Most Cited ICLR "fourier embedding" Papers
6,124 papers found • Page 12 of 31
Conference
What should a neuron aim for? Designing local objective functions based on information theory
Andreas C. Schneider, Valentin Neuhaus, David Ehrlich et al.
A Common Pitfall of Margin-based Language Model Alignment: Gradient Entanglement
Hui Yuan, Yifan Zeng, Yue Wu et al.
ZETA: Leveraging $Z$-order Curves for Efficient Top-$k$ Attention
Qiuhao Zeng, Jierui Huang, Peng Lu et al.
Anti-Exposure Bias in Diffusion Models
Junyu Zhang, Daochang Liu, Eunbyung Park et al.
Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning
Fengyu Gao, Ruida Zhou, Tianhao Wang et al.
Unraveling the Enigma of Double Descent: An In-depth Analysis through the Lens of Learned Feature Space
Yufei Gu, Xiaoqing Zheng, Tomaso Aste
Reinforcement learning with combinatorial actions for coupled restless bandits
Lily Xu, Bryan Wilder, Elias Khalil et al.
When LLMs Play the Telephone Game: Cultural Attractors as Conceptual Tools to Evaluate LLMs in Multi-turn Settings
Jérémy Perez, Grgur Kovac, Corentin Léger et al.
High-Precision Dichotomous Image Segmentation via Probing Diffusion Capacity
Qian Yu, Peng-Tao Jiang, Hao Zhang et al.
Bayesian WeakS-to-Strong from Text Classification to Generation
Ziyun Cui, Ziyang Zhang, Guangzhi Sun et al.
Neural Interactive Proofs
Lewis Hammond, Sam Adam-Day
uniINF: Best-of-Both-Worlds Algorithm for Parameter-Free Heavy-Tailed MABs
Yu Chen, Jiatai Huang, Yan Dai et al.
EBMDock: Neural Probabilistic Protein-Protein Docking via a Differentiable Energy Model
Huaijin Wu, Wei Liu, Yatao Bian et al.
SpaCE: The Spatial Confounding Environment
Mauricio Tec, Ana Trisovic, Michelle Audirac et al.
Ensembles of Low-Rank Expert Adapters
Yinghao Li, Vianne Gao, Chao Zhang et al.
Conserve-Update-Revise to Cure Generalization and Robustness Trade-off in Adversarial Training
Shruthi Gowda, Bahram Zonooz, Elahe Arani
TODO: Enhancing LLM Alignment with Ternary Preferences
Yuxiang Guo, Lu Yin, Bo Jiang et al.
NUDGE: Lightweight Non-Parametric Fine-Tuning of Embeddings for Retrieval
Sepanta Zeighami, Zac Wellmer, Aditya Parameswaran
Faster Inference of Flow-Based Generative Models via Improved Data-Noise Coupling
Aram Davtyan, Leello Dadi, Volkan Cevher et al.
Studying the Interplay Between the Actor and Critic Representations in Reinforcement Learning
Samuel Garcin, Trevor McInroe, Pablo Samuel Castro et al.
Advancing Graph Generation through Beta Diffusion
Xinyang Liu, Yilin He, Bo Chen et al.
Optimization by Parallel Quasi-Quantum Annealing with Gradient-Based Sampling
Yuma Ichikawa, Yamato Arai
DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction
Xinwei Zhang, Zhiqi Bu, Borja Balle et al.
STAR: Stability-Inducing Weight Perturbation for Continual Learning
Masih Eskandar, Tooba Imtiaz, Davin Hill et al.
OASIS Uncovers: High-Quality T2I Models, Same Old Stereotypes
Sepehr Dehdashtian, Gautam Sreekumar, Vishnu Boddeti
Differentially Private Federated Learning with Time-Adaptive Privacy Spending
Shahrzad Kianidehkordi, Nupur Kulkarni, Adam Dziedzic et al.
On Generalization Across Environments In Multi-Objective Reinforcement Learning
Jayden Teoh, Pradeep Varakantham, Peter Vamplew
Topological Schrödinger Bridge Matching
Maosheng Yang
Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning
Md Rifat Arefin, Gopeshh Raaj Subbaraj, Nicolas Gontier et al.
Learning to Communicate Through Implicit Communication Channels
Han Wang, Binbin Chen, zhang et al.
