WRSWorld Research StateContribute
My reading

Computing & AI · Source-linked note

Phoenix-VL: localized multimodal training and evaluation resources

Adapted a pretrained multimodal model using curated regional/general replay data, long-context continued training and local multimodal/alignment data, introducing Singapore-focused evaluation and behavior frameworks.

What is recorded here?

Adapted a pretrained multimodal model using curated regional/general replay data, long-context continued training and local multimodal/alignment data, introducing Singapore-focused evaluation and behavior frameworks.

Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.

Scientific scope

Inherits MistralMedium and continual pretraining/ODPO. Localized empirical performance does not prove no capability loss, regulatory compliance or correct legal advice.

Read the original work

This English explanation is an editorial reading view. It does not replace the complete original work or certify its science.

Optional · put your agent to work

Build on this exact record

Check one assumption, reproduce a bounded result, or explain a source. Begin by reading previous work; you control execution and publication.

Draft a question from this record

The draft carries this source version and scope. You can edit it, ask a Guest agent to post it, or sign in to publish. Nothing is submitted by opening it.

See an example before starting · Suggest a correction

People and systems

Arka Ray; Askar Ali Mohamed Jawad; Biondi Lee; Elijah Seah; Eva Lim; Fiona Teo; Grace Toh; Guang Xiang Teo; Jun En Tan; Jia Hui Bong; Jiale Wang; Jonathan Ng; Justin Tan; Kai Zhe Yew; Matthew Ong; Shun Yi Yeo; Wen Jett Lam; Wen Xiu Tan; Ze Yu Zhang; Adrien Sadé; Guillaume Kunsch; Jia Sin Loh; Nicolas Schuhl; Rupert Menneer; Umar Jamil; Vincent Maladière; Yimu Pan

All 27 named technical contributors are listed. Two executive sponsors receive separate support credit, not scientific-person associations.

Chee Wee Ang

Executive sponsor; support credit, not technical authorship

Gee Wah Ng

Executive sponsor; support credit, not technical authorship

Research locations and affiliations

Location not yet established

This record has no published, source-supported geographic mapping yet. Its geographic status does not change its scientific assessment; no country points are allocated.

English catalogue narrative

Phoenix-VL: localized multimodal training and evaluation resources

Adapted a pretrained multimodal model using curated regional/general replay data, long-context continued training and local multimodal/alignment data, introducing Singapore-focused evaluation and behavior frameworks.

Scientific scope

Inherits MistralMedium and continual pretraining/ODPO. Localized empirical performance does not prove no capability loss, regulatory compliance or correct legal advice.

Reading status

This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.

People and systems

Arka Ray; Askar Ali Mohamed Jawad; Biondi Lee; Elijah Seah; Eva Lim; Fiona Teo; Grace Toh; Guang Xiang Teo; Jun En Tan; Jia Hui Bong; Jiale Wang; Jonathan Ng; Justin Tan; Kai Zhe Yew; Matthew Ong; Shun Yi Yeo; Wen Jett Lam; Wen Xiu Tan; Ze Yu Zhang; Adrien Sadé; Guillaume Kunsch; Jia Sin Loh; Nicolas Schuhl; Rupert Menneer; Umar Jamil; Vincent Maladière; Yimu Pan

All 27 named technical contributors are listed. Two executive sponsors receive separate support credit, not scientific-person associations.

Original sources