Most Cited 2024 "conditional score networks" Papers
12,324 papers found • Page 39 of 62
Conference
Improving Sharpness-Aware Minimization by Lookahead
Runsheng Yu, Youzhi Zhang, James Kwok
SHINE: Shielding Backdoors in Deep Reinforcement Learning
Zhuowen Yuan, Wenbo Guo, Jinyuan Jia et al.
Not Just Pretty Pictures: Toward Interventional Data Augmentation Using Text-to-Image Generators
Jianhao Yuan, Francesco Pinto, Adam Davies et al.
DiffAug: Enhance Unsupervised Contrastive Learning with Domain-Knowledge-Free Diffusion-based Data Augmentation
Zelin Zang, Hao Luo, Kai Wang et al.
Robustly Learning Single-Index Models via Alignment Sharpness
Nikos Zarifis, Puqian Wang, Ilias Diakonikolas et al.
In-Context Decision Transformer: Reinforcement Learning via Hierarchical Chain-of-Thought
sili huang, Jifeng Hu, Hechang Chen et al.
tnGPS: Discovering Unknown Tensor Network Structure Search Algorithms via Large Language Models (LLMs)
Junhua Zeng, Chao Li, Zhun Sun et al.
Token-level Direct Preference Optimization
Yongcheng Zeng, Guoqing Liu, Weiyu Ma et al.
Learning Reward for Robot Skills Using Large Language Models via Self-Alignment
Yuwei Zeng, Yao Mu, Lin Shao
Graph Mixup on Approximate Gromov–Wasserstein Geodesics
Zhichen Zeng, Ruizhong Qiu, Zhe Xu et al.
IM-Unpack: Training and Inference with Arbitrarily Low Precision Integers
Zhanpeng Zeng, Karthikeyan Sankaralingam, Vikas Singh
Differentiable Annealed Importance Sampling Minimizes The Jensen-Shannon Divergence Between Initial and Target Distribution
Johannes Zenn, Robert Bamler
Robust Learning-Augmented Dictionaries
Ali Zeynali, Shahin Kamali, Mohammad Hajiesmaili
Tight Partial Identification of Causal Effects with Marginal Distribution of Unmeasured Confounders
Zhiheng Zhang
DAG-Based Column Generation for Adversarial Team Games
Youzhi Zhang, Bo An, Daniel Zeng
Efficient Stochastic Approximation of Minimax Excess Risk Optimization
Lijun Zhang, Haomin Bai, Wei-Wei Tu et al.
Discounted Adaptive Online Learning: Towards Better Regularization
Zhiyu Zhang, David Bombara, Heng Yang
Provably Efficient Partially Observable Risk-sensitive Reinforcement Learning with Hindsight Observation
Tonghe Zhang, Yu Chen, Longbo Huang
Self-Supervised Coarsening of Unstructured Grid with Automatic Differentiation
Sergei Shumilin, Alexander Ryabov, Nikolay Yavich et al.
LQER: Low-Rank Quantization Error Reconstruction for LLMs
Cheng Zhang, Jianyi Cheng, George Constantinides et al.
Random Scaling and Momentum for Non-smooth Non-convex Optimization
Qinzi Zhang, Ashok Cutkosky
Look Ahead or Look Around? A Theoretical Comparison Between Autoregressive and Masked Pretraining
Qi Zhang, Tianqi Du, Haotian Huang et al.
CaM: Cache Merging for Memory-efficient LLMs Inference
Yuxin Zhang, Yuxuan Du, Gen Luo et al.
Watermarks in the Sand: Impossibility of Strong Watermarking for Language Models
Hanlin Zhang, Benjamin Edelman, Danilo Francati et al.
MILP-FBGen: LP/MILP Instance Generation with Feasibility/Boundedness
Yahong Zhang, Chenchen Fan, Donghui Chen et al.
ILILT: Implicit Learning of Inverse Lithography Technologies
Haoyu Yang, Mark Ren
SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning
Shuai Zhang, Heshan Fernando, Miao Liu et al.
More Benefits of Being Distributional: Second-Order Bounds for Reinforcement Learning
Kaiwen Wang, Owen Oertell, Alekh Agarwal et al.
