模型而不是bert类的模型,因为有更多网上数据并且经过...
[RAG|LLM] embedding的后bert时代 | Improving Text Embeddings with Large Language Models 一只小茄墩 一条向外,通往星辰大海;一条对内,通往虚拟现实。 来自专栏 · 小台阶 30 人赞同了该文章 MTEB榜单,终于又迎来了LLM底座的SOTA。 现有的多阶段方法有几个缺点。首先,它们需要复杂的多阶段训练管道,需要大...
We then fine-tune open-source decoder-only LLMs on the synthetic data using standard contrastive loss. Experiments demonstrate that our method achieves strong performance on highly competitive text embedding benchmarks without using any labeled data. Furthermore, when fine-tuned with a mixture o...
In this paper, we propose an improving embedding learning by virtual attribute decoupling (iVAD) model for learning modality-invariant image-text embeddings. To the best of our knowledge, this is the first work which performs unsupervised attribute decoupling in text-based person search task. In ...
As shown in Figure 1, we first preprocess customer data with different formats into structured textsand save them as Dataverse entities. These entities are sent to the document featurization pipeline for chunking, text feature extraction, and...
This project aims to improve text embedding of smaller Language Models (LMs) up to 2B parameters using the contrastive fine-tuning technique. Specifically, the InfoNCE loss is utilized as a training objective. min − log e sim ( h i , h i + ) / τ ∑ i ( e sim ( h i , ...
GAugLLM Official code for "GAugLLM: Improving Graph Contrastive Learning for Text-Attributed Graphs with Large Language Models". GAugLLM is a novel framework for augmenting TAGs, leveraging advanced large language models like Mistral to enhance self-supervised graph learning. Pipeline of the GAugLLM ...
在这篇论文中,探索出了一种对自然语言理解任务的半监督方法,融合了无监督的预训练(pre-training)和有监督的微调(fine-tuning)过程。本文提出了一种通用表示,能够在范围广泛的任务中稍加修改、适应就能快速进行transfer.整个过程分成两个阶段。 阶段一:在无标签的海量数据中训练语言模型,学习神经网络模型的参数。
LangChain: An open-source framework for developing language model-powered applications. It provides prompt templates, models, document loaders, text splitters, andmany other tools for interacting with models. LangSmith: A tool to more efficiently debug LLM apps by showing the trace of LLM calls, ...
Building a Contextual Retrieval System for Improving RAG Accuracy To enhance AI models for specific tasks, they require domain-specific knowledge. For instance, customer support chatbots need business-related information, while legal bots rely on historical case da.....