activity
20222025
most citedMiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

21 citations · 27 across the 8 of their papers we have counts for

collaborators

8 papers

cs.MM2025

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…

cs.CL2024★ 1 cited

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…

cs.CL2024

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…

cs.CL2024★ 21 cited

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…

cs.CL2024★ 2 cited

Bench: Extending Long Context Evaluation Beyond 100K Tokens

Xinrong Zhang, Yingfa Chen, Shengding Hu +8

Processing and reasoning over long contexts is crucial for many practical applications of Large Language Models (LLMs), such as document comprehension and agent construction. Despi…

cs.CL2024★ 2 cited

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…

cs.CL2023★ 1 cited

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…

cs.DL2022

Phocus: Picking Valuable Research from a Sea of Citations

Xinrong Zhang, Zihou Ren, Xi Li +5

The deluge of new papers has significantly blocked the development of academics, which is mainly caused by author-level and publication-level evaluation metrics that only focus on…