Most Cited ICLR "gradient descent robustness" Papers
6,124 papers found • Page 11 of 31
Conference
ELICIT: LLM Augmentation Via External In-context Capability
Futing Wang, Jianhao (Elliott) Yan, Yue Zhang et al.
Dynamical Diffusion: Learning Temporal Dynamics with Diffusion Models
Xingzhuo Guo, Yu Zhang, Baixu Chen et al.
Mask in the Mirror: Implicit Sparsification
Tom Jacobs, Rebekka Burkholz
Student-Informed Teacher Training
Nico Messikommer, Jiaxu Xing, Elie Aljalbout et al.
Divergence-enhanced Knowledge-guided Context Optimization for Visual-Language Prompt Tuning
Yilun Li, Miaomiao Cheng, Xu Han et al.
Advantage Alignment Algorithms
Juan Duque, Milad Aghajohari, Timotheus Cooijmans et al.
TaskGalaxy: Scaling Multi-modal Instruction Fine-tuning with Tens of Thousands Vision Task Types
Jiankang Chen, Tianke Zhang, Changyi Liu et al.
Spreading Out-of-Distribution Detection on Graphs
Daeho Um, Jongin Lim, Sunoh Kim et al.
Bidirectional Decoding: Improving Action Chunking via Guided Test-Time Sampling
Yuejiang Liu, Jubayer Hamid, Annie Xie et al.
Revisiting a Design Choice in Gradient Temporal Difference Learning
Xiaochi Qian, Shangtong Zhang
Autocorrelation Matters: Understanding the Role of Initialization Schemes for State Space Models
Fusheng Liu, Qianxiao Li
IMDPrompter: Adapting SAM to Image Manipulation Detection by Cross-View Automated Prompt Learning
Quan Zhang, Yuxin Qi, Xi Tang et al.
MindSimulator: Exploring Brain Concept Localization via Synthetic fMRI
Qi Zhang, Qi Zhang, Zixuan Gong et al.
The Curse of Diversity in Ensemble-Based Exploration
Zhixuan Lin, Pierluca D'Oro, Evgenii Nikishin et al.
Investigating the Pre-Training Dynamics of In-Context Learning: Task Recognition vs. Task Learning
Xiaolei Wang, Xinyu Tang, Junyi Li et al.
Intrinsic Dimension Correlation: uncovering nonlinear connections in multimodal representations
Lorenzo Basile, Santiago Acevedo, Luca Bortolussi et al.
DRL: Decomposed Representation Learning for Tabular Anomaly Detection
Hangting Ye, He Zhao, Wei Fan et al.
End-to-end Learning of Gaussian Mixture Priors for Diffusion Sampler
Denis Blessing, Xiaogang Jia, Gerhard Neumann
On the Identification of Temporal Causal Representation with Instantaneous Dependence
Zijian Li, Yifan Shen, Kaitao Zheng et al.
GNNs Getting ComFy: Community and Feature Similarity Guided Rewiring
Celia Rubio-Madrigal, Adarsh Jamadandi, Rebekka Burkholz
6D Object Pose Tracking in Internet Videos for Robotic Manipulation
Georgy Ponimatkin, Martin Cífka, Tomas Soucek et al.
Growth Inhibitors for Suppressing Inappropriate Image Concepts in Diffusion Models
Die Chen, Zhiwen Li, Mingyuan Fan et al.
Linear combinations of latents in generative models: subspaces and beyond
Erik Bodin, Alexandru Stere, Dragos Margineantu et al.
Bridging Compressed Image Latents and Multimodal Large Language Models
Chia-Hao Kao, Cheng Chien, Yu-Jen Tseng et al.
Expressivity of Neural Networks with Random Weights and Learned Biases
Ezekiel Williams, Alexandre Payeur, Avery Ryoo et al.
Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models
Jun Zhang, Jue Wang, Huan Li et al.
CLIPDrag: Combining Text-based and Drag-based Instructions for Image Editing
Ziqi Jiang, Zhen Wang, Long Chen
AdaFisher: Adaptive Second Order Optimization via Fisher Information
Damien GOMES, Yanlei Zhang, Eugene Belilovsky et al.
T-JEPA: Augmentation-Free Self-Supervised Learning for Tabular Data
Hugo Thimonier, José Lucas De Melo Costa, Fabrice Popineau et al.
Multiview Equivariance Improves 3D Correspondence Understanding with Minimal Feature Finetuning
Yang You, Yixin Li, Congyue Deng et al.
SimXRD-4M: Big Simulated X-ray Diffraction Data and Crystal Symmetry Classification Benchmark
Bin Cao, Yang Liu, Zinan Zheng et al.
GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning
Minghao Xu, Yunteng Geng, Yihang Zhang et al.
UV-Attack: Physical-World Adversarial Attacks on Person Detection via Dynamic-NeRF-based UV Mapping
Yanjie Li, Kaisheng Liang, Bin Xiao
Stable Hadamard Memory: Revitalizing Memory-Augmented Agents for Reinforcement Learning
Hung Le, Dung Nguyen, Kien Do et al.
Leveraging Submodule Linearity Enhances Task Arithmetic Performance in LLMs
Rui Dai, Sile Hu, Xu Shen et al.
Diffusion Bridge AutoEncoders for Unsupervised Representation Learning
Yeongmin Kim, Kwanghyeon Lee, Minsang Park et al.
Gen-Z: Generative Zero-Shot Text Classification with Contextualized Label Descriptions
Sachin Kumar, Chan Young Park, Yulia Tsvetkov
Probabilistic Learning to Defer: Handling Missing Expert Annotations and Controlling Workload Distribution
Cuong Nguyen, Thanh-Toan Do, Gustavo Carneiro
Towards Understanding the Robustness of Diffusion-Based Purification: A Stochastic Perspective
Yiming Liu, Kezhao Liu, Yao Xiao et al.
Out-of-Variable Generalisation for Discriminative Models
Siyuan Guo, Jonas Wildberger, Bernhard Schoelkopf
Analyzing and Improving Optimal-Transport-based Adversarial Networks
Jaemoo Choi, Jaewoong Choi, Myungjoo Kang
Not All LLM-Generated Data Are Equal: Rethinking Data Weighting in Text Classification
Hsun-Yu Kuo, Yin-Hsiang Liao, Yu-Chieh Chao et al.
Enhancing Cognition and Explainability of Multimodal Foundation Models with Self-Synthesized Data
Yucheng Shi, Quanzheng Li, Jin Sun et al.
Enabling Realtime Reinforcement Learning at Scale with Staggered Asynchronous Inference
Matt Riemer, Gopeshh Raaj Subbaraj, Glen Berseth et al.
Active Task Disambiguation with LLMs
Katarzyna Kobalczyk, Nicolás Astorga, Tennison Liu et al.
Multi-View Representation is What You Need for Point-Cloud Pre-Training
Siming Yan, Chen Song, Youkang Kong et al.
Learning a Neural Solver for Parametric PDEs to Enhance Physics-Informed Methods
Lise Le Boudec, Emmanuel de Bézenac, Louis Serrano et al.
Bayesian Experimental Design Via Contrastive Diffusions
Jacopo Iollo, Christophe Heinkelé, Pierre Alliez et al.
Concept-ROT: Poisoning Concepts in Large Language Models with Model Editing
Keltin Grimes, Marco Christiani, David Shriver et al.
IDInit: A Universal and Stable Initialization Method for Neural Network Training
Yu Pan, Chaozheng Wang, Zekai Wu et al.
Optimizing Posterior Samples for Bayesian Optimization via Rootfinding
Taiwo Adebiyi, Bach Do, Ruda Zhang
On the Expressive Power of Sparse Geometric MPNNs
Yonatan Sverdlov, Nadav Dym
Multi-Task Dense Predictions via Unleashing the Power of Diffusion
Yuqi Yang, Peng-Tao Jiang, Qibin Hou et al.
PlaSma: Procedural Knowledge Models for Language-based Planning and Re-Planning
Faeze Brahman, Chandra Bhagavatula, Valentina Pyatkin et al.
Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control
Songyuan Zhang, Oswin So, Mitchell Black et al.
CAMEx: Curvature-aware Merging of Experts
Dung Viet Nguyen, Minh Nguyen, Luc Nguyen et al.
Tight Clusters Make Specialized Experts
Stefan Nielsen, Rachel Teo, Laziz Abdullaev et al.
Entropy-MCMC: Sampling from Flat Basins with Ease
Bolian Li, Ruqi Zhang
IGL-Bench: Establishing the Comprehensive Benchmark for Imbalanced Graph Learning
Jiawen Qin, Haonan Yuan, Qingyun Sun et al.
Generalization Bounds and Model Complexity for Kolmogorov–Arnold Networks
Xianyang Zhang, Huijuan Zhou
Gradient descent with generalized Newton’s method
Zhiqi Bu, Shiyun Xu
Alice Benchmarks: Connecting Real World Re-Identification with the Synthetic
Xiaoxiao Sun, Yue Yao, Shengjin Wang et al.
Weakly-Supervised Affordance Grounding Guided by Part-Level Semantic Priors
Peiran Xu, Yadong MU
STAR: Stability-Inducing Weight Perturbation for Continual Learning
Masih Eskandar, Tooba Imtiaz, Davin Hill et al.