Advancing DRL Agents in Commercial Fighting Games: Training, Integration, and Agent-Human Alignment
Chen Zhang, Qiang HE, Yuan Zhou et al.
Parameter-Efficient Fine-Tuning with Controls
Chi Zhang, Jingpu Cheng, Yanyu Xu et al.
Deep Regression Representation Learning with Topology
Shihao Zhang, Kenji Kawaguchi, Angela Yao
Understanding Unimodal Bias in Multimodal Deep Linear Networks
Yedi Zhang, Peter Latham, Andrew Saxe
Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark
Yihua Zhang, Pingzhi Li, Junyuan Hong et al.
S3O: A Dual-Phase Approach for Reconstructing Dynamic Shape and Skeleton of Articulated Objects from Single Monocular Video
Hao Zhang, Fang Li, Samyak Rawlekar et al.
Understanding and Diagnosing Deep Reinforcement Learning
Ezgi Korkmaz
Tackling Non-Stationarity in Reinforcement Learning via Causal-Origin Representation
Wanpeng Zhang, Yilin Li, Boyu Yang et al.
Multi-Factor Adaptive Vision Selection for Egocentric Video Question Answering
Haoyu Zhang, Meng Liu, Zixin Liu et al.
UP2ME: Univariate Pre-training to Multivariate Fine-tuning as a General-purpose Framework for Multivariate Time Series Analysis
Yunhao Zhang, Liu Minghao, Shengyang Zhou et al.
Improving Accuracy-robustness Trade-off via Pixel Reweighted Adversarial Training
Jiacheng Zhang, Feng Liu, Dawei Zhou et al.
MagicLens: Self-Supervised Image Retrieval with Open-Ended Instructions
Kai Zhang, Yi Luan, Hexiang Hu et al.
Wukong: Towards a Scaling Law for Large-Scale Recommendation
Buyun Zhang, Liang Luo, Yuxin Chen et al.
Nonparametric Teaching of Implicit Neural Representations
Chen Zhang, Steven T. S. Luo, Jason Chun Lok Li et al.
Sparse-to-dense Multimodal Image Registration via Multi-Task Learning
Kaining Zhang, Jiayi Ma
In-Context Principle Learning from Mistakes
Tianjun Zhang, Aman Madaan, Luyu Gao et al.
A Federated Stochastic Multi-level Compositional Minimax Algorithm for Deep AUC Maximization
Xinwen Zhang, Ali Payani, Myungjin Lee et al.
Riemannian Preconditioned LoRA for Fine-Tuning Foundation Models
Fangzhao Zhang, Mert Pilanci
Enhancing Storage and Computational Efficiency in Federated Multimodal Learning for Large-Scale Models
Zixin Zhang, Fan Qi, Changsheng Xu
Online Resource Allocation with Non-Stationary Customers
Xiaoyue Zhang, Hanzhang Qin, Mabel Chou
Debiased Offline Representation Learning for Fast Online Adaptation in Non-stationary Dynamics
Xinyu Zhang, Wenjie Qiu, Yi-Chen Li et al.
Fair Risk Control: A Generalized Framework for Calibrating Multi-group Fairness Risks
Lujing Zhang, Aaron Roth, Linjun Zhang
Online Matching with Stochastic Rewards: Provable Better Bound via Adversarial Reinforcement Learning
Qiankun Zhang, Aocheng Shen, Boyu Zhang et al.
Trustworthy Alignment of Retrieval-Augmented Large Language Models via Reinforcement Learning
Zongmeng Zhang, Yufeng Shi, Jinhua Zhu et al.
Switchable Decision: Dynamic Neural Generation Networks
Shujian Zhang, Korawat Tanwisuth, Chengyue Gong et al.
Interpreting and Improving Large Language Models in Arithmetic Calculation
Wei Zhang, Wan Chaoqun, Yonggang Zhang et al.
GroupCover: A Secure, Efficient and Scalable Inference Framework for On-device Model Protection based on TEEs
Zheng Zhang, Na Wang, Ziqi Zhang et al.
Candidate Pseudolabel Learning: Enhancing Vision-Language Models by Prompt Tuning with Unlabeled Data
Jiahan Zhang, Qi Wei, Feng Liu et al.
