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cs.CL2026
Instella-MoE Technical Report
Jiang Liu, Sudhanshu Ranjan, Prakamya Mishra +10
In this work, we introduce Instella-MoE, a fully open Mixture-of-Experts (MoE) language model with 16 billion total parameters and 2.8 billion active parameters per token, trained…
cs.CL2025
Instella: Fully Open Language Models with Stellar Performance
Jiang Liu, Jialian Wu, Xiaodong Yu +10
Large language models (LLMs) have demonstrated remarkable performance across a wide range of tasks, yet the majority of high-performing models remain closed-source or partially ope…
cs.CL2022
Progressive Sentiment Analysis for Code-Switched Text Data
Sudhanshu Ranjan, Dheeraj Mekala, Jingbo Shang
Multilingual transformer language models have recently attracted much attention from researchers and are used in cross-lingual transfer learning for many NLP tasks such as text cla…