Understanding the Generalization of In-Context Learning in Transformers: An Empirical Study
Xingxuan Zhang, Haoran Wang, Jiansheng Li et al.
ADMM for Nonconvex Optimization under Minimal Continuity Assumption
Ganzhao Yuan
LICORICE: Label-Efficient Concept-Based Interpretable Reinforcement Learning
Zhuorui Ye, Stephanie Milani, Geoff Gordon et al.
Accelerating 3D Molecule Generation via Jointly Geometric Optimal Transport
Haokai Hong, Wanyu LIN, KC Tan
Natural Language Inference Improves Compositionality in Vision-Language Models
Paola Cascante-Bonilla, Yu (Hope) Hou, Yang Cao et al.
GLoRa: A Benchmark to Evaluate the Ability to Learn Long-Range Dependencies in Graphs
Dongzhuoran Zhou, Evgeny Kharlamov, Egor Kostylev
Episodic Novelty Through Temporal Distance
Yuhua Jiang, Qihan Liu, Yiqin Yang et al.
Montessori-Instruct: Generate Influential Training Data Tailored for Student Learning
Xiaochuan Li, Zichun Yu, Chenyan Xiong
Zeroth-Order Fine-Tuning of LLMs with Transferable Static Sparsity
Wentao Guo, Jikai Long, Yimeng Zeng et al.
Learning Hierarchical Polynomials with Three-Layer Neural Networks
Zihao Wang, Eshaan Nichani, Jason Lee
BigDocs: An Open Dataset for Training Multimodal Models on Document and Code Tasks
Juan A. Rodriguez, Xiangru Jian, Siba Smarak Panigrahi et al.
Model-Free Offline Reinforcement Learning with Enhanced Robustness
Chi Zhang, Zain Ulabedeen Farhat, George Atia et al.
E(3)-equivariant models cannot learn chirality: Field-based molecular generation
Alexandru Dumitrescu, Dani Korpela, Markus Heinonen et al.
Towards Understanding Text Hallucination of Diffusion Models via Local Generation Bias
Rui Lu, Runzhe Wang, Kaifeng Lyu et al.
Conformal Language Model Reasoning with Coherent Factuality
Maxon Rubin-Toles, Maya Gambhir, Keshav Ramji et al.
Beyond FVD: An Enhanced Evaluation Metrics for Video Generation Distribution Quality
Ge Ya Luo, Gian M Favero, Zhi Hao Luo et al.
CityAnchor: City-scale 3D Visual Grounding with Multi-modality LLMs
Jinpeng Li, Haiping Wang, Jiabin chen et al.
Toward Generalizing Visual Brain Decoding to Unseen Subjects
Xiangtao Kong, Kexin Huang, Ping Li et al.
Lawma: The Power of Specialization for Legal Annotation
Ricardo Dominguez-Olmedo, Vedant Nanda, Rediet Abebe et al.
ScImage: How good are multimodal large language models at scientific text-to-image generation?
Leixin Zhang, Steffen Eger, Yinjie Cheng et al.
PFDiff: Training-Free Acceleration of Diffusion Models Combining Past and Future Scores
Guangyi Wang, Yuren Cai, lijiang Li et al.
Q-Adapter: Customizing Pre-trained LLMs to New Preferences with Forgetting Mitigation
Yi-Chen Li, Fuxiang Zhang, Wenjie Qiu et al.
Wasserstein Distances, Neuronal Entanglement, and Sparsity
Shashata Sawmya, Linghao Kong, Ilia Markov et al.
Test-time Adaptation for Regression by Subspace Alignment
Kazuki Adachi, Shin'ya Yamaguchi, Atsutoshi Kumagai et al.
Advancing Prompt-Based Methods for Replay-Independent General Continual Learning
Zhiqi KANG, Liyuan Wang, Xingxing Zhang et al.
MetaDesigner: Advancing Artistic Typography through AI-Driven, User-Centric, and Multilingual WordArt Synthesis
Jun-Yan He, Zhi-Qi Cheng, Chenyang Li et al.
Privacy-Preserving Personalized Federated Prompt Learning for Multimodal Large Language Models
Linh Tran, Wei Sun, Stacy Patterson et al.
Learning Graph Invariance by Harnessing Spuriosity
Tianjun Yao, Yongqiang Chen, Kai Hu et al.
Optimal Non-Asymptotic Rates of Value Iteration for Average-Reward Markov Decision Processes
Jongmin Lee, Ernest Ryu
Cocoon: Robust Multi-Modal Perception with Uncertainty-Aware Sensor Fusion
Minkyoung Cho, Yulong Cao, Jiachen Sun et al.
