Jun 17, 2023 · Delve into Transformer architectures: from the original encoder-decoder structure, to BERT & RoBERTa encoder-only models, to the GPT series focused on decoding. Explore their evolution, strengths, & applications in NLP tasks.

Apr 9, 2024 · In this work, we introduce LLM2Vec, a simple unsupervised approach that can transform any decoder-only LLM into a strong text encoder. LLM2Vec consists of three simple steps: 1) enabling bidirectional attention, 2) masked next token prediction, and 3) unsupervised contrastive learning.

LLM2Vec is a simple recipe to convert decoder-only LLMs into text encoders. It consists of 3 simple steps: 1) enabling bidirectional attention, 2) training with masked next token prediction, and 3) unsupervised contrastive learning.

Apr 27, 2024 · This comprehensive guide delves into decoder-based Large Language Models (LLMs), exploring their architecture, innovations, and applications in natural language processing. Highlighting the evolution from the traditional transformer model, it discusses how LLMs utilize decoder-only architecture to enhance text generation and processing ...

Mar 22, 2024 · Encoders and embeddings are foundational elements of Large Language Models, enabling these AI systems to process, understand, and generate human-like text. Encoders transform raw text into...

Oct 1, 2024 · Much machine learning research focuses on encoder-decoder models for natural language processing (NLP) tasks involving large language models (LLMs). Encoder-decoder models are used to handle sequential data, specifically mapping input sequences to output sequences of different lengths, such as neural machine translation, text summarization ...

Feb 7, 2023 · Following the original transformer architecture, large language model research started to bifurcate in two directions: encoder-style transformers for predictive modeling tasks such as text classification and decoder-style transformers for generative modeling tasks such as translation, summarization, and other forms of text creation.

Nov 20, 2024 · Large Language Models (LLMs) have transformed how we handle and generate text, supporting tasks like sentiment analysis, summarization, and real-time language translation. Choosing the right...

Mar 11, 2025 · The breakthrough 2017 Transformer architecture powers virtually all modern Large Language Models through several key components: Encoder layers process input text into rich contextual representations. Decoder layers generate output based on encoded information. Multi-head attention allows simultaneous focus on different aspects of text

Oct 11, 2024 · Large language models (LLMs) have changed the game for machine translation (MT). LLMs vary in architecture, ranging from decoder-only designs to encoder-decoder frameworks. Encoder-decoder models, such as Google ’s T5 and Meta ’s BART, consist of two distinct components: an encoder and a decoder.