5 papers · 1 filter
See it to Place it: Evolving Macro Placements with Vision-Language Models
Ikechukwu Uchendu, Swati Goel, Karly Hou +5
We propose using Vision-Language Models (VLMs) for macro placement in chip floorplanning, a complex optimization task that has recently shown promising advancements through machine…
EUGens: Efficient, Unified, and General Dense Layers
Sang Min Kim, Byeongchan Kim, Arijit Sehanobish +7
Efficient neural networks are essential for scaling machine learning models to real-time applications and resource-constrained environments. Fully-connected feedforward layers (FFL…
Sampling 3D Molecular Conformers with Diffusion Transformers
J. Thorben Frank, Winfried Ripken, Gregor Lied +3
Diffusion Transformers (DiTs) have demonstrated strong performance in generative modeling, particularly in image synthesis, making them a compelling choice for molecular conformer…
Sleepless Nights, Sugary Days: Creating Synthetic Users with Health Conditions for Realistic Coaching Agent Interactions
Taedong Yun, Eric Yang, Mustafa Safdari +13
We present an end-to-end framework for generating synthetic users for evaluating interactive agents designed to encourage positive behavior changes, such as in health and lifestyle…
Small steps no more: Global convergence of stochastic gradient bandits for arbitrary learning rates
Jincheng Mei, Bo Dai, Alekh Agarwal +4
We provide a new understanding of the stochastic gradient bandit algorithm by showing that it converges to a globally optimal policy almost surely using \emph{any} constant learnin…