Fast and unified path gradient estimators for normalizing flows
Lorenz Vaitl, Ludwig Winkler, Lorenz Richter et al.
Learning Hierarchical Polynomials with Three-Layer Neural Networks
Zihao Wang, Eshaan Nichani, Jason Lee
When Selection Meets Intervention: Additional Complexities in Causal Discovery
Haoyue Dai, Ignavier Ng, Jianle Sun et al.
BigDocs: An Open Dataset for Training Multimodal Models on Document and Code Tasks
Juan A. Rodriguez, Xiangru Jian, Siba Smarak Panigrahi et al.
From Probability to Counterfactuals: the Increasing Complexity of Satisfiability in Pearl's Causal Hierarchy
Julian Dörfler, Benito van der Zander, Markus Bläser et al.
Disentangling Representations through Multi-task Learning
Pantelis Vafidis, Aman Bhargava, Antonio Rangel
Rethinking Fair Representation Learning for Performance-Sensitive Tasks
Charles Jones, Fabio De Sousa Ribeiro, Mélanie Roschewitz et al.
Not-So-Optimal Transport Flows for 3D Point Cloud Generation
Ka-Hei Hui, Chao Liu, xiaohui zeng et al.
Beyond Random Masking: When Dropout meets Graph Convolutional Networks
Yuankai Luo, Xiao-Ming Wu, Hao Zhu
Language Agents Meet Causality -- Bridging LLMs and Causal World Models
John Gkountouras, Matthias Lindemann, Phillip Lippe et al.
Montessori-Instruct: Generate Influential Training Data Tailored for Student Learning
Xiaochuan Li, Zichun Yu, Chenyan Xiong
Learning to engineer protein flexibility
Petr Kouba, Joan Planas-Iglesias, Jiri Damborsky et al.
UniWav: Towards Unified Pre-training for Speech Representation Learning and Generation
Alexander Liu, Sang-gil Lee, Chao-Han Huck Yang et al.
The Hyperfitting Phenomenon: Sharpening and Stabilizing LLMs for Open-Ended Text Generation
Fredrik Carlsson, Fangyu Liu, Daniel Ward et al.
Causal Structure Recovery with Latent Variables under Milder Distributional and Graphical Assumptions
Xiuchuan Li, Kun Zhang, Tongliang Liu
Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson–Romberg Extrapolation
Marina Sheshukova, Denis Belomestny, Alain Oliviero Durmus et al.
Noisy Test-Time Adaptation in Vision-Language Models
Chentao Cao, Zhun Zhong, (Andrew) Zhanke Zhou et al.
Long-horizon Visual Instruction Generation with Logic and Attribute Self-reflection
Yucheng Suo, Fan Ma, Kaixin Shen et al.
Copyright-Protected Language Generation via Adaptive Model Fusion
Javier Abad, Konstantin Donhauser, Francesco Pinto et al.
Motion Control of High-Dimensional Musculoskeletal Systems with Hierarchical Model-Based Planning
Yunyue Wei, Shanning Zhuang, Vincent Zhuang et al.
CARTS: Advancing Neural Theorem Proving with Diversified Tactic Calibration and Bias-Resistant Tree Search
Xiao-Wen Yang, Zhi Zhou, Haiming Wang et al.
Time-Varying Propensity Score to Bridge the Gap between the Past and Present
Rasool Fakoor, Jonas Mueller, Zachary Lipton et al.
Extreme Risk Mitigation in Reinforcement Learning using Extreme Value Theory
Jan Drgona, Mahantesh Halappanavar, Frank Liu et al.
Behavioral Entropy-Guided Dataset Generation for Offline Reinforcement Learning
Wesley Suttle, Aamodh Suresh, Carlos Nieto-Granda
CryoFM: A Flow-based Foundation Model for Cryo-EM Densities
Yi Zhou, Yilai Li, Jing Yuan et al.
Where Am I and What Will I See: An Auto-Regressive Model for Spatial Localization and View Prediction
Junyi Chen, Di Huang, Weicai Ye et al.
Towards Establishing Guaranteed Error for Learned Database Operations
Sepanta Zeighami, Cyrus Shahabi
Unposed Sparse Views Room Layout Reconstruction in the Age of Pretrain Model
Yaxuan Huang, Xili Dai, Jianan Wang et al.
