Most Cited 2024 "hierarchical interaction model" Papers
12,324 papers found • Page 62 of 62
Conference
GroupCover: A Secure, Efficient and Scalable Inference Framework for On-device Model Protection based on TEEs
Zheng Zhang, Na Wang, Ziqi Zhang et al.
Rethinking Guidance Information to Utilize Unlabeled Samples: A Label Encoding Perspective
Yulong Zhang, Yuan Yao, Shuhao Chen et al.
Two Heads Are Better Than One: Boosting Graph Sparse Training via Semantic and Topological Awareness
Guibin Zhang, Yanwei Yue, kun wang et al.
MLIP: Efficient Multi-Perspective Language-Image Pretraining with Exhaustive Data Utilization
Yu Zhang, Qi Zhang, Zixuan Gong et al.
Efficient Denoising Diffusion via Probabilistic Masking
Weizhong Zhang, Zhiwei Zhang, Renjie Pi et al.
Neural Jump-Diffusion Temporal Point Processes
Shuai Zhang, Chuan Zhou, Yang Liu et al.
Fast Text-to-3D-Aware Face Generation and Manipulation via Direct Cross-modal Mapping and Geometric Regularization
Jinlu Zhang, Yiyi Zhou, Qiancheng Zheng et al.
Accelerating Iterative Retrieval-augmented Language Model Serving with Speculation
Zhihao Zhang, Alan Zhu, Lijie Yang et al.
Absolute Policy Optimization: Enhancing Lower Probability Bound of Performance with High Confidence
Weiye Zhao, Feihan Li, Yifan Sun et al.
Rethinking Adversarial Robustness in the Context of the Right to be Forgotten
Chenxu Zhao, Wei Qian, Yangyi Li et al.
Unsupervised Representation Learning of Brain Activity via Bridging Voxel Activity and Functional Connectivity
Ali Behrouz, Parsa Delavari, Farnoosh Hashemi
Double-Step Alternating Extragradient with Increasing Timescale Separation for Finding Local Minimax Points: Provable Improvements
Kyuwon Kim, Donghwan Kim
CompeteAI: Understanding the Competition Dynamics of Large Language Model-based Agents
Qinlin Zhao, Jindong Wang, Yixuan Zhang et al.
LangCell: Language-Cell Pre-training for Cell Identity Understanding
Suyuan Zhao, Jiahuan Zhang, Yushuai Wu et al.
Graph-based Time Series Clustering for End-to-End Hierarchical Forecasting
Andrea Cini, Danilo Mandic, Cesare Alippi
Exploiting Negative Samples: A Catalyst for Cohort Discovery in Healthcare Analytics
Kaiping Zheng, Horng-Ruey Chua, Melanie Herschel et al.
Characteristic Guidance: Non-linear Correction for Diffusion Model at Large Guidance Scale
Candi Zheng, Yuan LAN
Premier-TACO is a Few-Shot Policy Learner: Pretraining Multitask Representation via Temporal Action-Driven Contrastive Loss
Ruijie Zheng, Yongyuan Liang, xiyao wang et al.
Learning Latent Space Hierarchical EBM Diffusion Models
Jiali Cui, Tian Han
DPN: Decoupling Partition and Navigation for Neural Solvers of Min-max Vehicle Routing Problems
zhi Zheng, Shunyu Yao, Zhenkun Wang et al.
Self-Infilling Code Generation
Lin Zheng, Jianbo Yuan, Zhi Zhang et al.
ERQ: Error Reduction for Post-Training Quantization of Vision Transformers
Yunshan Zhong, Jiawei Hu, You Huang et al.
Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret
Han Zhong, Jiachen Hu, Yecheng Xue et al.
GNNs Also Deserve Editing, and They Need It More Than Once
Shaochen (Henry) Zhong, Duy Le, Zirui Liu et al.
Causal-IQA: Towards the Generalization of Image Quality Assessment Based on Causal Inference
Yan Zhong, Xingyu Wu, Li Zhang et al.
Pedestrian Attribute Recognition as Label-balanced Multi-label Learning
Yibo Zhou, Hai-Miao Hu, Yirong Xiang et al.
Sequential Kernel Goodness-of-fit Testing
Zhengyu Zhou, Weiwei Liu
GALA3D: Towards Text-to-3D Complex Scene Generation via Layout-guided Generative Gaussian Splatting
Xiaoyu Zhou, Xingjian Ran, Yajiao Xiong et al.