Exploring the Benefit of Activation Sparsity in Pre-training
Zhengyan Zhang, Chaojun Xiao, Qiujieli Qin et al.
Causal Representation Learning from Multiple Distributions: A General Setting
Kun Zhang, Shaoan Xie, Ignavier Ng et al.
FESSNC: Fast Exponentially Stable and Safe Neural Controller
Jingdong Zhang, Luan Yang, Qunxi Zhu et al.
Rethinking Guidance Information to Utilize Unlabeled Samples: A Label Encoding Perspective
Yulong Zhang, Yuan Yao, Shuhao Chen et al.
Minimax Optimality of Score-based Diffusion Models: Beyond the Density Lower Bound Assumptions
Kaihong Zhang, Heqi Yin, Feng Liang 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.
Beyond the ROC Curve: Classification Trees Using Cost-Optimal Curves, with Application to Imbalanced Datasets
Magzhan Gabidolla, Arman Zharmagambetov, Miguel Carreira-Perpinan
Distributionally Robust Data Valuation
Xiaoqiang Lin, Xinyi Xu, Zhaoxuan Wu et al.
MLIP: Efficient Multi-Perspective Language-Image Pretraining with Exhaustive Data Utilization
Yu Zhang, Qi Zhang, Zixuan Gong et al.
Efficient Contextual Bandits with Uninformed Feedback Graphs
Mengxiao Zhang, Yuheng Zhang, Haipeng Luo et al.
Efficient Denoising Diffusion via Probabilistic Masking
Weizhong Zhang, Zhiwei Zhang, Renjie Pi et al.
Confronting Reward Overoptimization for Diffusion Models: A Perspective of Inductive and Primacy Biases
Ziyi Zhang, Sen Zhang, Yibing Zhan et al.
Uncertainty-Aware Reward-Free Exploration with General Function Approximation
Junkai Zhang, Weitong Zhang, Dongruo Zhou et al.
Feature Contamination: Neural Networks Learn Uncorrelated Features and Fail to Generalize
Tianren Zhang, Chujie Zhao, Guanyu Chen et al.
On the Expressive Power of Spectral Invariant Graph Neural Networks
Bohang Zhang, Lingxiao Zhao, Haggai Maron
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.
Position: Measure Dataset Diversity, Don't Just Claim It
Dora Zhao, Jerone Andrews, Orestis Papakyriakopoulos et al.
Long Is More for Alignment: A Simple but Tough-to-Beat Baseline for Instruction Fine-Tuning
Hao Zhao, Maksym Andriushchenko, Francesco Croce et al.
Absolute Policy Optimization: Enhancing Lower Probability Bound of Performance with High Confidence
Weiye Zhao, Feihan Li, Yifan Sun et al.
Spider: A Unified Framework for Context-dependent Concept Segmentation
Xiaoqi Zhao, Youwei Pang, Wei Ji et al.
Rethinking Adversarial Robustness in the Context of the Right to be Forgotten
Chenxu Zhao, Wei Qian, Yangyi Li et al.
Quantum Implicit Neural Representations
Jiaming Zhao, Wenbo Qiao, Peng Zhang et al.
Is Inverse Reinforcement Learning Harder than Standard Reinforcement Learning? A Theoretical Perspective
Lei Zhao, Mengdi Wang, Yu Bai
A Statistical Theory of Regularization-Based Continual Learning
Xuyang Zhao, Huiyuan Wang, Weiran Huang 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.
Conformal Predictions under Markovian Data
Frédéric Zheng, Alexandre Proutiere
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.
On Prompt-Driven Safeguarding for Large Language Models
Chujie Zheng, Fan Yin, Hao Zhou 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.
On the Emergence of Cross-Task Linearity in Pretraining-Finetuning Paradigm
Zhanpeng Zhou, Zijun Chen, Yilan Chen et al.
Finite-Time Convergence and Sample Complexity of Actor-Critic Multi-Objective Reinforcement Learning
Tianchen Zhou, Hairi, Haibo Yang et al.
Pedestrian Attribute Recognition as Label-balanced Multi-label Learning
Yibo Zhou, Hai-Miao Hu, Yirong Xiang et al.
