ICLR Papers

Local Composite Saddle Point Optimization

Site Bai, Brian Bullins

Local Graph Clustering with Noisy Labels

Artur Back de Luca, Kimon Fountoulakis, Shenghao Yang

Locality-Aware Graph Rewiring in GNNs

Federico Barbero, Ameya Velingker, Amin Saberi et al.

Locality Sensitive Sparse Encoding for Learning World Models Online

Zichen Liu, Chao Du, Wee Sun Lee et al.

Localizing and Editing Knowledge In Text-to-Image Generative Models

Samyadeep Basu, Nanxuan Zhao, Vlad Morariu et al.

Local Search GFlowNets

Minsu Kim, Yun Taeyoung, Emmanuel Bengio et al.

LoftQ: LoRA-Fine-Tuning-aware Quantization for Large Language Models

Yixiao Li, Yifan Yu, Chen Liang et al.

Logical Languages Accepted by Transformer Encoders with Hard Attention

Pablo Barcelo, Alexander Kozachinskiy, Anthony W. Lin et al.

LogicMP: A Neuro-symbolic Approach for Encoding First-order Logic Constraints

Weidi Xu, Jingwei Wang, Lele Xie et al.

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LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models

Yukang Chen, Shengju Qian, Haotian Tang et al.

Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation

Yunyang Li, Yusong Wang, Lin Huang et al.

Long-tailed Diffusion Models with Oriented Calibration

Tianjiao Zhang, Huangjie Zheng, Jiangchao Yao et al.

Long-Term Typhoon Trajectory Prediction: A Physics-Conditioned Approach Without Reanalysis Data

Young-Jae Park, Minseok Seo, Doyi Kim et al.

Look, Remember and Reason: Grounded Reasoning in Videos with Language Models

Apratim Bhattacharyya, Sunny Panchal, Reza Pourreza et al.

Looped Transformers are Better at Learning Learning Algorithms

Liu Yang, Kangwook Lee, Robert Nowak et al.

LOQA: Learning with Opponent Q-Learning Awareness

Milad Aghajohari, Juan Duque, Timotheus Cooijmans et al.

LoTa-Bench: Benchmarking Language-oriented Task Planners for Embodied Agents

Jae-Woo Choi, Youngwoo Yoon, Youngwoo Yoon et al.

Low Rank Matrix Completion via Robust Alternating Minimization in Nearly Linear Time

Yuzhou Gu, Zhao Song, Junze Yin et al.

lpNTK: Better Generalisation with Less Data via Sample Interaction During Learning

Shangmin Guo, YI REN, Stefano Albrecht et al.

LQ-LoRA: Low-rank plus Quantized Matrix Decomposition for Efficient Language Model Finetuning

Han Guo, Philip Greengard, Eric Xing et al.

LRM: Large Reconstruction Model for Single Image to 3D

Yicong Hong, Kai Zhang, Jiuxiang Gu et al.

LRR: Language-Driven Resamplable Continuous Representation against Adversarial Tracking Attacks

Jianlang Chen, Xuhong Ren, Qing Guo et al.

LUM-ViT: Learnable Under-sampling Mask Vision Transformer for Bandwidth Limited Optical Signal Acquisition

Lingfeng Liu, Dong Ni, Hangjie Yuan

LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language Models

Gunho Park, baeseong park, Minsub Kim et al.

M3C: A Framework towards Convergent, Flexible, and Unsupervised Learning of Mixture Graph Matching and Clustering

Jiaxin Lu, Zetian Jiang, Tianzhe Wang et al.

Machine Unlearning for Image-to-Image Generative Models

Guihong Li, Hsiang Hsu, Chun-Fu Chen et al.

Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors

Guocheng Qian, Jinjie Mai, Abdullah Hamdi et al.

MagicDrive: Street View Generation with Diverse 3D Geometry Control

Ruiyuan Gao, Kai Chen, Enze Xie et al.

MaGIC: Multi-modality Guided Image Completion

Hao Wang, Yongsheng Yu, Tiejian Luo et al.

Magnitude Invariant Parametrizations Improve Hypernetwork Learning

Jose Javier Gonzalez Ortiz, John Guttag, Adrian Dalca

Magnushammer: A Transformer-Based Approach to Premise Selection

Maciej Mikuła, Szymon Tworkowski, Szymon Antoniak et al.

Making LLaMA SEE and Draw with SEED Tokenizer

Yuying Ge, Sijie Zhao, Ziyun Zeng et al.

Making Pre-trained Language Models Great on Tabular Prediction

Jiahuan Yan, Bo Zheng, Hongxia Xu et al.

Making Retrieval-Augmented Language Models Robust to Irrelevant Context

Ori Yoran, Tomer Wolfson, Ori Ram et al.

Making RL with Preference-based Feedback Efficient via Randomization

Runzhe Wu, Wen Sun

MAMBA: an Effective World Model Approach for Meta-Reinforcement Learning

Zohar Rimon, Tom Jurgenson, Orr Krupnik et al.

MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning

Xiang Yue, Xingwei Qu, Ge Zhang et al.

Manifold Diffusion Fields

Ahmed Elhag, Ahmed Elhag, Yuyang Wang et al.

Manifold Preserving Guided Diffusion

Yutong He, Naoki Murata, Chieh-Hsin Lai et al.

Manipulating dropout reveals an optimal balance of efficiency and robustness in biological and machine visual systems

Jacob Prince, Gabriel Fajardo, George Alvarez et al.

MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding

Lirong Wu, Yijun Tian, Yufei Huang et al.

MAP IT to Visualize Representations

Robert Jenssen

Mask-Based Modeling for Neural Radiance Fields

Ganlin Yang, Guoqiang Wei, Zhizheng Zhang et al.

Masked Audio Generation using a Single Non-Autoregressive Transformer

Alon Ziv, Itai Gat, Gael Le Lan et al.

Masked Autoencoders with Multi-Window Local-Global Attention Are Better Audio Learners

Sarthak Yadav, Sergios Theodoridis, Lars Kai Hansen et al.

Masked Completion via Structured Diffusion with White-Box Transformers

Druv Pai, Sam Buchanan, Ziyang Wu et al.

Masked Distillation Advances Self-Supervised Transformer Architecture Search

Caixia Yan, Xiaojun Chang, Zhihui Li et al.

Masked Structural Growth for 2x Faster Language Model Pre-training

Yiqun Yao, Zheng Zhang, Jing Li et al.

Masks, Signs, And Learning Rate Rewinding

Advait Gadhikar, Rebekka Burkholz