GitHub

SynCABEL: Synthetic Contextualized Augmentation for Biomedical Entity Linking

SynCABEL is a novel framework designed to enhance generative biomedical entity linking (BEL) by leveraging Large Language Models (LLMs) to generate synthetic, contextualized training data for all ...
note

Natural Language Processing and Speech in the G Certification: Differences between word2vec, LSTM, Transformer, and BERT/GPT

Click here for the previous article: Part 6: "G Certification CNN and Image Recognition: Calculating Output Size and How to Distinguish ResNet, YOLO, and U-Net" Natural language processing and speech ...
huggingface

Compositional Reasoning on Arithmetic: LSTM and Transformer Checkpoints

This repo holds the 12 trained checkpoints from the paper Partial Competence and Limited Transfer: Comparing LSTM and Transformer Generalization on Arithmetic Expressions (arXiv ID pending). The ...
huggingface

TarjimaAI: English-to-Uzbek Neural Machine Translation (Seq2Seq with Bahdanau Attention)

Official PyTorch model checkpoints and token vocabularies for TarjimaAI, a neural machine translation system trained from scratch on parallel English-Uzbek corpora.
blog.csdn

Encoder 与 Decoder 详解：从 Embedding 到 Seq2Seq 的完整数据流

本内容遵循CC 4.0 BY-SA版权协议 本文用一个完整例子解释：输入“我爱你”后，每个词怎样经过 Embedding、Encoder，最后由 Decoder 生成 “I love you”。重点是区分词向量、上下文表示和生成过程。
blog.csdn

Seq2Seq模型原理与实战：从编码器到注意力机制详解

本内容遵循CC 4.0 BY-SA版权协议 Seq2Seq（Sequence to Sequence）模型是自然语言处理领域的经典框架，主要用于处理任意长度序列到另一序列的转换任务。我第一次接触这个模型是在2016年机器翻译项目 ...
Hà Tĩnh 24h

Chân dung 'quái kiệt' gốc Hà Tĩnh rời Google, sáng lập startup AI định giá 50 tỷ USD gây chấn động Silicon Valley

Trong số 4 nhà đồng sáng lập, bên cạnh những tên tuổi như Jeff Dean, Sanjay Ghemawat và Oriol Vinyals, có sự xuất hiện của Lê ...
note

G検定の自然言語処理と音声：word2vec・LSTM・Transformer・BERT/GPTの違い

前回の記事はこちら：第6回「G検定のCNNと画像認識：出力サイズの計算とResNet・YOLO・U-Netの見分け方」 G検定の自然言語処理と音声処理は、覚える名前の多さでつまずく単元です。2026年第2 ...