3 citations · 7 across the 19 of their papers we have counts for
13 papers · 1 filter
A Theoretical Framework for Masked Pretraining (MPT)
Qi Zhang, Runyu Zhou, Yifei Wang +1
Recently, Masked Pretraining (MPT) based on reconstruction pretraining tasks has risen to a promising self-supervised learning paradigm across various domains and achieves remarkab…
Beyond the Next Step: Variable-Length Latent World Models for Long-Horizon Planning
Tianqi Du, Qi Zhang, Yifei Wang +1
Recently, world models have emerged as a promising paradigm for building intelligent agents by learning predictive models that estimate future environment states conditioned on obs…
Scaling Attention via Feature Sparsity
Yan Xie, Tiansheng Wen, Tangda Huang +4
Scaling Transformers to ultra-long contexts is bottlenecked by the cost of self-attention. Existing methods reduce this cost along the sequence axis through local window…
LANPO: Bootstrapping Language and Numerical Feedback for Reinforcement Learning in LLMs
Ang Li, Yifei Wang, Zhihang Yuan +2
Reinforcement learning in large language models (LLMs) often relies on scalar rewards, a practice that discards valuable textual rationale buried in the rollouts, forcing the model…
G1: Teaching LLMs to Reason on Graphs with Reinforcement Learning
Xiaojun Guo, Ang Li, Yifei Wang +2
Although Large Language Models (LLMs) have demonstrated remarkable progress, their proficiency in graph-related tasks remains notably limited, hindering the development of truly ge…
On the Emergence of Position Bias in Transformers
Xinyi Wu, Yifei Wang, Stefanie Jegelka +1
Recent studies have revealed various manifestations of position bias in transformer architectures, from the "lost-in-the-middle" phenomenon to attention sinks, yet a comprehensive…