ICML Papers
5,975 papers found • Page 111 of 120
Scaling Rectified Flow Transformers for High-Resolution Image Synthesis
Patrick Esser, Sumith Kulal, Andreas Blattmann et al.
Scaling Speech Technology to 1,000+ Languages
Vineel Pratap Konduru, Andros Tjandra, Bowen Shi et al.
Scaling Tractable Probabilistic Circuits: A Systems Perspective
Anji Liu, Kareem Ahmed, Guy Van den Broeck
SceneCraft: An LLM Agent for Synthesizing 3D Scenes as Blender Code
ziniu hu, Ahmet Iscen, Aashi Jain et al.
Scene Graph Generation Strategy with Co-occurrence Knowledge and Learnable Term Frequency
Hyeongjin Kim, Sangwon Kim, Dasom Ahn et al.
SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models
Xiaoxuan Wang, ziniu hu, Pan Lu et al.
Score-Based Causal Discovery of Latent Variable Causal Models
Ignavier Ng, Xinshuai Dong, Haoyue Dai et al.
Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation
Mingyuan Zhou, Huangjie Zheng, Zhendong Wang et al.
SCoRe: Submodular Combinatorial Representation Learning
Anay Majee, Suraj Kothawade, Krishnateja Killamsetty et al.
Scribble-Supervised Semantic Segmentation with Prototype-based Feature Augmentation
Guiyang Chan, Pengcheng Zhang, Hai Dong et al.
Second-Order Uncertainty Quantification: A Distance-Based Approach
Yusuf Sale, Viktor Bengs, Michele Caprio et al.
See More Details: Efficient Image Super-Resolution by Experts Mining
Eduard Zamfir, Zongwei Wu, Nancy Mehta et al.
Seesaw: Compensating for Nonlinear Reduction with Linear Computations for Private Inference
Fabing Li, Yuanhao Zhai, Shuangyu Cai et al.
Seizing Serendipity: Exploiting the Value of Past Success in Off-Policy Actor-Critic
Tianying Ji, Yu Luo, Fuchun Sun et al.
Selecting Large Language Model to Fine-tune via Rectified Scaling Law
Haowei Lin, Baizhou Huang, Haotian Ye et al.
Selective Mixup Helps with Distribution Shifts, But Not (Only) because of Mixup
Damien Teney, Jindong Wang, Ehsan Abbasnejad
Self-Alignment of Large Language Models via Monopolylogue-based Social Scene Simulation
Xianghe Pang, shuo tang, Rui Ye et al.
Self-attention Networks Localize When QK-eigenspectrum Concentrates
Han Bao, Ryuichiro Hataya, Ryo Karakida
Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian Processes
Yingyi Chen, Qinghua Tao, Francesco Tonin et al.
Self-cognitive Denoising in the Presence of Multiple Noisy Label Sources
Yi-Xuan Sun, Ya-Lin Zhang, BIN HAN et al.
Self-Composing Policies for Scalable Continual Reinforcement Learning
Mikel Malagón, Josu Ceberio, Jose A Lozano
Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction
He Zhang, Chang Liu, wang et al.
Self-Correcting Self-Consuming Loops for Generative Model Training
Nate Gillman, Michael Freeman, Daksh Aggarwal et al.
Self-Driven Entropy Aggregation for Byzantine-Robust Heterogeneous Federated Learning
Wenke Huang, Zekun Shi, Mang Ye et al.
SelfIE: Self-Interpretation of Large Language Model Embeddings
Haozhe Chen, Carl Vondrick, Chengzhi Mao
Self-Infilling Code Generation
Lin Zheng, Jianbo Yuan, Zhi Zhang et al.
Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models
Zixiang Chen, Yihe Deng, Huizhuo Yuan et al.
Self-Rewarding Language Models
Weizhe Yuan, Richard Yuanzhe Pang, Kyunghyun Cho et al.
Self-Supervised Coarsening of Unstructured Grid with Automatic Differentiation
Sergei Shumilin, Alexander Ryabov, Nikolay Yavich et al.
Self-Supervised Interpretable End-to-End Learning via Latent Functional Modularity
Hyunki Seong, Hyunchul Shim
SelfVC: Voice Conversion With Iterative Refinement using Self Transformations
Paarth Neekhara, Shehzeen Hussain, Rafael Valle et al.
SelMatch: Effectively Scaling Up Dataset Distillation via Selection-Based Initialization and Partial Updates by Trajectory Matching
Yongmin Lee, Hye Won Chung
Semantically-correlated memories in a dense associative model
Thomas F Burns
Semantic-Aware Human Object Interaction Image Generation
zhu xu, Qingchao Chen, Yuxin Peng et al.
SeMOPO: Learning High-quality Model and Policy from Low-quality Offline Visual Datasets
Shenghua Wan, Ziyuan Chen, Le Gan et al.
Sequence Compression Speeds Up Credit Assignment in Reinforcement Learning
Aditya A. Ramesh, Kenny Young, Louis Kirsch et al.
Sequential Asynchronous Action Coordination in Multi-Agent Systems: A Stackelberg Decision Transformer Approach
Bin Zhang, Hangyu Mao, Lijuan Li et al.
Sequential Disentanglement by Extracting Static Information From A Single Sequence Element
Nimrod Berman, Ilan Naiman, Idan Arbiv et al.
Sequential Kernel Goodness-of-fit Testing
Zhengyu Zhou, Weiwei Liu
Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models
Louis Sharrock, Jack Simons, Song Liu et al.
SFC: Achieve Accurate Fast Convolution under Low-precision Arithmetic
Liulu He, yufei zhao, rui gao et al.
SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning
Shuai Zhang, Heshan Fernando, Miao Liu et al.
Sharpness-Aware Data Generation for Zero-shot Quantization
Hoang Dung, Cuong Pham, Trung Le et al.
Sharp Rates in Dependent Learning Theory: Avoiding Sample Size Deflation for the Square Loss
Ingvar Ziemann, Stephen Tu, George Pappas et al.
Shifted Interpolation for Differential Privacy
Jinho Bok, Weijie Su, Jason Altschuler
SHINE: Shielding Backdoors in Deep Reinforcement Learning
Zhuowen Yuan, Wenbo Guo, Jinyuan Jia et al.
Short-Long Convolutions Help Hardware-Efficient Linear Attention to Focus on Long Sequences
Zicheng Liu, Siyuan Li, Li Wang et al.
Should we be going MAD? A Look at Multi-Agent Debate Strategies for LLMs
Andries Smit, Nathan Grinsztajn, Paul Duckworth et al.
SiBBlInGS: Similarity-driven Building-Block Inference using Graphs across States
Noga Mudrik, Gal Mishne, Adam Charles
Sign Gradient Descent-based Neuronal Dynamics: ANN-to-SNN Conversion Beyond ReLU Network
Hyunseok Oh, Youngki Lee