ICLR Papers
6,124 papers found • Page 86 of 123
Counting Graph Substructures with Graph Neural Networks
Charilaos Kanatsoulis, Alejandro Ribeiro
Course Correcting Koopman Representations
Mahan Fathi, Clement Gehring, Jonathan Pilault et al.
CoVLM: Composing Visual Entities and Relationships in Large Language Models Via Communicative Decoding
Junyan Li, Delin Chen, Yining Hong et al.
CPPO: Continual Learning for Reinforcement Learning with Human Feedback
Han Zhang, Yu Lei, Lin Gui et al.
CRAFT: Customizing LLMs by Creating and Retrieving from Specialized Toolsets
Lifan Yuan, Yangyi Chen, Xingyao Wang et al.
CrIBo: Self-Supervised Learning via Cross-Image Object-Level Bootstrapping
Tim Lebailly, Thomas Stegmüller, Behzad Bozorgtabar et al.
Critical Learning Periods Emerge Even in Deep Linear Networks
Michael Kleinman, Alessandro Achille, Stefano Soatto
CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing
Zhibin Gou, Zhihong Shao, Yeyun Gong et al.
CrossLoco: Human Motion Driven Control of Legged Robots via Guided Unsupervised Reinforcement Learning
Tianyu Li, Hyunyoung Jung, Matthew Gombolay et al.
Cross-Modal Contextualized Diffusion Models for Text-Guided Visual Generation and Editing
Ling Yang, Zhilong Zhang, Zhaochen Yu et al.
CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity
Aditya Bhatt, Daniel Palenicek, Boris Belousov et al.
Crystalformer: Infinitely Connected Attention for Periodic Structure Encoding
Tatsunori Taniai, Ryo Igarashi, Yuta Suzuki et al.
C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion
Hee Suk Yoon, Eunseop Yoon, Joshua Tian Jin Tee et al.
Curiosity-driven Red-teaming for Large Language Models
Zhang-Wei Hong, Idan Shenfeld, Johnson (Tsun-Hsuan) Wang et al.
Curriculum reinforcement learning for quantum architecture search under hardware errors
Yash J. Patel, Akash Kundu, Mateusz Ostaszewski et al.
Customizable Combination of Parameter-Efficient Modules for Multi-Task Learning
Haowen Wang, Tao Sun, Congyun Jin et al.
Cycle Consistency Driven Object Discovery
Aniket Rajiv Didolkar, Anirudh Goyal, Yoshua Bengio
DAFA: Distance-Aware Fair Adversarial Training
Hyungyu Lee, Saehyung Lee, Hyemi Jang et al.
DAM: Towards a Foundation Model for Forecasting
Luke Darlow, Qiwen Deng, Ahmed Hassan et al.
Data Debugging with Shapley Importance over Machine Learning Pipelines
Bojan Karlaš, David Dao, Matteo Interlandi et al.
Data Distillation Can Be Like Vodka: Distilling More Times For Better Quality
Xuxi Chen, Yu Yang, Zhangyang Wang et al.
Data Filtering Networks
Alex Fang, Albin Madappally Jose, Amit Jain et al.
Data-independent Module-aware Pruning for Hierarchical Vision Transformers
Yang He, Joey Tianyi Zhou
DataInf: Efficiently Estimating Data Influence in LoRA-tuned LLMs and Diffusion Models
Yongchan Kwon, Eric Wu, Kevin Wu et al.
DATS: Difficulty-Aware Task Sampler for Meta-Learning Physics-Informed Neural Networks
Maryam Toloubidokhti, Yubo Ye, Ryan Missel et al.
Davidsonian Scene Graph: Improving Reliability in Fine-grained Evaluation for Text-to-Image Generation
Jaemin Cho, Yushi Hu, Jason Baldridge et al.
DDMI: Domain-agnostic Latent Diffusion Models for Synthesizing High-Quality Implicit Neural Representations
Dogyun Park, Sihyeon Kim, Sojin Lee et al.
Debiased Collaborative Filtering with Kernel-Based Causal Balancing
Haoxuan Li, Chunyuan Zheng, Yanghao Xiao et al.
Debiasing Algorithm through Model Adaptation
Tomasz Limisiewicz, David Mareček, Tomáš Musil
Debiasing Attention Mechanism in Transformer without Demographics
Shenyu Lu, Yipei Wang, Xiaoqian Wang
Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold
Jun Chen, Haishan Ye, Mengmeng Wang et al.
Deceptive Fairness Attacks on Graphs via Meta Learning
Jian Kang, Yinglong Xia, Ross Maciejewski et al.
Decision ConvFormer: Local Filtering in MetaFormer is Sufficient for Decision Making
Jeonghye Kim, Su Young Lee, Woojun Kim et al.
Decodable and Sample Invariant Continuous Object Encoder
Dehao Yuan, Furong Huang, Cornelia Fermuller et al.
Decoding Natural Images from EEG for Object Recognition
Yonghao Song, Bingchuan Liu, Xiang Li et al.
DecompOpt: Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimization
Xiangxin Zhou, Xiwei Cheng, Yuwei Yang et al.
Decomposed Diffusion Sampler for Accelerating Large-Scale Inverse Problems
Hyungjin Chung, Suhyeon Lee, Jong Chul YE
Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces
Omer Nahum, Gali Noti, David Parkes et al.
Decoupled Marked Temporal Point Process using Neural Ordinary Differential Equations
Yujee Song, Donghyun LEE, Rui Meng et al.
Decoupling regularization from the action space
Sobhan Mohammadpour, Emma Frejinger, Pierre-Luc Bacon
Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks
Tianyu Fan, Lirong Wu, Yufei Huang et al.
Deep Confident Steps to New Pockets: Strategies for Docking Generalization
Gabriele Corso, Arthur Deng, Nicholas Polizzi et al.
Deep Generative Clustering with Multimodal Diffusion Variational Autoencoders
Emanuele Palumbo, Laura Manduchi, Sonia Laguna et al.
Deep Geodesic Canonical Correlation Analysis for Covariance-Based Neuroimaging Data
Ce Ju, Reinmar Kobler, Liyao Tang et al.
DEEP NEURAL NETWORK INITIALIZATION WITH SPARSITY INDUCING ACTIVATIONS
Ilan Price, Nicholas Daultry Ball, Adam Jones et al.
Deep Neural Networks Tend To Extrapolate Predictably
Katie Kang, Amrith Setlur, Claire Tomlin et al.
Deep Orthogonal Hypersphere Compression for Anomaly Detection
Yunhe Zhang, Yan Sun, Jinyu Cai et al.
Deep Reinforcement Learning for Modelling Protein Complexes
Ziqi Gao, Tao Feng, Jiaxuan You et al.
Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling
Cong Zhang, Zhiguang Cao, Wen Song et al.
Deep SE(3)-Equivariant Geometric Reasoning for Precise Placement Tasks
Ben Eisner, Yi Yang, Todor Davchev et al.