accepted papers

Note we will have two poster sessions ([P1] and [P2]). Please check below when your poster shall be presented and see here when the two sessions will be held.

Video presentations of some of the accepted papers are available here

[P1] LoRA-Mini: Adaptation Matrices Decomposition and Selective Training

Ayush Singh, Rajdeep Aher, Shivank Garg
[P1] VB-LoRA: Extreme Parameter Efficient Fine-Tuning with Vector Banks

Yang Li, Shaobo Han, Shihao Ji
[P1] Non-negative Tensor Low-rank Decompositions Through the Lens of Information Geometry

Kazu Ghalamkari, Jesper Løve Hinrich, Morten Mørup
[P1] Privacy-Preserving Low-Rank Adaptation against Membership Inference Attacks for Latent Diffusion Models

Zihao Luo, Xilie Xu, Feng Liu, Yun Sing Koh, Di Wang, Jingfeng Zhang
[P1] Reinforcement Learning for Quantum Circuit Design: Using Matrix Representations

Zhiyuan Wang, Chunlin Feng, Christopher Poon, Lijian Huang, Xingjian Zhao, Yao Ma, Tianfan Fu, Xiao-Yang Liu
[P1] Low-Rank Adaptation with Task-Relevant Feature Enhancement for Fine-tuning Language Models

Changqun Li, Chaofan Ding, Kexin Luan, Xinhan Di
[P1] Compositionality Unlocks Deep Interpretable Models

Thomas Dooms, Ward Gauderis, Geraint A. Wiggins, Jose Oramas
[P1] KLay: Accelerating Sparse Arithmetic Circuits

Jaron Maene, Vincent Derkinderen, Pedro Zuidberg Dos Martires
[P2] On Faster Marginalization with Squared Circuits via Orthonormalization

Lorenzo Loconte, Antonio Vergari
[P1] Low-rank Finetuning for LLMs is Inherently Unfair

Saswat Das, Marco Romanelli, Cuong Tran, Bhavya Kailkhura, Ferdinando Fioretto
[P2] Transplanting Knowledge: A Study on Layer-Specific Grafting in LLMs

Bastien Zimmermann, Matthieu Boussard
[P2] Low-Rank Adapters Meet Neural Architecture Search for LLM Compression

Juan Pablo Munoz, Jinjie Yuan, Nilesh Jain
[P2] Low Tensor Rank Learning of Neural Dynamics

Arthur Pellegrino, N Alex Cayco Gajic, Angus Chadwick
[P2] Towards Symmetric Low-Rank Adapters

Tales Panoutsos Malheiros Lima, Rodrygo Santos, Flavio Figueiredo
[P2] FinLoRA: Finetuning Quantized Financial Large Language Models Using Low-Rank Adaptation

Dannong Wang, Daniel Kim, Bo Jin, Xingjian Zhao, Tianfan Fu, Steve Yang, Xiao-Yang Liu
[P2] Stochastic Gradient Descent on Tensors with Missing Data

Alexander Xue, Deanna Needell, Anna Ma
[P2] Restructuring Tractable Probabilistic Circuits

Honghua Zhang, Benjie Wang, Marcelo Arenas, Guy Van den Broeck
[P1] A Low-Rank Perspective on Oversmoothing in Graph Neural Networks

Kaicheng Zhang, Piero Deidda, Desmond Higham, Francesco Tudisco
[P2] Entropy Coding Compression of Tree Tensor Networks

Rafael Ballester-Ripoll, Roxana Bujack
[P2] Scaling up Probabilistic Circuits via Monarch Transformations

Honghua Zhang, Benjie Wang, Meihua Dang, Nanyun Peng, Stefano Ermon, Guy Van den Broeck
[P1] Low Rank Adaptations for Effective Machine Unlearning

Atharv Mittal