ICLR Papers
6,124 papers found • Page 97 of 123
Improved sampling via learned diffusions
Lorenz Richter, Julius Berner
Improved statistical and computational complexity of the mean-field Langevin dynamics under structured data
Atsushi Nitanda, Kazusato Oko, Taiji Suzuki et al.
Improved Techniques for Training Consistency Models
Yang Song, Prafulla Dhariwal
Improving Convergence and Generalization Using Parameter Symmetries
Bo Zhao, Robert M. Gower, Robin Walters et al.
Improving Domain Generalization with Domain Relations
Huaxiu Yao, Xinyu Yang, Xinyi Pan et al.
Improving equilibrium propagation without weight symmetry through Jacobian homeostasis
Axel Laborieux, Friedemann Zenke
Improving Generalization of Alignment with Human Preferences through Group Invariant Learning
Rui Zheng, Wei Shen, Yuan Hua et al.
Improving Intrinsic Exploration by Creating Stationary Objectives
Roger Creus Castanyer, Joshua Romoff, Glen Berseth
Improving LoRA in Privacy-preserving Federated Learning
Youbang Sun, Zitao Li, Yaliang Li et al.
Improving Non-Transferable Representation Learning by Harnessing Content and Style
Ziming Hong, Zhenyi Wang, Li Shen et al.
Improving Offline RL by Blending Heuristics
Sinong Geng, Aldo Pacchiano, Andrey Kolobov et al.
Improving protein optimization with smoothed fitness landscapes
Andrew Kirjner, Jason Yim, Raman Samusevich et al.
Improving the Convergence of Dynamic NeRFs via Optimal Transport
Sameera Ramasinghe, Violetta Shevchenko, Gil Avraham et al.
IMPUS: Image Morphing with Perceptually-Uniform Sampling Using Diffusion Models
Zhaoyuan Yang, Zhengyang Yu, Zhiwei Xu et al.
Incentive-Aware Federated Learning with Training-Time Model Rewards
Zhaoxuan Wu, Mohammad Mohammadi Amiri, Ramesh Raskar et al.
Incentivized Truthful Communication for Federated Bandits
Zhepei Wei, Chuanhao Li, Tianze Ren et al.
In-context Autoencoder for Context Compression in a Large Language Model
Tao Ge, Hu Jing, Lei Wang et al.
In-context Exploration-Exploitation for Reinforcement Learning
Zhenwen Dai, Federico Tomasi, Sina Ghiassian
In-Context Learning Dynamics with Random Binary Sequences
Eric Bigelow, Ekdeep Singh Lubana, Robert Dick et al.
In-Context Learning Learns Label Relationships but Is Not Conventional Learning
Jannik Kossen, Yarin Gal, Tom Rainforth
In-Context Learning through the Bayesian Prism
Madhur Panwar, Kabir Ahuja, Navin Goyal
In-Context Pretraining: Language Modeling Beyond Document Boundaries
Weijia Shi, Sewon Min, Maria Lomeli et al.
Increasing Model Capacity for Free: A Simple Strategy for Parameter Efficient Fine-tuning
Haobo Song, Haobo SONG, Hao Zhao et al.
Incremental Randomized Smoothing Certification
Shubham Dipak Ugare, Tarun Suresh, Debangshu Banerjee et al.
In defense of parameter sharing for model-compression
Aditya Desai, Anshumali Shrivastava
Independent-Set Design of Experiments for Estimating Treatment and Spillover Effects under Network Interference
Chencheng Cai, Xu Zhang, Edoardo Airoldi
Inducing High Energy-Latency of Large Vision-Language Models with Verbose Images
Kuofeng Gao, Yang Bai, Jindong Gu et al.
Influencer Backdoor Attack on Semantic Segmentation
Haoheng Lan, Jindong Gu, Philip Torr et al.
InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning
Ziheng Qin, Kai Wang, Zangwei Zheng et al.
InfoCon: Concept Discovery with Generative and Discriminative Informativeness
Ruizhe Liu, Qian Luo, Yanchao Yang
Information Bottleneck Analysis of Deep Neural Networks via Lossy Compression
Ivan Butakov, Aleksandr Tolmachev, Sofia Malanchuk et al.
Information Retention via Learning Supplemental Features
Zhipeng Xie, Yahe Li
Inherently Interpretable Time Series Classification via Multiple Instance Learning
Joseph Early, Gavin Cheung, Kurt Cutajar et al.
Initializing Models with Larger Ones
Zhiqiu Xu, Yanjie Chen, Kirill Vishniakov et al.
Inner Classifier-Free Guidance and Its Taylor Expansion for Diffusion Models
Shikun Sun, Longhui Wei, Zhicai Wang et al.
Input-gradient space particle inference for neural network ensembles
Trung Trinh, Markus Heinonen, Luigi Acerbi et al.
Ins-DetCLIP: Aligning Detection Model to Follow Human-Language Instruction
Renjie Pi, Lewei Yao, Jianhua Han et al.
InsertNeRF: Instilling Generalizability into NeRF with HyperNet Modules
Yanqi Bao, Tianyu Ding, Jing Huo et al.
INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection
Chao Chen, Kai Liu, Ze Chen et al.
InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation
Xingchao Liu, Xiwen Zhang, Jianzhu Ma et al.
#InsTag: Instruction Tagging for Analyzing Supervised Fine-tuning of Large Language Models
Keming Lu, Hongyi Yuan, Zheng Yuan et al.
Instant3D: Fast Text-to-3D with Sparse-view Generation and Large Reconstruction Model
Jiahao Li, Hao Tan, Kai Zhang et al.
InstructCV: Instruction-Tuned Text-to-Image Diffusion Models as Vision Generalists
Yulu Gan, Sung Woo Park, Alexander Schubert et al.
InstructDET: Diversifying Referring Object Detection with Generalized Instructions
Ronghao Dang, Jiangyan Feng, Haodong Zhang et al.
Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy Instructions
Taehyeon Kim, JOONKEE KIM, Gihun Lee et al.
InstructPix2NeRF: Instructed 3D Portrait Editing from a Single Image
Jianhui Li, Shilong Liu, Zidong Liu et al.
InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Prior
Chenguo Lin, Yadong MU
Integrating Planning and Deep Reinforcement Learning via Automatic Induction of Task Substructures
Jung-Chun Liu, Chi-Hsien Chang, Shao-Hua Sun et al.
Intelligent Switching for Reset-Free RL
Darshan Patil, Janarthanan Rajendran, Glen Berseth et al.
Internal Cross-layer Gradients for Extending Homogeneity to Heterogeneity in Federated Learning
Yun-Hin Chan, Rui Zhou, Running Zhao et al.