Stabilizing Policy Gradients for Stochastic Differential Equations via Consistency with Perturbation Process
Xiangxin Zhou, Liang Wang, Yichi Zhou
DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection
Zhi Zhou, Ming Yang, Jiang-Xin Shi et al.
Graphon Mean Field Games with a Representative Player: Analysis and Learning Algorithm
Fuzhong Zhou, Chenyu Zhang, Xu Chen et al.
Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation
Mingyuan Zhou, Huangjie Zheng, Zhendong Wang et al.
Exploring Training on Heterogeneous Data with Mixture of Low-rank Adapters
Yuhang Zhou, Zhao Zihua, Siyuan Du et al.
Iterative Search Attribution for Deep Neural Networks
Zhiyu Zhu, Huaming Chen, Xinyi Wang et al.
Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF
Banghua Zhu, Michael Jordan, Jiantao Jiao
Toward Availability Attacks in 3D Point Clouds
Yifan Zhu, Yibo Miao, Yinpeng Dong et al.
Antibody Design Using a Score-based Diffusion Model Guided by Evolutionary, Physical and Geometric Constraints
Tian Zhu, Milong Ren, Haicang Zhang
Dynamic Evaluation of Large Language Models by Meta Probing Agents
Kaijie Zhu, Jindong Wang, Qinlin Zhao et al.
CRoFT: Robust Fine-Tuning with Concurrent Optimization for OOD Generalization and Open-Set OOD Detection
Lin Zhu, Yifeng Yang, Qinying Gu et al.
Stealthy Imitation: Reward-guided Environment-free Policy Stealing
Zhixiong Zhuang, Irina Nicolae, Mario Fritz
Reinformer: Max-Return Sequence Modeling for Offline RL
Zifeng Zhuang, Dengyun Peng, Jinxin Liu et al.
Towards Efficient Spiking Transformer: a Token Sparsification Framework for Training and Inference Acceleration
Zhengyang Zhuge, Peisong Wang, Xingting Yao et al.
Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models
Yongshuo Zong, Ondrej Bohdal, Tingyang Yu et al.
BiE: Bi-Exponent Block Floating-Point for Large Language Models Quantization
Lancheng Zou, Wenqian Zhao, Shuo Yin et al.
Visual Representation Learning with Stochastic Frame Prediction
Huiwon Jang, Dongyoung Kim, Junsu Kim et al.
Exploration and Anti-Exploration with Distributional Random Network Distillation
Kai Yang, jian tao, Jiafei Lyu et al.
Position: Is machine learning good or bad for the natural sciences?
David W. Hogg, Soledad Villar
Multi-class Probabilistic Bounds for Majority Vote Classifiers with Partially Labeled Data
Vasilii Feofanov, Emilie Devijver, Massih-Reza Amini
AquaLoRA: Toward White-box Protection for Customized Stable Diffusion Models via Watermark LoRA
Weitao Feng, Wenbo Zhou, Jiyan He et al.
Revisiting Character-level Adversarial Attacks for Language Models
Elias Abad Rocamora, Yongtao Wu, Fanghui Liu et al.
Position: Quo Vadis, Unsupervised Time Series Anomaly Detection?
M. Saquib Sarfraz, Mei-Yen Chen, Lukas Layer et al.
Scaling Beyond the GPU Memory Limit for Large Mixture-of-Experts Model Training
Yechan Kim, Hwijoon Lim, Dongsu Han
Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game
Zelai Xu, Chao Yu, Fei Fang et al.
COPAL: Continual Pruning in Large Language Generative Models
Srikanth Malla, Joon Hee Choi, Chiho Choi
Online Isolation Forest
Filippo Leveni, Guilherme Weigert Cassales, Bernhard Pfahringer et al.
Multimodal Prototyping for cancer survival prediction
Andrew Song, Richard Chen, Guillaume Jaume et al.
A Dense Reward View on Aligning Text-to-Image Diffusion with Preference
Shentao Yang, Tianqi Chen, Mingyuan Zhou
MorphGrower: A Synchronized Layer-by-layer Growing Approach for Plausible Neuronal Morphology Generation
Nianzu Yang, Kaipeng Zeng, Haotian Lu et al.
Counterfactual Metarules for Local and Global Recourse
Tom Bewley, Salim I. Amoukou, Saumitra Mishra et al.
UGrid: An Efficient-And-Rigorous Neural Multigrid Solver for Linear PDEs
Xi Han, Fei Hou, Hong Qin
RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback
Harrison Lee, Samrat Phatale, Hassan Mansoor et al.
