News

Forbes India6d
Amitabh Nag: Breaking Indian language barriers in AI
As the CEO of Bhashini, Nag is helping build the government's platform to make digital content and services more accessible ...
Geeky Gadgets7mon
Understanding GPTs: A Deep Dive into AI Language Models
Generative Pre-trained Transformers (GPTs) have transformed natural language processing (NLP), allowing machines ... importance to each token. Decoder: Uses the encoder’s outputs, along with ...
GitHub11mon
Graph2Seq is a simple code for building a graph-encoder and sequence-decoder for NLP and other AI/ML/DL tasks.
each line is a json object whose keys are "seq", "g_ids", "g_id_features", "g_adj": "seq" is a text which is supposed to be the output of the decoder "g_ids" is a ...
techxplore1y
Voice at the wheel: Study introduces an encoder-decoder framework for AI systems
Such an endeavor intersects two critical domains: computer vision and natural language processing (NLP). A pivotal research challenge ... The model is structured around an Encoder-Decoder framework, ...
GitHub1y
encoder-decoder-architecture
This Project is based on multilingual Translation by using the Transformer with an encoder-decoder architecture along with the multi ... English to French language using various Techniques of NLP and ...
marktechpost1y
Deep Learning Architectures From CNN, RNN, GAN, and Transformers To Encoder-Decoder Architectures
The ability of transformers to handle data sequences without the need for sequential processing makes them extremely effective for various NLP tasks, including translation, text summarization, and ...
marktechpost1y
LLM2Vec: A Simple AI Approach to Transform Any Decoder-Only LLM into a Text Encoder Achieving SOTA Performance on MTEB in the Unsupervised and Supervised Category
Natural Language Processing (NLP) tasks heavily rely on text embedding models as they translate the semantic meaning of text into vector representations. These representations make it possible to ...