14 citations · 23 across the 10 of their papers we have counts for
10 papers
Prism-GRPO: Faster VLA Policy Optimization via Splitting Same-outcome Groups
Zeyun Deng, Yuzhe Lu, Yawei Wang +6
GRPO is increasingly used for reinforcement learning of vision-language-action (VLA) policies because, unlike PPO, it does not require training a critic. This simplification comes…
CLEAR: Context Augmentation from Contrastive Learning of Experience via Agentic Reflection
Linbo Liu, Guande Wu, Han Ding +7
Large language model agents rely on effective model context to obtain task-relevant information for decision-making. Many existing context engineering approaches primarily rely on…
Energy-Based Transfer for Reinforcement Learning
Zeyun Deng, Jasorsi Ghosh, Fiona Xie +4
Reinforcement learning remains sample inefficient, particularly when agents must adapt over time to related but distinct tasks, as in continual learning settings. Efficiency can be…
A Systematic Survey of Automatic Prompt Optimization Techniques
Kiran Ramnath, Kang Zhou, Sheng Guan +18
Since the advent of large language models (LLMs), prompt engineering has been a crucial step for eliciting desired responses for various Natural Language Processing (NLP) tasks. Ho…
Collaborative LLM Numerical Reasoning with Local Data Protection
Min Zhang, Yuzhe Lu, Yun Zhou +4
Numerical reasoning over documents, which demands both contextual understanding and logical inference, is challenging for low-capacity local models deployed on computation-constrai…
VL-Cache: Sparsity and Modality-Aware KV Cache Compression for Vision-Language Model Inference Acceleration
Dezhan Tu, Danylo Vashchilenko, Yuzhe Lu +1
Vision-Language Models (VLMs) have demonstrated impressive performance across a versatile set of tasks. A key challenge in accelerating VLMs is storing and accessing the large Key-…
Effectively Fine-tune to Improve Large Multimodal Models for Radiology Report Generation
Yuzhe Lu, Sungmin Hong, Yash Shah +1
Writing radiology reports from medical images requires a high level of domain expertise. It is time-consuming even for trained radiologists and can be error-prone for inexperienced…
On-the-fly Object Detection using StyleGAN with CLIP Guidance
Yuzhe Lu, Shusen Liu, Jayaraman J. Thiagarajan +2
We present a fully automated framework for building object detectors on satellite imagery without requiring any human annotation or intervention. We achieve this by leveraging the…
Simplified Gating in Long Short-term Memory (LSTM) Recurrent Neural Networks
Yuzhen Lu, Fathi M. Salem
The standard LSTM recurrent neural networks while very powerful in long-range dependency sequence applications have highly complex structure and relatively large (adaptive) paramet…
Empirical Evaluation of A New Approach to Simplifying Long Short-term Memory (LSTM)
Yuzhen Lu
The standard LSTM, although it succeeds in the modeling long-range dependences, suffers from a highly complex structure that can be simplified through modifications to its gate uni…