BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models arxiv: https://arxiv.org/abs/2301.12597 arxiv: https://arxiv.org/abs/2301.12597 [Submitted on 3…
《EVEv2: Improved Baselines for Encoder-Free Vision-Language Models》是BAAI、PKU和UCAS等结构提出的一个工作,提出了Visual-Encoder-Free的多模态大模型EVEv2,是前面EVE的一个Improved 的Version。 在视觉语言模型或者多模态大模型里面,视觉输入信息和文本信息的融合一般通过Visual Encoder(Visual Backbone)、Visual En...
对于Decoder-only的LLM作者使用language modeling loss,LLM需要给出基于视觉表示的文本;对于encoder-decoder结构的LLM作者使用prefix language modeling loss,prefix text与output query连接作为编码器输入,suffix text作为解码器的生成目标。 模型预训练 略 实验 Q-Former存在的问题 难训练,训练图像与测试图像有gap的话效果...
(2014), where an encoder is responsible for encoding the input data into a hidden space, while a decoder is used to generate the target output text. Figure 1: Encoder-Decoder (ED) framework and decoder-only Language Model (LM). Recently, many promising large language models (GPT Radford ...
苏州大学从头训练的双语非对称Encoder-Decoder模型OpenBA已正式开源! 主要亮点包括: 亮点一:此模型为中文开源社区贡献了一个有代表性的编码器解码器大语言模型,其训练过程(包括数据收集与清洗、模型构建与训练)已完全开源。 亮点二:数据方面,OpenBA所使用的数据均公开可获取,模型的能力产生更加透明。
Motivation 以前的模型大多都只依赖于encoder或关注于decoder,分别对于生成和理解任务是次优的; 此外,大多数现有的方法把code看作是像NL这样的标记序列,只是在其上采用传统的NLP预训练技术,这在很大程度上忽略了代码中丰富的结构性信息,而这对于完全理解代码的语义至
With all the excitement around decoder-based large language models (aka “autoregressive models” or “GPT-style LLMs”), encoder-basedTransformershave not received the attention they deserve. Now,ModernBERT, a new encoder model developed byAnswer.AIandLightOn, is helping encoders catch up with ...
Return of the Encoder: Efficient Small Language Models Code and Models of the Paper Return of the Encoder Overview While large language models continue to grow in size, smaller models (≤1B parameters) require thoughtful architectural decisions. Our work demonstrates that encoder-decoder models inhere...
Hierarchical Attention Encoder Decoder 1 Jun 2023 · Asier Mujika · Edit social preview Recent advances in large language models have shown that autoregressive modeling can generate complex and novel sequences that have many real-world applications. However, these models must generate outputs ...
Large decoder-only language models (LLMs) are the state-of-the-art models on most of today's NLP tasks and benchmarks. Yet, the community is only slowly adopting these models for text embedding tasks, which require rich contextualized representations. In this work, we introduce LLM2Vec, a...