Conformalized Adaptive Forecasting of Heterogeneous Trajectories
Yanfei Zhou, Lars Lindemann, Matteo Sesia
Sequential Kernel Goodness-of-fit Testing
Zhengyu Zhou, Weiwei Liu
RAUCA: A Novel Physical Adversarial Attack on Vehicle Detectors via Robust and Accurate Camouflage Generation
Jiawei Zhou, Linye Lyu, Daojing He et al.
CurBench: Curriculum Learning Benchmark
Yuwei Zhou, Zirui Pan, Xin Wang et al.
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.
ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL
Yifei Zhou, Andrea Zanette, Jiayi Pan 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.
Generative Active Learning for Long-tailed Instance Segmentation
Muzhi Zhu, Chengxiang Fan, Hao Chen et al.
Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF
Banghua Zhu, Michael Jordan, Jiantao Jiao
Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model
Lianghui Zhu, Bencheng Liao, Qian Zhang et al.
Switched Flow Matching: Eliminating Singularities via Switching ODEs
Qunxi Zhu, Wei Lin
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
Online Learning in Betting Markets: Profit versus Prediction
Haiqing Zhu, Alexander Soen, Yun Kuen Cheung et al.
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.
Translation Equivariant Transformer Neural Processes
Matthew Ashman, Cristiana Diaconu, Junhyuck Kim et al.
Language Models Represent Beliefs of Self and Others
Wentao Zhu, Zhining Zhang, Yizhou Wang
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.
Converting Transformers to Polynomial Form for Secure Inference Over Homomorphic Encryption
Itamar Zimerman, Moran Baruch, Nir Drucker et al.
Viewing Transformers Through the Lens of Long Convolutions Layers
Itamar Zimerman, Lior Wolf
Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models
Yongshuo Zong, Ondrej Bohdal, Tingyang Yu et al.
Compositional Few-Shot Class-Incremental Learning
Yixiong Zou, Shanghang Zhang, haichen zhou et al.
BiE: Bi-Exponent Block Floating-Point for Large Language Models Quantization
Lancheng Zou, Wenqian Zhao, Shuo Yin et al.
Improving Equivariant Graph Neural Networks on Large Geometric Graphs via Virtual Nodes Learning
Yuelin Zhang, Jiacheng Cen, Jiaqi Han et al.
REST: Efficient and Accelerated EEG Seizure Analysis through Residual State Updates
Arshia Afzal, Grigorios Chrysos, Volkan Cevher et al.
Amend to Alignment: Decoupled Prompt Tuning for Mitigating Spurious Correlation in Vision-Language Models
Jie ZHANG, Xiaosong Ma, Song Guo 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
Sample Complexity Bounds for Estimating Probability Divergences under Invariances
Behrooz Tahmasebi, Stefanie Jegelka
AquaLoRA: Toward White-box Protection for Customized Stable Diffusion Models via Watermark LoRA
Weitao Feng, Wenbo Zhou, Jiyan He et al.
On the Embedding Collapse when Scaling up Recommendation Models
Xingzhuo Guo, Junwei Pan, Ximei Wang 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
Position: Understanding LLMs Requires More Than Statistical Generalization
Patrik Reizinger, Szilvia Ujváry, Anna Mészáros et al.
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.
Differentially Private Sum-Product Networks
Xenia Heilmann, Mattia Cerrato, Ernst Althaus
Log Neural Controlled Differential Equations: The Lie Brackets Make A Difference
Benjamin Walker, Andrew McLeod, Tiexin QIN et al.
A Dense Reward View on Aligning Text-to-Image Diffusion with Preference
Shentao Yang, Tianqi Chen, Mingyuan Zhou
Improved Differentially Private and Lazy Online Convex Optimization: Lower Regret without Smoothness Requirements
Naman Agarwal, Satyen Kale, Karan Singh et al.
MorphGrower: A Synchronized Layer-by-layer Growing Approach for Plausible Neuronal Morphology Generation
Nianzu Yang, Kaipeng Zeng, Haotian Lu et al.
Expand-and-Cluster: Parameter Recovery of Neural Networks
Flavio Martinelli, Berfin Simsek, Wulfram Gerstner et al.
