7 papers
Normalized Low-Rank Adaptation
Jiale Kang, Ziyin Yue, Zheng Zhan +2
While low-rank adaptation (LoRA) is widely used for parameter-efficient model adaptation, how to regularize its training dynamics for stable and effective optimization remains unde…
PEFT-Arena: Understanding Parameter-Efficient Finetuning from a Stability-Plasticity Perspective
Yangyi Huang, Ruotian Peng, Zeju Qiu +4
Parameter-efficient finetuning (PEFT) has become the standard approach for adapting large language models, yet evaluations largely emphasize downstream accuracy while overlooking t…
When Good Equations Get Bad Scores: Improving Symbolic Regression Through Better Parameter Optimization
Boxiao Wang, Kai Li, Zhiwei Chen +5
Symbolic Regression (SR) plays a central role in scientific knowledge discovery by distilling mathematical equations from observational data. Most existing SR methods function with…
Compositional Machine Design as Program Synthesis with LLMs
Wenqian Zhang, Yangyi Huang, Weiyang Liu +1
Large language models (LLMs) have shown strong abilities in writing and revising programs, yet many program-synthesis benchmarks still evaluate programs in symbolic or digital envi…
Symbolic Graphics Programming with Large Language Models
Yamei Chen, Haoquan Zhang, Yangyi Huang +4
Large language models (LLMs) excel at program synthesis, yet their ability to produce symbolic graphics programs (SGPs) that render into precise visual content remains underexplore…
Dream, Lift, Animate: From Single Images to Animatable Gaussian Avatars
Marcel C. Bühler, Ye Yuan, Xueting Li +3
We introduce Dream, Lift, Animate (DLA), a novel framework that reconstructs animatable 3D human avatars from a single image. This is achieved by leveraging multi-view generation,…