Infinite-Resolution Integral Noise Warping for Diffusion Models
Yitong Deng, Winnie Lin, Lingxiao Li et al.
Correlating instruction-tuning (in multimodal models) with vision-language processing (in the brain)
SUBBA REDDY OOTA, Akshett Rai Jindal, Ishani Mondal et al.
Harnessing Joint Rain-/Detail-aware Representations to Eliminate Intricate Rains
Wu Ran, Peirong Ma, Zhiquan He et al.
Pursuing Better Decision Boundaries for Long-Tailed Object Detection via Category Information Amount
Yanbiao Ma, Wei Dai, Jiayi Chen
Can Video LLMs Refuse to Answer? Alignment for Answerability in Video Large Language Models
Eunseop Yoon, Hee Suk Yoon, Mark Hasegawa-Johnson et al.
Human-Aligned Chess With a Bit of Search
Yiming Zhang, Athul Jacob, Vivian Lai et al.
A Unified Framework for Forward and Inverse Problems in Subsurface Imaging using Latent Space Translations
Naveen Gupta, Medha Sawhney, Arka Daw et al.
SiMHand: Mining Similar Hands for Large-Scale 3D Hand Pose Pre-training
Nie Lin, Takehiko Ohkawa, Yifei Huang et al.
Dataset Distillation via Knowledge Distillation: Towards Efficient Self-Supervised Pre-training of Deep Networks
Siddharth Joshi, Jiayi Ni, Baharan Mirzasoleiman
COPER: Correlation-based Permutations for Multi-View Clustering
Ran Eisenberg, Jonathan Svirsky, Ofir Lindenbaum
LLaMaFlex: Many-in-one LLMs via Generalized Pruning and Weight Sharing
Ruisi Cai, Saurav Muralidharan, Hongxu Yin et al.
AdvPaint: Protecting Images from Inpainting Manipulation via Adversarial Attention Disruption
Joonsung Jeon, Woo Jae Kim, Suhyeon Ha et al.
3D StreetUnveiler with Semantic-aware 2DGS - a simple baseline
Jingwei Xu, Yikai Wang, Yiqun Zhao et al.
On the Hölder Stability of Multiset and Graph Neural Networks
Yair Davidson, Nadav Dym
Exposure Bracketing Is All You Need For A High-Quality Image
Zhilu Zhang, Shuohao Zhang, Renlong Wu et al.
3D-MolT5: Leveraging Discrete Structural Information for Molecule-Text Modeling
Qizhi Pei, Rui Yan, Kaiyuan Gao et al.
MeToken: Uniform Micro-environment Token Boosts Post-Translational Modification Prediction
Cheng Tan, Zhenxiao Cao, Zhangyang Gao et al.
Multi-Label Test-Time Adaptation with Bound Entropy Minimization
Xiangyu Wu, Feng Yu, Yang Yang et al.
UniDrive: Towards Universal Driving Perception Across Camera Configurations
Ye Li, Wenzhao Zheng, Xiaonan Huang et al.
High-Dimensional Bayesian Optimisation with Gaussian Process Prior Variational Autoencoders
Siddharth Ramchandran, Manuel Haussmann, Harri Lähdesmäki
Bridging the Semantic Gap Between Text and Table: A Case Study on NL2SQL
Lin Long, Xijun Gu, Xinjie Sun et al.
Conditional Diffusion Models are Minimax-Optimal and Manifold-Adaptive for Conditional Distribution Estimation
Rong Tang, Lizhen Lin, Yun Yang
Unlocking the Potential of Model Calibration in Federated Learning
Yun-Wei Chu, Dong-Jun Han, Seyyedali Hosseinalipour et al.
STAFF: Speculative Coreset Selection for Task-Specific Fine-tuning
Xiaoyu Zhang, Juan Zhai, Shiqing Ma et al.
BiGR: Harnessing Binary Latent Codes for Image Generation and Improved Visual Representation Capabilities
Shaozhe Hao, Xuantong LIU, Xianbiao Qi et al.
Revisiting Convolution Architecture in the Realm of DNA Foundation Models
Yu Bo, Weian Mao, Daniel Shao et al.
