6 papers
Hybrid Gated Attention
Zekun Zhou, Ruobing Xie, Lanrui Wang +1
Gated attention is an effective approach to mitigate attention sinks and enhance the representational capacity of attention. To further extend its effectiveness-efficiency Pareto f…
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…
NeedleInATable: Exploring Long-Context Capability of Large Language Models towards Long-Structured Tables
Lanrui Wang, Mingyu Zheng, Hongyin Tang +5
Processing structured tabular data, particularly large and lengthy tables, constitutes a fundamental yet challenging task for large language models (LLMs). However, existing long-c…
A Factuality and Diversity Reconciled Decoding Method for Knowledge-Grounded Dialogue Generation
Chenxu Yang, Zheng Lin, Chong Tian +6
Grounding external knowledge can enhance the factuality of responses in dialogue generation. However, excessive emphasis on it might result in the lack of engaging and diverse expr…
TableDreamer: Progressive and Weakness-guided Data Synthesis from Scratch for Table Instruction Tuning
Mingyu Zheng, Zhifan Feng, Jia Wang +4
Despite the commendable progress of recent LLM-based data synthesis methods, they face two limitations in generating table instruction tuning data. First, they can not thoroughly e…
Sibyl: Empowering Empathetic Dialogue Generation in Large Language Models via Sensible and Visionary Commonsense Inference
Lanrui Wang, Jiangnan Li, Chenxu Yang +6
Recently, there has been a heightened interest in building chatbots based on Large Language Models (LLMs) to emulate human-like qualities in multi-turn conversations. Despite havin…