Optimal Recurrent Network Topologies for Dynamical Systems Reconstruction
Christoph Jürgen Hemmer, Manuel Brenner, Florian Hess et al.
Unmasking Vulnerabilities: Cardinality Sketches under Adaptive Inputs
Sara Ahmadian, Edith Cohen
Knowledge-aware Reinforced Language Models for Protein Directed Evolution
Yuhao Wang, Qiang Zhang, Ming Qin et al.
Adapt and Diffuse: Sample-adaptive Reconstruction via Latent Diffusion Models
Zalan Fabian, Berk Tinaz, Mahdi Soltanolkotabi
DNCs Require More Planning Steps
Yara Shamshoum, Nitzan Hodos, Yuval Sieradzki et al.
I/O Complexity of Attention, or How Optimal is FlashAttention?
Barna Saha, Christopher Ye
A Distributional Analogue to the Successor Representation
Harley Wiltzer, Jesse Farebrother, Arthur Gretton et al.
A Theoretical Analysis of Backdoor Poisoning Attacks in Convolutional Neural Networks
Boqi Li, Weiwei Liu
Conditionally-Conjugate Gaussian Process Factor Analysis for Spike Count Data via Data Augmentation
Yididiya Nadew, Xuhui Fan, Christopher J Quinn
Understanding the Training Speedup from Sampling with Approximate Losses
Rudrajit Das, Xi Chen, Bertram Ieong et al.
Adaptive Horizon Actor-Critic for Policy Learning in Contact-Rich Differentiable Simulation
Ignat Georgiev, Krishnan Srinivasan, Jie Xu et al.
Mathematical Framework for Online Social Media Auditing
Wasim Huleihel, Yehonathan Refael
Low-Rank Similarity Mining for Multimodal Dataset Distillation
Yue Xu, Zhilin Lin, Yusong Qiu et al.
How Do Nonlinear Transformers Learn and Generalize in In-Context Learning?
Hongkang Li, Meng Wang, Songtao Lu et al.
Compositional Text-to-Image Generation with Dense Blob Representations
Weili Nie, Sifei Liu, Morteza Mardani et al.
Learning High-Frequency Functions Made Easy with Sinusoidal Positional Encoding
Chuanhao Sun, Zhihang Yuan, Kai Xu et al.
A Neural-Preconditioned Poisson Solver for Mixed Dirichlet and Neumann Boundary Conditions
Kai Weixian Lan, Elias Gueidon, Ayano Kaneda et al.
Do Topological Characteristics Help in Knowledge Distillation?
Jungeun Kim, Junwon You, Dongjin Lee et al.
DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems
Yair Schiff, Zhong Yi Wan, Jeffrey Parker et al.
Unveiling and Harnessing Hidden Attention Sinks: Enhancing Large Language Models without Training through Attention Calibration
Zhongzhi Yu, Zheng Wang, Yonggan Fu et al.
BAT: Learning to Reason about Spatial Sounds with Large Language Models
Zhisheng Zheng, Puyuan Peng, Ziyang Ma et al.
From Biased Selective Labels to Pseudo-Labels: An Expectation-Maximization Framework for Learning from Biased Decisions
Trenton Chang, Jenna Wiens
How Does Goal Relabeling Improve Sample Efficiency?
Sirui Zheng, Chenjia Bai, Zhuoran Yang et al.
Theory of Consistency Diffusion Models: Distribution Estimation Meets Fast Sampling
Zehao Dou, Minshuo Chen, Mengdi Wang et al.
Enhancing Adversarial Robustness in SNNs with Sparse Gradients
Yujia Liu, Tong Bu, Ding Jianhao et al.
Analysis for Abductive Learning and Neural-Symbolic Reasoning Shortcuts
Xiao-Wen Yang, Wen-Da Wei, Jie-Jing Shao et al.
On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis
Jerry Yao-Chieh Hu, Thomas Lin, Zhao Song et al.
EMC$^2$: Efficient MCMC Negative Sampling for Contrastive Learning with Global Convergence
Chung-Yiu Yau, Hoi To Wai, Parameswaran Raman et al.
Smoothness Adaptive Hypothesis Transfer Learning
Haotian Lin, Matthew Reimherr
Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection
Chentao Cao, Zhun Zhong, Zhanke Zhou et al.
Interacting Diffusion Processes for Event Sequence Forecasting
Mai Zeng, Florence Regol, Mark Coates
On Interpolating Experts and Multi-Armed Bandits
Houshuang Chen, Yuchen He, Chihao Zhang
NeuralIndicator: Implicit Surface Reconstruction from Neural Indicator Priors
Shi-Sheng Huang, Guo Chen, Li-heng Chen et al.
