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Vu Minh Chien

5 accepted papers

2025

Aurora-M: Open Source Continual Pre-training for Multilingual Language and Code

Taishi Nakamura, Mayank Mishra, Simone Tedeschi, Yekun Chai, Jason T. Stillerman, Felix Friedrich +35
COLING 2025industry

Pretrained language models are integral part of AI applications, but their high computational cost for training limits accessibility. Initiatives such as Bloom and StarCoder aim to democratize access to pretrained models for collaborative community development. Despite these efforts, such models enc…

Cited by 2Source ↗PDF ↗Scholar ↗
2025

BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions

Terry Yue Zhuo, Vu Minh Chien, Jenny Chim, Han Hu, Wenhao Yu, Ratnadira Widyasari +27
ICLR 2025oral

Task automation has been greatly empowered by the recent advances in Large Language Models (LLMs) via Python code, where the tasks range from software engineering development to general-purpose reasoning. While current benchmarks have shown that LLMs can solve tasks using programs like human develop…

Cited by 609Source ↗PDF ↗Scholar ↗
2025

Bridging the Data Provenance Gap Across Text, Speech, and Video

Shayne Longpre, Nikhil Singh, Manuel Cherep, Kushagra Tiwary, Joanna Materzynska, William Brannon +37
ICLR 2025poster

Progress in AI is driven largely by the scale and quality of training data. Despite this, there is a deficit of empirical analysis examining the attributes of well-established datasets beyond text. In this work we conduct the largest and first-of-its-kind longitudinal audit across modalities --- pop…

Cited by 1Source ↗PDF ↗Scholar ↗
2024

Consent in Crisis: The Rapid Decline of the AI Data Commons

Shayne Longpre, Robert Mahari, Ariel N. Lee, Campbell S. Lund, Hamidah Oderinwale, William Brannon +43
NeurIPS 2024poster

General-purpose artificial intelligence (AI) systems are built on massive swathes of public web data, assembled into corpora such as C4, RefinedWeb, and Dolma. To our knowledge, we conduct the first, large-scale, longitudinal audit of the consent protocols for the web domains underlying AI training…

Cited by 36Source ↗Scholar ↗
2022

The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset

Hugo Laurençon, Lucile Saulnier, Thomas Wang, Christopher Akiki, Albert Villanova del Moral, Teven Le Scao +48
NeurIPS 2022accept

As language models grow ever larger, the need for large-scale high-quality text datasets has never been more pressing, especially in multilingual settings. The BigScience workshop, a 1-year international and multidisciplinary initiative, was formed with the goal of researching and training large lan…

Cited by 214Source ↗PDF ↗Scholar ↗