ALAM: Averaged Low-Precision Activation for Memory-Efficient Training of Transformer Models
Sunghyeon Woo, SunWoo Lee, Dongsuk Jeon
On the Linear Speedup of Personalized Federated Reinforcement Learning with Shared Representations
GUOJUN XIONG, Shufan Wang, Daniel Jiang et al.
Microcanonical Langevin Ensembles: Advancing the Sampling of Bayesian Neural Networks
Emanuel Sommer, Jakob Robnik, Giorgi Nozadze et al.
f-FERM: A Scalable Framework for Robust Fair Empirical Risk Minimization
Sina Baharlouei, Shivam Patel, Meisam Razaviyayn
Training-Free Message Passing for Learning on Hypergraphs
Bohan Tang, Zexi Liu, Keyue Jiang et al.
Transformers Handle Endogeneity in In-Context Linear Regression
Haodong Liang, Krishna Balasubramanian, Lifeng Lai
SymmetricDiffusers: Learning Discrete Diffusion on Finite Symmetric Groups
Yongxing Zhang, Donglin Yang, Renjie Liao
Domain Guidance: A Simple Transfer Approach for a Pre-trained Diffusion Model
Jincheng Zhong, XiangCheng Zhang, Jianmin Wang et al.
Global Well-posedness and Convergence Analysis of Score-based Generative Models via Sharp Lipschitz Estimates
Connor Mooney, Zhongjian Wang, Jack Xin et al.
SBSC: Step-by-Step Coding for Improving Mathematical Olympiad Performance
Kunal Singh, Ankan Biswas, Sayandeep Bhowmick et al.
Zero-shot Model-based Reinforcement Learning using Large Language Models
Abdelhakim Benechehab, Youssef Attia El Hili, Ambroise Odonnat et al.
Learning to Plan Before Answering: Self-Teaching LLMs to Learn Abstract Plans for Problem Solving
Jin Zhang, Flood Sung, Zhilin Yang et al.
GridMix: Exploring Spatial Modulation for Neural Fields in PDE Modeling
Honghui Wang, Shiji Song, Gao Huang
PAC-FNO: Parallel-Structured All-Component Fourier Neural Operators for Recognizing Low-Quality Images
Jinsung Jeon, Hyundong Jin, Jonghyun Choi et al.
Learning Mask Invariant Mutual Information for Masked Image Modeling
Tao Huang, Yanxiang Ma, Shan You et al.
ParaSolver: A Hierarchical Parallel Integral Solver for Diffusion Models
Jianrong Lu, Zhiyu Zhu, Junhui Hou
Visually Consistent Hierarchical Image Classification
Seulki Park, Youren Zhang, Stella Yu et al.
ComPC: Completing a 3D Point Cloud with 2D Diffusion Priors
Tianxin Huang, Zhiwen Yan, Yuyang Zhao et al.
How Far Are We from True Unlearnability?
Kai Ye, Liangcai Su, Chenxiong Qian
Augmented Bayesian Policy Search
Mahdi Kallel, Debabrota Basu, Riad Akrour et al.
MotionDreamer: One-to-Many Motion Synthesis with Localized Generative Masked Transformer
Yilin Wang, chuan guo, Yuxuan Mu et al.
SPDIM: Source-Free Unsupervised Conditional and Label Shift Adaptation in EEG
Shanglin Li, Motoaki Kawanabe, Reinmar Kobler
How Does Vision-Language Adaptation Impact the Safety of Vision Language Models?
Seongyun Lee, Geewook Kim, Jiyeon Kim et al.
Efficient Training of Neural Stochastic Differential Equations by Matching Finite Dimensional Distributions
Jianxin Zhang, Josh Viktorov, Doosan Jung et al.
On the Performance Analysis of Momentum Method: A Frequency Domain Perspective
Xianliang Li, Jun Luo, Zhiwei Zheng et al.
Range, not Independence, Drives Modularity in Biologically Inspired Representations
Will Dorrell, Kyle Hsu, Luke Hollingsworth et al.
Discriminating image representations with principal distortions
Jenelle Feather, David Lipshutz, Sarah Harvey et al.
HyPoGen: Optimization-Biased Hypernetworks for Generalizable Policy Generation
Hanxiang Ren, Li Sun, Xulong Wang et al.
