ICLR Papers
6,124 papers found • Page 16 of 123
Data Selection via Optimal Control for Language Models
Yuxian Gu, Li Dong, Hongning Wang et al.
Dataset Distillation via Knowledge Distillation: Towards Efficient Self-Supervised Pre-training of Deep Networks
Siddharth Joshi, Jiayi Ni, Baharan Mirzasoleiman
Dataset Ownership Verification in Contrastive Pre-trained Models
Yuechen Xie, Jie Song, Mengqi Xue et al.
Data Shapley in One Training Run
Jiachen (Tianhao) Wang, Prateek Mittal, Dawn Song et al.
Data Taggants: Dataset Ownership Verification Via Harmless Targeted Data Poisoning
Wassim Bouaziz, Nicolas Usunier, El-Mahdi El-Mhamdi
Data Unlearning in Diffusion Models
Silas Alberti, Kenan Hasanaliyev, Manav Shah et al.
DaWin: Training-free Dynamic Weight Interpolation for Robust Adaptation
Changdae Oh, Yixuan Li, Kyungwoo Song et al.
DAWN: Dynamic Frame Avatar with Non-autoregressive Diffusion Framework for Talking head Video Generation
Hanbo Cheng, Limin Lin, Chenyu Liu et al.
DCT-CryptoNets: Scaling Private Inference in the Frequency Domain
Arjun Roy, Kaushik Roy
DebGCD: Debiased Learning with Distribution Guidance for Generalized Category Discovery
Yuanpei Liu, Kai Han
Debiasing Federated Learning with Correlated Client Participation
Zhenyu Sun, Ziyang Zhang, Zheng Xu et al.
Debiasing Mini-Batch Quadratics for Applications in Deep Learning
Lukas Nicola Tatzel, Bálint Mucsányi, Osane Hackel et al.
dEBORA: Efficient Bilevel Optimization-based low-Rank Adaptation
Emanuele Zangrando, Sara Venturini, Francesco Rinaldi et al.
Decentralized Optimization with Coupled Constraints
Demyan Yarmoshik, Alexander Rogozin, Nikita Kiselev et al.
Decentralized Sporadic Federated Learning: A Unified Algorithmic Framework with Convergence Guarantees
Shahryar Zehtabi, Dong-Jun Han, Rohit Parasnis et al.
DeciMamba: Exploring the Length Extrapolation Potential of Mamba
Assaf Ben-Kish, Itamar Zimerman, Shady Abu-Hussein et al.
Decision Information Meets Large Language Models: The Future of Explainable Operations Research
Yansen Zhang, Qingcan Kang, Wing Yin YU et al.
Decision Tree Induction Through LLMs via Semantically-Aware Evolution
Tennison Liu, Nicolas Huynh, Mihaela van der Schaar
Decoding Game: On Minimax Optimality of Heuristic Text Generation Strategies
Sijin Chen, Omar Hagrass, Jason Klusowski
Decomposition Polyhedra of Piecewise Linear Functions
Marie-Charlotte Brandenburg, Moritz Grillo, Christoph Hertrich
Deconstructing Denoising Diffusion Models for Self-Supervised Learning
Xinlei Chen, Zhuang Liu, Saining Xie et al.
Deconstructing What Makes a Good Optimizer for Autoregressive Language Models
Rosie Zhao, Depen Morwani, David Brandfonbrener et al.
DECO: Unleashing the Potential of ConvNets for Query-based Detection and Segmentation
Xinghao Chen, Siwei Li, Yijing Yang et al.
Decoupled Finetuning for Domain Generalizable Semantic Segmentation
Jaehyun Pahk, Donghyeon Kwon, Seong Joon Oh et al.
Decoupled Graph Energy-based Model for Node Out-of-Distribution Detection on Heterophilic Graphs
Yuhan Chen, Yihong Luo, Yifan Song et al.
Decoupled Subgraph Federated Learning
Javad Aliakbari, Johan Östman, Alexandre Graell i Amat
Decoupling Angles and Strength in Low-rank Adaptation
Massimo Bini, Leander Girrbach, Zeynep Akata
Decoupling Layout from Glyph in Online Chinese Handwriting Generation
Minsi Ren, Yan-Ming Zhang, yi chen
DEEM: Diffusion models serve as the eyes of large language models for image perception
Run Luo, Yunshui Li, Longze Chen et al.
Deep Compression Autoencoder for Efficient High-Resolution Diffusion Models
Junyu Chen, Han Cai, Junsong Chen et al.
Deep Distributed Optimization for Large-Scale Quadratic Programming
Augustinos Saravanos, Hunter Kuperman, Alex Oshin et al.
DeeperForward: Enhanced Forward-Forward Training for Deeper and Better Performance
Liang Sun, Yang Zhang, Weizhao He et al.
DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale
Ziyang Zheng, Shan Huang, Jianyuan Zhong et al.
Deep Incomplete Multi-view Learning via Cyclic Permutation of VAEs
Xin Gao, Jian Pu
Deep Kernel Posterior Learning under Infinite Variance Prior Weights
Jorge Loría, Anindya Bhadra
Deep Kernel Relative Test for Machine-generated Text Detection
Yiliao Song, Zhenqiao Yuan, Shuhai Zhang et al.
Deep Learning Alternatives Of The Kolmogorov Superposition Theorem
Leonardo Ferreira Guilhoto, Paris Perdikaris
Deep Linear Probe Generators for Weight Space Learning
Jonathan Kahana, Eliahu Horwitz, Imri Shuval et al.
DeepLTL: Learning to Efficiently Satisfy Complex LTL Specifications for Multi-Task RL
Mathias Jackermeier, Alessandro Abate
Deep MMD Gradient Flow without adversarial training
Alexandre Galashov, Valentin De Bortoli, Arthur Gretton
Deep Networks Learn Features From Local Discontinuities in the Label Function
Prithaj Banerjee, Harish G Ramaswamy, Mahesh Yadav et al.
Deep Random Features for Scalable Interpolation of Spatiotemporal Data
Weibin Chen, Azhir Mahmood, Michel Tsamados et al.
DeepRTL: Bridging Verilog Understanding and Generation with a Unified Representation Model
Yi Liu, Changran Xu, Yunhao Zhou et al.
DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search
Huajian Xin, Z.Z. Ren, Junxiao Song et al.
Deep Signature: Characterization of Large-Scale Molecular Dynamics
Tiexin Qin, Mengxu ZHU, Chunyang Li et al.
DeepTAGE: Deep Temporal-Aligned Gradient Enhancement for Optimizing Spiking Neural Networks
Wei Liu, Li Yang, Mingxuan Zhao et al.
Deep Weight Factorization: Sparse Learning Through the Lens of Artificial Symmetries
Chris Kolb, Tobias Weber, Bernd Bischl et al.
DeFT: Decoding with Flash Tree-attention for Efficient Tree-structured LLM Inference
Jinwei Yao, Kaiqi Chen, Kexun Zhang et al.
DELIFT: Data Efficient Language model Instruction Fine-Tuning
Ishika Agarwal, Krishnateja Killamsetty, Lucian Popa et al.
DeLLMa: Decision Making Under Uncertainty with Large Language Models
Ollie Liu, Deqing Fu, Dani Yogatama et al.