Aktrea

ADA (Anchor Data Augmentation) offers a novel approach to data augmentation by mixing multiple samples based on clustering. 

ADA: A Powerful Data Augmentation Technique for Improved Regression Robustness

In this paper we propose a new few-shot learning approach that allows us to decouple the complexity of the task space from the complexity of individual tasks.

HyperTransformer: Conclusion and References

In the space of local LLMs, I first ran into LMStudio. While the app itself is easy to use, I liked the simplicity and maneuverability that Ollama provides.

How to Use Ollama: Hands-On With Local LLMs and Building a Chatbot

Few-shot classification involves training a model to perform a new classification task with a handful of labeled data. 

Transductive Learning for Textual Few-Shot: Limitations, Acknowledgements, & References

Antares rather gains in redness when viewed with a glass. 

THE STARS OF SUMMER

On December 10th, the studio behind the ever-popular sandbox game Minecraft published a blog post detailing a bug it identified in Log4j.

The Log4j Bug Can't Hurt WordPress - But There's an Ongoing Attack That Can

Many developers are familiar with the situation like “where did this code fragment come from and why is it needed?”. You have to spend time and deal with the details already considered by another colleague. How to make it take a less amount of time? To achieve this, pay attention to a process of writing descriptions for Pull Requests (known as “PRs”) and Merge Requests (known as “MRs”). This article will focus on the content of the PR description without any explanation of coding since each project has its own coding-related specifications and requirements.

How to Create A Detailed Description for Your Pull Request

In 2018, more than 150,000 businesses all over the world hopped on the train of Salesforce, the most fast-evolving CRM solution in the world. With adidas, Amazon, and American Express among Salesforce’s customers, the platform has been winning the market over—and pretty steadily indeed. 

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