4 papers
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…
Can Prompts Rewind Time for LLMs? Evaluating the Effectiveness of Prompted Knowledge Cutoffs
Xin Gao, Ruiyi Zhang, Daniel Du +3
Large Language Models (LLMs) are widely used for temporal prediction, but their reliance on pretraining data raises contamination concerns, as accurate predictions on pre-cutoff te…
Improving the Language Understanding Capabilities of Large Language Models Using Reinforcement Learning
Bokai Hu, Sai Ashish Somayajula, Xin Pan +1
Instruction-fine-tuned large language models (LLMs) under 14B parameters continue to underperform on natural language understanding (NLU) tasks, often trailing smaller models like…
Downstream Task Guided Masking Learning in Masked Autoencoders Using Multi-Level Optimization
Han Guo, Ramtin Hosseini, Ruiyi Zhang +4
Masked Autoencoder (MAE) is a notable method for self-supervised pretraining in visual representation learning. It operates by randomly masking image patches and reconstructing the…