REMEDI: Corrective Transformations for Improved Neural Entropy Estimation
Viktor Nilsson, Anirban Samaddar, Sandeep Madireddy et al.
Principled Penalty-based Methods for Bilevel Reinforcement Learning and RLHF
Han Shen, Zhuoran Yang, Tianyi Chen
Momentor: Advancing Video Large Language Model with Fine-Grained Temporal Reasoning
Long Qian, Juncheng Li, Yu Wu 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
StackSight: Unveiling WebAssembly through Large Language Models and Neurosymbolic Chain-of-Thought Decompilation
Weike Fang, Zhejian Zhou, Junzhou He et al.
Disentangled Continual Graph Neural Architecture Search with Invariant Modular Supernet
Zeyang Zhang, Xin Wang, Yijian Qin et al.
Disentangled Graph Self-supervised Learning for Out-of-Distribution Generalization
Haoyang Li, Xin Wang, Zeyang Zhang et al.
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
On the Effectiveness of Supervision in Asymmetric Non-Contrastive Learning
Jeongheon Oh, Kibok Lee
DiracDiffusion: Denoising and Incremental Reconstruction with Assured Data-Consistency
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
Position: Data Authenticity, Consent, & Provenance for AI are all broken: what will it take to fix them?
Shayne Longpre, Robert Mahari, Naana Obeng-Marnu et al.
Lookbehind-SAM: k steps back, 1 step forward
Gonçalo Mordido, Pranshu Malviya, Aristide Baratin et al.
A Distributional Analogue to the Successor Representation
Harley Wiltzer, Jesse Farebrother, Arthur Gretton et al.
From Neurons to Neutrons: A Case Study in Interpretability
Ouail Kitouni, Niklas Nolte, Víctor Samuel Pérez-Díaz et al.
A Theoretical Analysis of Backdoor Poisoning Attacks in Convolutional Neural Networks
Boqi Li, Weiwei Liu
Do Transformer World Models Give Better Policy Gradients?
Michel Ma, Tianwei Ni, Clement Gehring et al.
Conformal prediction for multi-dimensional time series by ellipsoidal sets
Chen Xu, Hanyang Jiang, Yao Xie
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.
Skill Set Optimization: Reinforcing Language Model Behavior via Transferable Skills
Kolby Nottingham, Bodhisattwa Prasad Majumder, Bhavana Dalvi 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.
MC-GTA: Metric-Constrained Model-Based Clustering using Goodness-of-fit Tests with Autocorrelations
Zhangyu Wang, Gengchen Mai, Krzysztof Janowicz et al.
Enforcing Constraints in RNA Secondary Structure Predictions: A Post-Processing Framework Based on the Assignment Problem
Geewon Suh, Gyeongjo Hwang, SeokjunKang et al.
Reshape and Adapt for Output Quantization (RAOQ): Quantization-aware Training for In-memory Computing Systems
Bonan Zhang, Chia-Yu Chen, Naveen Verma
What Improves the Generalization of Graph Transformers? A Theoretical Dive into the Self-attention and Positional Encoding
Hongkang Li, Meng Wang, Tengfei Ma et al.
How Do Nonlinear Transformers Learn and Generalize in In-Context Learning?
Hongkang Li, Meng Wang, Songtao Lu et al.
Catapults in SGD: spikes in the training loss and their impact on generalization through feature learning
Libin Zhu, Chaoyue Liu, Adityanarayanan Radhakrishnan et al.
ProtoGate: Prototype-based Neural Networks with Global-to-local Feature Selection for Tabular Biomedical Data
Xiangjian Jiang, Andrei Margeloiu, Nikola Simidjievski et al.
Controllable Prompt Tuning For Balancing Group Distributional Robustness
Hoang Phan, Andrew Wilson, Qi Lei
Position: Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized
Shomik Jain, Kathleen A. Creel, Ashia Wilson
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.
Deep Functional Factor Models: Forecasting High-Dimensional Functional Time Series via Bayesian Nonparametric Factorization
Yirui Liu, Xinghao Qiao, Yulong Pei et al.
A Neural-Preconditioned Poisson Solver for Mixed Dirichlet and Neumann Boundary Conditions
Kai Weixian Lan, Elias Gueidon, Ayano Kaneda et al.