6 citations · 12 across the 8 of their papers we have counts for
10 papers
Generative Modeling of Bach-Style Symbolic Music: A Comparative Study of Autoregressive, Latent-Variable, and Adversarial Approaches
Dezhi Yu, Kyuil Lee, Yongkang Huang
We study generative modeling of Bach-style symbolic piano music using a shared MIDI corpus and three model families: autoregressive LSTMs with attention, latent-variable models inc…
Direct Preference Optimization for Chatbot Fine-Tuning: An Empirical Study
Dezhi Yu, Yvonne Qiu, ShuoJia Fu
We present an approach to fine-tuning large language models using Direct Preference Optimization (DPO), a reinforcement learning technique. Our experimental results demonstrate tha…
How Far Are Video Models from True Multimodal Reasoning?
Xiaotian Zhang, Jianhui Wei, Yuan Wang +9
Despite remarkable progress toward general-purpose video models, a critical question remains unanswered: how far are these models from achieving true multimodal reasoning? Existing…
DK-RRT: Deep Koopman RRT for Collision-Aware Motion Planning of Space Manipulators in Dynamic Debris Environments
Qi Chen, Rui Liu, Kangtong Mo +2
Trajectory planning for robotic manipulators operating in dynamic orbital debris environments poses significant challenges due to complex obstacle movements and uncertainties. This…
AdaMixup: A Dynamic Defense Framework for Membership Inference Attack Mitigation
Ying Chen, Jiajing Chen, Yijie Weng +3
Membership inference attacks have emerged as a significant privacy concern in the training of deep learning models, where attackers can infer whether a data point was part of the t…
KVDirect: Distributed Disaggregated LLM Inference
Shiyang Chen, Rain Jiang, Dezhi Yu +6
Large Language Models (LLMs) have become the new foundation for many applications, reshaping human society like a storm. Disaggregated inference, which separates prefill and decode…
ROSE: A Reward-Oriented Data Selection Framework for LLM Task-Specific Instruction Tuning
Yang Wu, Huayi Zhang, Yizheng Jiao +6
Instruction tuning has underscored the significant potential of large language models (LLMs) in producing more human controllable and effective outputs in various domains. In this…
Research on reinforcement learning based warehouse robot navigation algorithm in complex warehouse layout
Keqin Li, Lipeng Liu, Jiajing Chen +5
In this paper, how to efficiently find the optimal path in complex warehouse layout and make real-time decision is a key problem. This paper proposes a new method of Proximal Polic…
Predicting 30-Day Hospital Readmission in Medicare Patients: Insights from an LSTM Deep Learning Model
Xintao Li, Sibei Liu, Dezhi Yu +2
Readmissions among Medicare beneficiaries are a major problem for the US healthcare system from a perspective of both healthcare operations and patient caregiving outcomes. Our stu…
Deep Reinforcement Learning-based Obstacle Avoidance for Robot Movement in Warehouse Environments
Keqin Li, Jiajing Chen, Denzhi Yu +9
At present, in most warehouse environments, the accumulation of goods is complex, and the management personnel in the control of goods at the same time with the warehouse mobile ro…