14 citations · 18 across the 9 of their papers we have counts for
9 papers
Jais 2: A Family of Arabic-Centric Open Large Language Models
Mohamed Anwar, Abed Alhakim Freihat, George Ibrahim +57
Jais 2 is a family of Arabic-centric large language models developed jointly by MBZUAI, Cerebras, and Inception, designed to advance Arabic-centric language modeling, with strong p…
K2-V2: A 360-Open, Reasoning-Enhanced LLM
K2 Team, Zhengzhong Liu, Liping Tang +36
We introduce K2-V2, a 360-open LLM built from scratch as a superior base for reasoning adaptation, in addition to functions such as conversation and knowledge retrieval from genera…
PTPP-Aware Adaptation Scaling Laws: Predicting Domain-Adaptation Performance at Unseen Pre-Training Budgets
Etienne Goffinet, Shane Bergsma, Avraham Sheinin +4
Continual pre-training (CPT) for domain adaptation must balance target-domain gains with stability on the base domain. Existing CPT scaling laws typically assume a fixed pre-traini…
Llama-3-Nanda-10B-Chat: An Open Generative Large Language Model for Hindi
Monojit Choudhury, Shivam Chauhan, Rocktim Jyoti Das +27
Developing high-quality large language models (LLMs) for moderately resourced languages presents unique challenges in data availability, model adaptation, and evaluation. We introd…
Crystal: Illuminating LLM Abilities on Language and Code
Tianhua Tao, Junbo Li, Bowen Tan +8
Large Language Models (LLMs) specializing in code generation (which are also often referred to as code LLMs), e.g., StarCoder and Code Llama, play increasingly critical roles in va…
Bilingual Adaptation of Monolingual Foundation Models
Gurpreet Gosal, Yishi Xu, Gokul Ramakrishnan +19
We present an efficient method for adapting a monolingual Large Language Model (LLM) to another language, addressing challenges of catastrophic forgetting and tokenizer limitations…
Med42 -- Evaluating Fine-Tuning Strategies for Medical LLMs: Full-Parameter vs. Parameter-Efficient Approaches
Clément Christophe, Praveen K Kanithi, Prateek Munjal +13
This study presents a comprehensive analysis and comparison of two predominant fine-tuning methodologies - full-parameter fine-tuning and parameter-efficient tuning - within the co…
BTLM-3B-8K: 7B Parameter Performance in a 3B Parameter Model
Nolan Dey, Daria Soboleva, Faisal Al-Khateeb +11
We introduce the Bittensor Language Model, called "BTLM-3B-8K", a new state-of-the-art 3 billion parameter open-source language model. BTLM-3B-8K was trained on 627B tokens from th…
SlimPajama-DC: Understanding Data Combinations for LLM Training
Zhiqiang Shen, Tianhua Tao, Liqun Ma +8
This paper aims to understand the impacts of various data combinations (e.g., web text, Wikipedia, GitHub, books) on the pretraining of large language models using SlimPajama. Slim…