13 papers
Surface-to-Skeleton 3D Cephalometry: Estimating Hidden Skeletal Landmarks from CT-Derived External Soft-Tissue Surfaces
Tomoki Abe, Taiki Kanaya, Kazuki Saita +4
Existing 3D facial-landmark methods localize points on visible skin, but whether CT-defined internal skeletal landmarks can be inferred from external soft-tissue geometry remains u…
When Rubrics Fail: Error Enumeration as Reward in Reference-Free RL Post-Training for Virtual Try-On
Wisdom Ikezogwo, Mehmet Saygin Seyfioglu, Ranjay Krishna +1
Reinforcement learning with verifiable rewards (RLVR) and Rubrics as Rewards (RaR) have driven strong gains in domains with clear correctness signals and even in subjective domains…
Learning to Reason Efficiently with Discounted Reinforcement Learning
Alex Ayoub, Kavosh Asadi, Dale Schuurmans +2
Large reasoning models (LRMs) often consume excessive tokens, inflating computational cost and latency. More broadly, in goal reaching sequential decision problems we often want to…
Universal Guideline-Driven Image Clustering via a Hybrid LLM Agent
Wenliang Zhong, Rob Barton, Lucas Goncalves +7
Unifying image clustering across different clustering scenarios remains challenging due to fundamental gaps among tasks. We introduce a Guideline-Driven Image Clustering Agent, the…
Style-Instructed Mask-Free Virtual Try On
Mengqi Zhang, Qi Li, Mehmet Saygin Seyfioglu +1
Virtual Try-On is a promising research area with broad applications in e-commerce and everyday life, enabling users to visualize garments on themselves or others before purchase. M…
Enabling Fine-Grained Operating Points for Black-Box LLMs
Ege Beyazit, KL Navaneet, Prashant Mathur +3
Black-box Large Language Models (LLMs) provide practical and accessible alternatives to other machine learning methods, as they require minimal labeled data and machine learning ex…