Matcha: Mitigating Graph Structure Shifts with Test-Time Adaptation
Wenxuan Bao, Zhichen Zeng, Zhining Liu et al.
Scaling Convex Neural Networks with Burer-Monteiro Factorization
Arda Sahiner, Tolga Ergen, Batu Ozturkler et al.
Flow Distillation Sampling: Regularizing 3D Gaussians with Pre-trained Matching Priors
Lin-Zhuo Chen, Kangjie Liu, Youtian Lin et al.
PABBO: Preferential Amortized Black-Box Optimization
Xinyu Zhang, Daolang Huang, Samuel Kaski et al.
Captured by Captions: On Memorization and its Mitigation in CLIP Models
Wenhao Wang, Adam Dziedzic, Grace Kim et al.
Flow-based Variational Mutual Information: Fast and Flexible Approximations
Caleb Dahlke, Jason Pacheco
A Riemannian Framework for Learning Reduced-order Lagrangian Dynamics
Katharina Friedl, Noémie Jaquier, Jens Lundell et al.
ANaGRAM: A Natural Gradient Relative to Adapted Model for efficient PINNs learning
Nilo Schwencke, Cyril Furtlehner
Self-Supervised Diffusion MRI Denoising via Iterative and Stable Refinement
Chenxu Wu, Qingpeng Kong, Zihang Jiang et al.
MAST: model-agnostic sparsified training
Yury Demidovich, Grigory Malinovsky, Egor Shulgin et al.
SplineGS: Learning Smooth Trajectories in Gaussian Splatting for Dynamic Scene Reconstruction
Jihwan Yoon, Sangbeom Han, Jaeseok Oh et al.
Functional Homotopy: Smoothing Discrete Optimization via Continuous Parameters for LLM Jailbreak Attacks
Zi Wang, Divyam Anshumaan, Ashish Hooda et al.
Multi-Task Corrupted Prediction for Learning Robust Audio-Visual Speech Representation
Sungnyun Kim, Sungwoo Cho, Sangmin Bae et al.
Epistemic Monte Carlo Tree Search
Yaniv Oren, Viliam Vadocz, Matthijs T. J. Spaan et al.
Connecting Federated ADMM to Bayes
Siddharth Swaroop, Mohammad Emtiyaz Khan, Finale Doshi-Velez
Subgraph Federated Learning for Local Generalization
Sungwon Kim, Yoonho Lee, Yunhak Oh et al.
Quality over Quantity in Attention Layers: When Adding More Heads Hurts
Noah Amsel, Gilad Yehudai, Joan Bruna
GenDataAgent: On-the-fly Dataset Augmentation with Synthetic Data
Zhiteng Li, Lele Chen, Jerone Andrews et al.
Simple, Good, Fast: Self-Supervised World Models Free of Baggage
Jan Robine, Marc Höftmann, Stefan Harmeling
Towards Cross Domain Generalization of Hamiltonian Representation via Meta Learning
Yeongwoo Song, Hawoong Jeong
Varying Shades of Wrong: Aligning LLMs with Wrong Answers Only
Jihan Yao, Wenxuan Ding, Shangbin Feng et al.
One-shot Active Learning Based on Lewis Weight Sampling for Multiple Deep Models
Sheng-Jun Huang, Yi Li, Yiming Sun et al.
Guided Score identity Distillation for Data-Free One-Step Text-to-Image Generation
Mingyuan Zhou, Zhendong Wang, Huangjie Zheng et al.
Transformer Learns Optimal Variable Selection in Group-Sparse Classification
Chenyang Zhang, Xuran Meng, Yuan Cao
Distilling Dataset into Neural Field
Donghyeok Shin, HeeSun Bae, Gyuwon Sim et al.
Affine Steerable Equivariant Layer for Canonicalization of Neural Networks
Yikang Li, Yeqing Qiu, Yuxuan Chen et al.
Discovering Influential Neuron Path in Vision Transformers
Yifan Wang, Yifei Liu, Yingdong Shi et al.
Synergy Between Sufficient Changes and Sparse Mixing Procedure for Disentangled Representation Learning
Zijian Li, Shunxing Fan, Yujia Zheng et al.
