accepted.md

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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