5 papers
ExoPredicator: Learning Abstract Models of Dynamic Worlds for Robot Planning
Yichao Liang, Dat Nguyen, Cambridge Yang +7
Long-horizon embodied planning is challenging because the world does not only change through an agent's actions: exogenous processes (e.g., water heating, dominoes cascading) unfol…
Asynchronous Heavy-Tailed Optimization
Junfei Sun, Dixi Yao, Xuchen Gong +3
Heavy-tailed stochastic gradient noise, commonly observed in transformer models, can destabilize the optimization process. Recent works mainly focus on developing and understanding…
Amber-Image: Efficient Compression of Large-Scale Diffusion Transformers
Chaojie Yang, Tian Li, Yue Zhang +1
Diffusion Transformer (DiT) architectures have significantly advanced Text-to-Image (T2I) generation but suffer from prohibitive computational costs and deployment barriers. To add…
Hold Onto That Thought: Assessing KV Cache Compression On Reasoning
Minghui Liu, Aadi Palnitkar, Tahseen Rabbani +9
Large language models (LLMs) have demonstrated remarkable performance on long-context tasks, but are often bottlenecked by memory constraints. Namely, the KV cache, which is used t…
Large-scale automatic carbon ion treatment planning for head and neck cancers via parallel multi-agent reinforcement learning
Jueye Zhang, Chao Yang, Youfang Lai +9
Head-and-neck cancer (HNC) planning is difficult because multiple critical organs-at-risk (OARs) are close to complex targets. Intensity-modulated carbon-ion therapy (IMCT) offers…