FewShot AdaptiveMLC raised macro-F1 by 0.072 on a multi-label Bangla hate speech dataset by fine-tuning task-specific heads for minority labels while freezing the shared encoder.

An open-source system combining Arabic text analysis, image recognition and uncertainty-based escalation reached a macro F1 score of 0.71 on a machine-translated hateful-meme benchmark.

Kakao said on the 21st that it has released two of its self-developed "Kanana-2-Vision Encoder" models as open source on ...

Kakao has open-sourced two versions of its self-developed Kanana-2-vision-encoder on Hugging Face / Courtesy of Kakao As ...

Kakao announced on the 21st that it has released two of its in-house developed vision encoders, "Kanana-2-vision-encoder," as ...

Microsoft AI reveals a 2.8-trillion-parameter Mixture-of-Experts model trained on 16,000 NVIDIA GPUs, claiming 4-12x FLOPs ...

"I updated Python, but I can't read Japanese CSV files." When you open a file you've received and see a string of English ...

Up until the last article, we dealt with "numerical noise" such as missing values and outliers. This time, we are looking at ...

I checked one published byte-to-hex encoder against an independent implementation. This repository contains the test harness, controls and recorded result. The target is BytesToTextBase16 from ...

本内容遵循CC 4.0 BY-SA版权协议 In order to use JAVE in your Java application, you have to add the file jave-1.0.jar in your application CLASSPATH. JAVE runs on a Java Runtime Environment J2SE v.1.4 or later.