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First list of accepted papers
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arranger1044 committed Jan 10, 2025
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title: accepted papers
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# accepted papers

<div id="accepted-papers">
<ul>
<li>
<div class="paper-title">
<a href="https://openreview.net/forum?id=eWLtVJA6Um">
<b>LoRA-Mini: Adaptation Matrices Decomposition and Selective Training</b>
</a>
</div>
<div class="paper-authors">
<i>Ayush Singh, Rajdeep Aher, Shivank Garg</i>
</div>
</li>
<li>
<div class="paper-title">
<a href="https://openreview.net/forum?id=DGTH2eUU9U">
<b>VB-LoRA: Extreme Parameter Efficient Fine-Tuning with Vector Banks</b>
</a>
</div>
<div class="paper-authors">
<i>Yang Li, Shaobo Han, Shihao Ji </i>
</div>
</li>
<li>
<div class="paper-title">
<a href="https://openreview.net/forum?id=oie6YGA3Hm">
<b>Non-negative Tensor Low-rank Decompositions Through the Lens of Information Geometry</b>
</a>
</div>
<div class="paper-authors">
<i>Kazu Ghalamkari, Jesper Løve Hinrich, Morten Mørup</i>
</div>
</li>
<li>
<div class="paper-title">
<a href="https://openreview.net/forum?id=iVpribuyjP">
<b>Privacy-Preserving Low-Rank Adaptation against Membership Inference Attacks for Latent Diffusion Models</b>
</a>
</div>
<div class="paper-authors">
<i>Zihao Luo, Xilie Xu, Feng Liu, Yun Sing Koh, Di Wang, Jingfeng Zhang</i>
</div>
</li>
<li>
<div class="paper-title">
<a href="https://openreview.net/forum?id=XAseszkDDC">
<b>Reinforcement Learning for Quantum Circuit Design: Using Matrix Representations</b>
</a>
</div>
<div class="paper-authors">
<i>Zhiyuan Wang, Chunlin Feng, Christopher Poon, Lijian Huang, Xingjian Zhao, Yao Ma, Tianfan Fu, Xiao-Yang Liu </i>
</div>
</li>
<li>
<div class="paper-title">
<a href="https://openreview.net/forum?id=nqiFYh5VOV">
<b>Low-Rank Adaptation with Task-Relevant Feature Enhancement for Fine-tuning Language Models</b>
</a>
</div>
<div class="paper-authors">
<i>Changqun Li, Chaofan Ding, Kexin Luan, Xinhan Di</i>
</div>
</li>
<li>
<div class="paper-title">
<a href="https://openreview.net/forum?id=bXAt5iZ69l">
<b>Compositionality Unlocks Deep Interpretable Models</b>
</a>
</div>
<div class="paper-authors">
<i>Thomas Dooms, Ward Gauderis, Geraint A. Wiggins, Jose Oramas</i>
</div>
</li>
<li>
<div class="paper-title">
<a href="https://openreview.net/forum?id=vU8EPo44Gj">
<b>KLay: Accelerating Sparse Arithmetic Circuits</b>
</a>
</div>
<div class="paper-authors">
<i>Jaron Maene</i>
</div>
</li>
<li>
<div class="paper-title">
<a href="https://openreview.net/forum?id=WTRBDY9m3n">
<b>On Faster Marginalization with Squared Circuits via Orthonormalization</b>
</a>
</div>
<div class="paper-authors">
<i>Lorenzo Loconte, Antonio Vergari</i>
</div>
</li>
<li>
<div class="paper-title">
<a href="https://openreview.net/forum?id=qfVxGq2iiH">
<b>Low-rank Finetuning for LLMs is Inherently Unfair</b>
</a>
</div>
<div class="paper-authors">
