31 citations · 77 across the 20 of their papers we have counts for
20 papers
MAGNIFIED: RL Fine-tuning of Multimodal Large Language Models for Motion Planning
Letian Chen, Yiren Lu, Justin Fu +5
Multi-modal Large Language Models (MLLMs) have demonstrated remarkable capabilities in semantic understanding and common sense reasoning, making them promising candidates for solvi…
PulseCol: Periodically Refreshed Column-Sparse Attention for Accelerating Diffusion Language Models
Yanyi Lyu, Letian Chen, Futing Sun +3
Inference in diffusion large language models (dLLMs) is computationally expensive, as full self-attention must be repeatedly executed at each step of the denoising process without…
FlowLM: Few-Step Language Modeling via Diffusion-to-Flow Adaptation
Runzhe Zhang, Letian Chen, Wenpeng Zhang +2
We present FlowLM, a flow matching language model transformed from pre-trained diffusion language models via efficient fine-tuning. By re-aligning the curved sampling trajectories…
Towards Automated Semantic Interpretability in Reinforcement Learning via Vision-Language Models
Zhaoxin Li, Zhang Xi-Jia, Batuhan Altundas +3
Semantic interpretability in Reinforcement Learning (RL) enables transparency and verifiability of decision-making. Achieving semantic interpretability in reinforcement learning re…
ELEMENTAL: Interactive Learning from Demonstrations and Vision-Language Models for Reward Design in Robotics
Letian Chen, Nina Moorman, Matthew Gombolay
Reinforcement learning (RL) has demonstrated compelling performance in robotic tasks, but its success often hinges on the design of complex, ad hoc reward functions. Researchers ha…
Faster Model Predictive Control via Self-Supervised Initialization Learning
Zhaoxin Li, Xiaoke Wang, Letian Chen +3
Model Predictive Control (MPC) is widely used in robot control by optimizing a sequence of control outputs over a finite-horizon. Computational approaches for MPC include determini…