Remove Data Scarcity Remove Large Language Models Remove NLP
article thumbnail

Leveraging Linguistic Expertise in NLP: A Deep Dive into RELIES and Its Impact on Large Language Models

Marktechpost

With the significant advancement in the fields of Artificial Intelligence (AI) and Natural Language Processing (NLP), Large Language Models (LLMs) like GPT have gained attention for producing fluent text without explicitly built grammar or semantic modules.

article thumbnail

Advancing Cantonese NLP: Bridging Development Gaps in Large Language Models with New Benchmarks and Open-Source Innovations

Marktechpost

Large language models (LLMs) have revolutionized natural language processing (NLP), particularly for English and other data-rich languages. However, this rapid advancement has created a significant development gap for underrepresented languages, with Cantonese being a prime example.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Innovation in Synthetic Data Generation: Building Foundation Models for Specific Languages

Unite.AI

Synthetic data , artificially generated to mimic real data, plays a crucial role in various applications, including machine learning , data analysis , testing, and privacy protection. However, generating synthetic data for NLP is non-trivial, demanding high linguistic knowledge, creativity, and diversity.

NLP 173
article thumbnail

Unpacking the NLP Summit: The Promise and Challenges of Large Language Models

John Snow Labs

The recent NLP Summit served as a vibrant platform for experts to delve into the many opportunities and also challenges presented by large language models (LLMs). Strategy and Data: Non-top-performers highlight strategizing (24%), talent availability (21%), and data scarcity (18%) as their leading challenges.

article thumbnail

This AI Paper from Cohere for AI Presents a Comprehensive Study on Multilingual Preference Optimization

Marktechpost

Multilingual natural language processing (NLP) is a rapidly advancing field that aims to develop language models capable of understanding & generating text in multiple languages. These models facilitate effective communication and information access across diverse linguistic backgrounds.

article thumbnail

How Fastweb fine-tuned the Mistral model using Amazon SageMaker HyperPod as a first step to build an Italian large language model

AWS Machine Learning Blog

With a vision to build a large language model (LLM) trained on Italian data, Fastweb embarked on a journey to make this powerful AI capability available to third parties. To tackle this data scarcity challenge, Fastweb had to build a comprehensive training dataset from scratch to enable effective model fine-tuning.

article thumbnail

Brown University Researchers Propose LexC-Gen: A New Artificial Intelligence Method that Generates Low-Resource-Language Classification Task Data at Scale

Marktechpost

Data scarcity in low-resource languages can be mitigated using word-to-word translations from high-resource languages. However, bilingual lexicons typically need more overlap with task data, leading to inadequate translation coverage. Check out the Paper.