IFORMER: INTEGRATING CONVNET AND TRANSFORMER FOR MOBILE APPLICATION
Chuanyang Zheng
Path Choice Matters for Clear Attributions in Path Methods
Borui Zhang, Wenzhao Zheng, Jie Zhou et al.
Hot-pluggable Federated Learning: Bridging General and Personalized FL via Dynamic Selection
Lei Shen, Zhenheng Tang, Lijun Wu et al.
Solving Inverse Problems with Model Mismatch using Untrained Neural Networks within Model-based Architectures
Peimeng Guan, Naveed Iqbal, Mark Davenport et al.
Learning Equivariant Non-Local Electron Density Functionals
Nicholas Gao, Eike Eberhard, Stephan Günnemann
PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders
Tianyu Xie, David Harry Tyensoung Richman, Jiansi Gao et al.
ChemAgent: Self-updating Memories in Large Language Models Improves Chemical Reasoning
Xiangru Tang, Tianyu Hu, Muyang Ye et al.
DCT-CryptoNets: Scaling Private Inference in the Frequency Domain
Arjun Roy, Kaushik Roy
Small Models are LLM Knowledge Triggers for Medical Tabular Prediction
Jiahuan Yan, Jintai Chen, Chaowen Hu et al.
Bandits with Replenishable Knapsacks: the Best of both Worlds
Martino Bernasconi, Matteo Castiglioni, Andrea Celli et al.
Decentralized Sporadic Federated Learning: A Unified Algorithmic Framework with Convergence Guarantees
Shahryar Zehtabi, Dong-Jun Han, Rohit Parasnis et al.
Advantage-Guided Distillation for Preference Alignment in Small Language Models
Shiping Gao, Fanqi Wan, Jiajian Guo et al.
Multi-Draft Speculative Sampling: Canonical Decomposition and Theoretical Limits
Ashish Khisti, MohammadReza Ebrahimi, Hassan Dbouk et al.
Sum-Product-Set Networks: Deep Tractable Models for Tree-Structured Graphs
Milan Papez, Martin Rektoris, Vaclav Smidl et al.
Personalized Representation from Personalized Generation
Shobhita Sundaram, Julia Chae, Yonglong Tian et al.
Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery
Amin Soleimani Abyaneh, Mahrokh Boroujeni, Hsiu-Chin Lin et al.
Do Deep Neural Network Solutions Form a Star Domain?
Ankit Sonthalia, Alexander Rubinstein, Ehsan Abbasnejad et al.
Headless Language Models: Learning without Predicting with Contrastive Weight Tying
Nathan Godey, Éric Clergerie, Benoît Sagot
An Online Learning Theory of Trading-Volume Maximization
Tommaso Cesari, Roberto Colomboni
DRoP: Distributionally Robust Data Pruning
Artem Vysogorets, Kartik Ahuja, Julia Kempe
Learning Video-Conditioned Policy on Unlabelled Data with Joint Embedding Predictive Transformer
Hao Luo, Zongqing Lu
PaRa: Personalizing Text-to-Image Diffusion via Parameter Rank Reduction
Shangyu Chen, Zizheng Pan, Jianfei Cai et al.
Optimizing Backward Policies in GFlowNets via Trajectory Likelihood Maximization
Timofei Gritsaev, Nikita Morozov, Sergey Samsonov et al.
Tight Rates in Supervised Outlier Transfer Learning
Mohammadreza Mousavi Kalan, Samory Kpotufe
ImProver: Agent-Based Automated Proof Optimization
Riyaz Ahuja, Jeremy Avigad, Prasad Tetali et al.
Attribute-based Visual Reprogramming for Vision-Language Models
Chengyi Cai, Zesheng Ye, Lei Feng et al.
Kernel-based Optimally Weighted Conformal Time-Series Prediction
Jonghyeok Lee, Chen Xu, Yao Xie
Tackling Data Corruption in Offline Reinforcement Learning via Sequence Modeling
Jiawei Xu, Rui Yang, Shuang Qiu et al.
No Equations Needed: Learning System Dynamics Without Relying on Closed-Form ODEs
Krzysztof Kacprzyk, Mihaela van der Schaar
Fine-tuning can Help Detect Pretraining Data from Large Language Models
Hengxiang Zhang, Songxin Zhang, Bingyi Jing et al.
