1 citations · 1 across the 2 of their papers we have counts for
6 papers
Stuffed Mamba: Oversized States Lead to the Inability to Forget
Yingfa Chen, Xinrong Zhang, Shengding Hu +3
Recent advancements in recurrent architectures, such as Mamba and RWKV, have showcased strong language capabilities. Unlike transformer-based models, these architectures encode all…
Beyond the Turn-Based Game: Enabling Real-Time Conversations with Duplex Models
Xinrong Zhang, Yingfa Chen, Shengding Hu +6
As large language models (LLMs) increasingly permeate daily lives, there is a growing demand for real-time interactions that mirror human conversations. Traditional turn-based chat…
Mining the Social Fabric: Unveiling Communities for Fake News Detection in Short Videos
Haisong Gong, Bolan Su, Xinrong Zhang +4
Short video platforms have become a major medium for information sharing, but their rapid content generation and algorithmic amplification also enable the widespread dissemination…
Ouroboros: Generating Longer Drafts Phrase by Phrase for Faster Speculative Decoding
Weilin Zhao, Yuxiang Huang, Xu Han +7
Speculative decoding is a widely used method that accelerates the generation process of large language models (LLMs) with no compromise in model performance. It achieves this goal…
MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies
Shengding Hu, Yuge Tu, Xu Han +22
The burgeoning interest in developing Large Language Models (LLMs) with up to trillion parameters has been met with concerns regarding resource efficiency and practical expense, pa…
Predicting Emergent Abilities with Infinite Resolution Evaluation
Shengding Hu, Xin Liu, Xu Han +9
The scientific scale-up of large language models (LLMs) necessitates a comprehensive understanding of their scaling properties. However, the existing literature on the scaling prop…