3 citations · 3 across the 11 of their papers we have counts for
4 papers · 1 filter
DreamPRM: Domain-Reweighted Process Reward Model for Multimodal Reasoning
Qi Cao, Ruiyi Wang, Ruiyi Zhang +2
Reasoning has substantially improved the performance of large language models (LLMs) on complicated tasks. Central to the current reasoning studies, Process Reward Models (PRMs) of…
TapWeight: Reweighting Pretraining Objectives for Task-Adaptive Pretraining
Ruiyi Zhang, Sai Ashish Somayajula, Pengtao Xie
Large-scale general domain pretraining followed by downstream-specific finetuning has become a predominant paradigm in machine learning. However, discrepancies between the pretrain…
Token-Specific Watermarking with Enhanced Detectability and Semantic Coherence for Large Language Models
Mingjia Huo, Sai Ashish Somayajula, Youwei Liang +3
Large language models generate high-quality responses with potential misinformation, underscoring the need for regulation by distinguishing AI-generated and human-written texts. Wa…
Improving Differentiable Architecture Search with a Generative Model
Ruisi Zhang, Youwei Liang, Sai Ashish Somayajula +1
In differentiable neural architecture search (NAS) algorithms like DARTS, the training set used to update model weight and the validation set used to update model architectures are…