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cs.CL2026

Hy-MT2: A Family of Fast, Efficient and Powerful Multilingual Translation Models in the Wild

Mao Zheng, Zheng Li, Tao Chen +10

Hy-MT2 is a family of fast-thinking multilingual translation models designed for complex real-world scenarios. It includes three model sizes: 1.8B, 7B, and 30B-A3B (MoE), all of wh…

cs.CL2026

Revealing the Learning Dynamics of Long-Context Continual Pre-training

Yupu Liang, Shuang Chen, Guanwei Zhang +2

Existing studies on Long-Context Continual Pre-training (LCCP) mainly focus on small-scale models and limited data regimes (tens of billions of tokens). We argue that directly migr…

cs.CL2025

Hunyuan-TurboS: Advancing Large Language Models through Mamba-Transformer Synergy and Adaptive Chain-of-Thought

Tencent Hunyuan Team, Ao Liu, Botong Zhou +248

As Large Language Models (LLMs) rapidly advance, we introduce Hunyuan-TurboS, a novel large hybrid Transformer-Mamba Mixture of Experts (MoE) model. It synergistically combines Mam…

cs.CL202447 cited

Yi: Open Foundation Models by 01.AI

01. AI, :, Alex Young +30

We introduce the Yi model family, a series of language and multimodal models that demonstrate strong multi-dimensional capabilities. The Yi model family is based on 6B and 34B pret…

cs.CL2023

Dialog-to-Actions: Building Task-Oriented Dialogue System via Action-Level Generation

Yuncheng Hua, Xiangyu Xi, Zheng Jiang +4

End-to-end generation-based approaches have been investigated and applied in task-oriented dialogue systems. However, in industrial scenarios, existing methods face the bottlenecks…