<i>Saswat Das, Marco Romanelli, Cuong Tran, Bhavya Kailkhura, Ferdinando Fioretto</i>
</div>
</li>
<li>
<div class="paper-title">
<a href="https://openreview.net/forum?id=IqYqXVmy0m">
<b>Transplanting Knowledge: A Study on Layer-Specific Grafting in LLMs</b>
</a>
</div>
<div class="paper-authors">
<i>Bastien Zimmermann, Matthieu Boussard</i>
</div>
</li>
<li>
<div class="paper-title">
<a href="https://openreview.net/forum?id=aGJOXujXlu">
<b>Low-Rank Adapters Meet Neural Architecture Search for LLM Compression</b>
</a>
</div>
<div class="paper-authors">
<i>Juan Pablo Munoz, Jinjie Yuan, Nilesh Jain</i>
</div>
</li>
<li>
<div class="paper-title">
<a href="https://openreview.net/forum?id=9wI3rO5QqM">
<b>Low Tensor Rank Learning of Neural Dynamics</b>
</a>
</div>
<div class="paper-authors">
<i>Arthur Pellegrino, N Alex Cayco Gajic, Angus Chadwick</i>
</div>
</li>
<li>
<div class="paper-title">
<a href="https://openreview.net/forum?id=f1R95AoSAQ">
<b>Towards Symmetric Low-Rank Adapters</b>
</a>
</div>
<div class="paper-authors">
<i>Tales Panoutsos Malheiros Lima, Rodrygo Santos, Flavio Figueiredo</i>
</div>
</li>
<li>
<div class="paper-title">
<a href="https://openreview.net/forum?id=QgYl2J2m4n">
<b>FinLoRA: Finetuning Quantized Financial Large Language Models Using Low-Rank Adaptation</b>
</a>
</div>
<div class="paper-authors">
<i>Dannong Wang, Daniel Kim, Bo Jin, Xingjian Zhao, Tianfan Fu, Steve Yang, Xiao-Yang Liu</i>
</div>
</li>
<li>
<div class="paper-title">
<a href="https://openreview.net/forum?id=rQf2Y7qit5">
<b>Stochastic Gradient Descent on Tensors with Missing Data</b>
</a>
</div>
<div class="paper-authors">
<i>Alexander Xue, Deanna Needell, Anna Ma</i>
</div>
</li>
<li>
<div class="paper-title">
<a href="https://openreview.net/forum?id=VEXnS9zBXg">
<b>Restructuring Tractable Probabilistic Circuits</b>
</a>
</div>
<div class="paper-authors">
<i>Honghua Zhang, Benjie Wang, Marcelo Arenas, Guy Van den Broeck</i>
</div>
</li>
<li>
<div class="paper-title">
<a href="https://openreview.net/forum?id=syr78TFSWp">
<b>A Low-Rank Perspective on Oversmoothing in Graph Neural Networks</b>
</a>
</div>
<div class="paper-authors">
<i>Kaicheng Zhang, Piero Deidda, Desmond Higham, Francesco Tudisco</i>
</div>
</li>
<li>
<div class="paper-title">
<a href="https://openreview.net/forum?id=hGsxrFF0tY">
<b>Entropy Coding Compression of Tree Tensor Networks</b>
</a>
</div>
<div class="paper-authors">
<i>Rafael Ballester-Ripoll, Roxana Bujack</i>
</div>
</li>
<li>
<div class="paper-title">
<a href="https://openreview.net/forum?id=XAO6PASnFO">
<b>Scaling up Probabilistic Circuits via Monarch Transformations</b>
</a>
</div>
<div class="paper-authors">
<i>Honghua Zhang, Benjie Wang, Meihua Dang, Nanyun Peng, Stefano Ermon, Guy Van den Broeck</i>
</div>
</li>
<li>
<div class="paper-title">
<a href="https://openreview.net/forum?id=AOj5DLBbdM">
<b>Low Rank Adaptations for Effective Machine Unlearning</b>
</a>
</div>
<div class="paper-authors">
<i>Atharv Mittal</i>
</div>
</li>
</ul>
</div>

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