Summary of Prompt-based Length Controlled Generation with Reinforcement Learning, by Renlong Jie et al.
Prompt-Based Length Controlled Generation with Reinforcement Learningby Renlong Jie, Xiaojun Meng, Lifeng Shang, Xin Jiang,…
Summary of Archcomplete: Autoregressive 3d Architectural Design Generation with Hierarchical Diffusion-based Upsampling, by S. Rasoulzadeh et al.
ArchComplete: Autoregressive 3D Architectural Design Generation with Hierarchical Diffusion-Based Upsamplingby S. Rasoulzadeh, M. Bank, I.…
Summary of Distilled Decoding 1: One-step Sampling Of Image Auto-regressive Models with Flow Matching, by Enshu Liu et al.
Distilled Decoding 1: One-step Sampling of Image Auto-regressive Models with Flow Matchingby Enshu Liu, Xuefei…
Summary of When Worse Is Better: Navigating the Compression-generation Tradeoff in Visual Tokenization, by Vivek Ramanujan et al.
When Worse is Better: Navigating the compression-generation tradeoff in visual tokenizationby Vivek Ramanujan, Kushal Tirumala,…
Summary of Granger Causality Detection with Kolmogorov-arnold Networks, by Hongyu Lin et al.
Granger Causality Detection with Kolmogorov-Arnold Networksby Hongyu Lin, Mohan Ren, Paolo Barucca, Tomaso AsteFirst submitted…
Summary of Scamo: Exploring the Scaling Law in Autoregressive Motion Generation Model, by Shunlin Lu et al.
ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Modelby Shunlin Lu, Jingbo Wang, Zeyu…
Summary of Drivegpt: Scaling Autoregressive Behavior Models For Driving, by Xin Huang et al.
DriveGPT: Scaling Autoregressive Behavior Models for Drivingby Xin Huang, Eric M. Wolff, Paul Vernaza, Tung…
Summary of Numerical Pruning For Efficient Autoregressive Models, by Xuan Shen et al.
Numerical Pruning for Efficient Autoregressive Modelsby Xuan Shen, Zhao Song, Yufa Zhou, Bo Chen, Jing…
Summary of Emergence Of Abstractions: Concept Encoding and Decoding Mechanism For In-context Learning in Transformers, by Seungwook Han et al.
Emergence of Abstractions: Concept Encoding and Decoding Mechanism for In-Context Learning in Transformersby Seungwook Han,…
Summary of Bayesian Flow Is All You Need to Sample Out-of-distribution Chemical Spaces, by Nianze Tao
Bayesian Flow Is All You Need to Sample Out-of-Distribution Chemical Spacesby Nianze TaoFirst submitted to…