Size-invariance Matters: Rethinking Metrics and Losses for Imbalanced Multi-object Salient Object Detection
Feiran Li, Qianqian Xu, Shilong Bao et al.
RVI-SAC: Average Reward Off-Policy Deep Reinforcement Learning
Yukinari Hisaki, Isao Ono
Smooth Tchebycheff Scalarization for Multi-Objective Optimization
Xi Lin, Xiaoyuan Zhang, Zhiyuan Yang et al.
In-Context Unlearning: Language Models as Few-Shot Unlearners
Martin Pawelczyk, Seth Neel, Himabindu Lakkaraju
KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions
Fabian Fumagalli, Maximilian Muschalik, Patrick Kolpaczki et al.
Reference Neural Operators: Learning the Smooth Dependence of Solutions of PDEs on Geometric Deformations
Ze Cheng, Zhongkai Hao, Wang Xiaoqiang et al.
Accelerating Parallel Sampling of Diffusion Models
Zhiwei Tang, Jiasheng Tang, Hao Luo et al.
From Words to Actions: Unveiling the Theoretical Underpinnings of LLM-Driven Autonomous Systems
Jianliang He, Siyu Chen, Fengzhuo Zhang et al.
Acquiring Diverse Skills using Curriculum Reinforcement Learning with Mixture of Experts
Onur Celik, Aleksandar Taranovic, Gerhard Neumann
Inherent Trade-Offs between Diversity and Stability in Multi-Task Benchmarks
Guanhua Zhang, Moritz Hardt
On the Minimal Degree Bias in Generalization on the Unseen for non-Boolean Functions
Denys Pushkin, Raphaël Berthier, Emmanuel Abbe
Jacobian Regularizer-based Neural Granger Causality
Wanqi Zhou, Shuanghao Bai, Shujian Yu et al.
Projecting Molecules into Synthesizable Chemical Spaces
Shitong Luo, Wenhao Gao, Zuofan Wu et al.
Energy-based Backdoor Defense without Task-Specific Samples and Model Retraining
Yudong Gao, Honglong Chen, Peng Sun et al.
Break the Sequential Dependency of LLM Inference Using Lookahead Decoding
Yichao Fu, Peter Bailis, Ion Stoica et al.
Causal Inference from Competing Treatments
Ana-Andreea Stoica, Vivian Y. Nastl, Moritz Hardt
Denoising Autoregressive Representation Learning
Yazhe Li, Jorg Bornschein, Ting Chen
On a Neural Implementation of Brenier's Polar Factorization
Nina Vesseron, Marco Cuturi
Causally Motivated Personalized Federated Invariant Learning with Shortcut-Averse Information-Theoretic Regularization
Xueyang Tang, Song Guo, Jingcai Guo et al.
Privacy Attacks in Decentralized Learning
Abdellah El Mrini, Edwige Cyffers, Aurélien Bellet
Hybrid Neural Representations for Spherical Data
Hyomin Kim, Yunhui Jang, Jaeho Lee et al.
Mastering Zero-Shot Interactions in Cooperative and Competitive Simultaneous Games
Yannik Mahlau, Frederik Schubert, Bodo Rosenhahn
SparQ Attention: Bandwidth-Efficient LLM Inference
Luka Ribar, Ivan Chelombiev, Luke Hudlass-Galley et al.
Adaptive Stabilization Based on Machine Learning for Column Generation
Yunzhuang Shen, Yuan Sun, Xiaodong Li et al.
PAC-Bayesian Generalization Bounds for Knowledge Graph Representation Learning
Jaejun Lee, Minsung Hwang, Joyce Whang
Is In-Context Learning in Large Language Models Bayesian? A Martingale Perspective
Fabian Falck, Ziyu Wang, Christopher Holmes
Selective Mixup Helps with Distribution Shifts, But Not (Only) because of Mixup
Damien Teney, Jindong Wang, Ehsan Abbasnejad
Leveraging VLM-Based Pipelines to Annotate 3D Objects
Rishabh Kabra, Loic Matthey, Alexander Lerchner et al.
Understanding Heterophily for Graph Neural Networks
Junfu Wang, Yuanfang Guo, Liang Yang et al.
PEARL: Zero-shot Cross-task Preference Alignment and Robust Reward Learning for Robotic Manipulation
Runze Liu, Yali Du, Fengshuo Bai et al.