13 citations · 24 across the 13 of their papers we have counts for
13 papers
Orthogonal Model Merging
Sihan Yang, Kexuan Shi, Weiyang Liu
Merging finetuned Large Language Models (LLMs) has become increasingly important for integrating diverse capabilities into a single unified model. However, prevailing model merging…
CHIPS: Efficient CLIP Adaptation via Curvature-aware Hybrid Influence-based Data Selection
Xinlin Zhuang, Yichen Li, Xiwei Liu +11
Adapting CLIP to vertical domains is typically approached by novel fine-tuning strategies or by continual pre-training (CPT) on large domain-specific datasets. Yet, data itself rem…
VERA: Explainable Video Anomaly Detection via Verbalized Learning of Vision-Language Models
Muchao Ye, Weiyang Liu, Pan He
The rapid advancement of vision-language models (VLMs) has established a new paradigm in video anomaly detection (VAD): leveraging VLMs to simultaneously detect anomalies and provi…
Manifold-Constrained Nucleus-Level Denoising Diffusion Model for Structure-Based Drug Design
Shengchao Liu, Divin Yan, Weitao Du +6
Artificial intelligence models have shown great potential in structure-based drug design, generating ligands with high binding affinities. However, existing models have often overl…
Can Large Language Models Understand Symbolic Graphics Programs?
Zeju Qiu, Weiyang Liu, Haiwen Feng +7
Against the backdrop of enthusiasm for large language models (LLMs), there is a growing need to scientifically assess their capabilities and shortcomings. This is nontrivial in par…
ChatHuman: Chatting about 3D Humans with Tools
Jing Lin, Yao Feng, Weiyang Liu +1
Numerous methods have been proposed to detect, estimate, and analyze properties of people in images, including 3D pose, shape, contact, human-object interaction, and emotion. While…
Re-Thinking Inverse Graphics With Large Language Models
Peter Kulits, Haiwen Feng, Weiyang Liu +2
Inverse graphics -- the task of inverting an image into physical variables that, when rendered, enable reproduction of the observed scene -- is a fundamental challenge in computer…
GraphDreamer: Compositional 3D Scene Synthesis from Scene Graphs
Gege Gao, Weiyang Liu, Anpei Chen +2
As pretrained text-to-image diffusion models become increasingly powerful, recent efforts have been made to distill knowledge from these text-to-image pretrained models for optimiz…
Nonparametric Teaching for Multiple Learners
Chen Zhang, Xiaofeng Cao, Weiyang Liu +2
We study the problem of teaching multiple learners simultaneously in the nonparametric iterative teaching setting, where the teacher iteratively provides examples to the learner fo…
Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization
Weiyang Liu, Zeju Qiu, Yao Feng +11
Large foundation models are becoming ubiquitous, but training them from scratch is prohibitively expensive. Thus, efficiently adapting these powerful models to downstream tasks is…
Pairwise Similarity Learning is SimPLE
Yandong Wen, Weiyang Liu, Yao Feng +5
In this paper, we focus on a general yet important learning problem, pairwise similarity learning (PSL). PSL subsumes a wide range of important applications, such as open-set face…
Ghost on the Shell: An Expressive Representation of General 3D Shapes
Zhen Liu, Yao Feng, Yuliang Xiu +4
The creation of photorealistic virtual worlds requires the accurate modeling of 3D surface geometry for a wide range of objects. For this, meshes are appealing since they 1) enable…
Learning Disentangled Avatars with Hybrid 3D Representations
Yao Feng, Weiyang Liu, Timo Bolkart +3
Tremendous efforts have been made to learn animatable and photorealistic human avatars. Towards this end, both explicit and implicit 3D representations are heavily studied for a ho…