Unlocking Global Optimality in Bilevel Optimization: A Pilot Study
Quan Xiao, Tianyi Chen
Stem-OB: Generalizable Visual Imitation Learning with Stem-Like Convergent Observation through Diffusion Inversion
Kaizhe Hu, Zihang Rui, Yao He et al.
Self-supervised contrastive learning performs non-linear system identification
Rodrigo Gonzalez Laiz, Tobias Schmidt, Steffen Schneider
Forte : Finding Outliers with Representation Typicality Estimation
Debargha Ganguly, Warren Morningstar, Andrew Yu et al.
Erasing Concept Combination from Text-to-Image Diffusion Model
hongyi nie, Quanming Yao, Yang Liu et al.
Words in Motion: Extracting Interpretable Control Vectors for Motion Transformers
Omer Sahin Tas, Royden Wagner
eQMARL: Entangled Quantum Multi-Agent Reinforcement Learning for Distributed Cooperation over Quantum Channels
Alexander DeRieux, Walid Saad
On the Joint Interaction of Models, Data, and Features
Yiding Jiang, Christina Baek, J Kolter
Generating Physical Dynamics under Priors
Zihan Zhou, Xiaoxue Wang, Tianshu Yu
ACRF: Compressing Explicit Neural Radiance Fields via Attribute Compression
Guangchi Fang, Qingyong Hu, Longguang Wang et al.
On the Learn-to-Optimize Capabilities of Transformers in In-Context Sparse Recovery
Renpu Liu, Ruida Zhou, Cong Shen et al.
Boosting Multiple Views for pretrained-based Continual Learning
Quyen Tran, Tung Lam Tran, Khanh Doan et al.
Beyond Interpretability: The Gains of Feature Monosemanticity on Model Robustness
Qi Zhang, Yifei Wang, Jingyi Cui et al.
Quantitative Approximation for Neural Operators in Nonlinear Parabolic Equations
Takashi Furuya, Koichi Taniguchi, Satoshi Okuda
Controllable Blur Data Augmentation Using 3D-Aware Motion Estimation
Insoo Kim, Hana Lee, Hyong-Euk Lee et al.
Knowledge Distillation with Multi-granularity Mixture of Priors for Image Super-Resolution
Simiao Li, Yun Zhang, Wei Li et al.
Control-oriented Clustering of Visual Latent Representation
Han Qi, Haocheng Yin, Heng Yang
BAMDP Shaping: a Unified Framework for Intrinsic Motivation and Reward Shaping
Aly Lidayan, Michael Dennis, Stuart Russell
Rotated Runtime Smooth: Training-Free Activation Smoother for accurate INT4 inference
Ke Yi, Zengke Liu, jianwei zhang et al.
Meta-Dynamical State Space Models for Integrative Neural Data Analysis
Ayesha Vermani, Josue Nassar, Hyungju Jeon et al.
Mitigating Information Loss in Tree-Based Reinforcement Learning via Direct Optimization
Sascha Marton, Tim Grams, Florian Vogt et al.
NextBestPath: Efficient 3D Mapping of Unseen Environments
Shiyao Li, Antoine Guedon, Clémentin Boittiaux et al.
MeshMask: Physics-Based Simulations with Masked Graph Neural Networks
Paul Garnier, Vincent Lannelongue, Jonathan Viquerat et al.
A Black Swan Hypothesis: The Role of Human Irrationality in AI Safety
Hyunin Lee, Chanwoo Park, David Abel et al.
SCOPE: A Self-supervised Framework for Improving Faithfulness in Conditional Text Generation
Song Duong, Florian Le Bronnec, Alexandre Allauzen et al.
Certifying Counterfactual Bias in LLMs
Isha Chaudhary, Qian Hu, Manoj Kumar et al.
Understanding Matrix Function Normalizations in Covariance Pooling through the Lens of Riemannian Geometry
Ziheng Chen, Yue Song, Xiaojun Wu et al.
Reward Learning from Multiple Feedback Types
Yannick Metz, Andras Geiszl, Raphaël Baur et al.
Convergence and Implicit Bias of Gradient Descent on Continual Linear Classification
Hyunji Jung, Hanseul Cho, Chulhee Yun
Dataset Ownership Verification in Contrastive Pre-trained Models
Yuechen Xie, Jie Song, Mengqi Xue et al.