Polynomial Composition Activations: Unleashing the Dynamics of Large Language Models
Zhijian Zhuo, Ya Wang, Yutao Zeng et al.
Think Thrice Before You Act: Progressive Thought Refinement in Large Language Models
Chengyu Du, Jinyi Han, Yizhou Ying et al.
Streamlining Prediction in Bayesian Deep Learning
Rui Li, Marcus Klasson, Arno Solin et al.
QMP: Q-switch Mixture of Policies for Multi-Task Behavior Sharing
Grace Zhang, Ayush Jain, Injune Hwang et al.
SeRA: Self-Reviewing and Alignment of LLMs using Implicit Reward Margins
Jongwoo Ko, Saket Dingliwal, Bhavana Ganesh et al.
Graph Assisted Offline-Online Deep Reinforcement Learning for Dynamic Workflow Scheduling
Yifan Yang, Gang Chen, Hui Ma et al.
Sensitivity-Constrained Fourier Neural Operators for Forward and Inverse Problems in Parametric Differential Equations
Abdolmehdi Behroozi, Chaopeng Shen, Daniel Kifer
Flavors of Margin: Implicit Bias of Steepest Descent in Homogeneous Neural Networks
Nikolaos Tsilivis, Gal Vardi, Julia Kempe
Progressive Compression with Universally Quantized Diffusion Models
Yibo Yang, Justus Will, Stephan Mandt
A Generic Framework for Conformal Fairness
Aditya Vadlamani, Anutam Srinivasan, Pranav Maneriker et al.
Ask, and it shall be given: On the Turing completeness of prompting
Ruizhong Qiu, Zhe Xu, Wenxuan Bao et al.
CSA: Data-efficient Mapping of Unimodal Features to Multimodal Features
Po-han Li, Sandeep Chinchali, ufuk topcu
Bootstrapped Model Predictive Control
Yuhang Wang, Hanwei Guo, Sizhe Wang et al.
Unlocking Point Processes through Point Set Diffusion
David Lüdke, Enric Rabasseda Raventós, Marcel Kollovieh et al.
Learning Spatial-Semantic Features for Robust Video Object Segmentation
Xin Li, Deshui Miao, Zhenyu He et al.
Denoising with a Joint-Embedding Predictive Architecture
Chen Dengsheng, Jie Hu, Xiaoming Wei et al.
Robust Feature Learning for Multi-Index Models in High Dimensions
Alireza Mousavi-Hosseini, Adel Javanmard, Murat A Erdogdu
SAM-CP: Marrying SAM with Composable Prompts for Versatile Segmentation
Pengfei Chen, Lingxi Xie, xinyue huo et al.
UTILITY: Utilizing Explainable Reinforcement Learning to Improve Reinforcement Learning
Shicheng Liu, Minghui Zhu
MOFFlow: Flow Matching for Structure Prediction of Metal-Organic Frameworks
Nayoung Kim, Seongsu Kim, Minsu Kim et al.
Accelerating Training with Neuron Interaction and Nowcasting Networks
Boris Knyazev, Abhinav Moudgil, Guillaume Lajoie et al.
Boltzmann-Aligned Inverse Folding Model as a Predictor of Mutational Effects on Protein-Protein Interactions
Xiaoran Jiao, Weian Mao, Wengong Jin et al.
Analytic DAG Constraints for Differentiable DAG Learning
Zhen Zhang, Ignavier Ng, Dong Gong et al.
Pushing the Limits of All-Atom Geometric Graph Neural Networks: Pre-Training, Scaling, and Zero-Shot Transfer
Zihan Pengmei, Zhengyuan Shen, Zichen Wang et al.
BitStack: Any-Size Compression of Large Language Models in Variable Memory Environments
Xinghao Wang, Pengyu Wang, Bo Wang et al.
Deep Random Features for Scalable Interpolation of Spatiotemporal Data
Weibin Chen, Azhir Mahmood, Michel Tsamados et al.
Model-based Offline Reinforcement Learning with Lower Expectile Q-Learning
Kwanyoung Park, Youngwoon Lee
QA-Calibration of Language Model Confidence Scores
Putra Manggala, Atalanti A Mastakouri, Elke Kirschbaum et al.
HiGen: Hierarchical Graph Generative Networks
Mahdi Karami
Unveiling and Manipulating Prompt Influence in Large Language Models
Zijian Feng, Hanzhang Zhou, ZIXIAO ZHU et al.
An Intuitive Multi-Frequency Feature Representation for SO(3)-Equivariant Networks
Dongwon Son, Jaehyung Kim, Sanghyeon Son et al.
RA-TTA: Retrieval-Augmented Test-Time Adaptation for Vision-Language Models
Youngjun Lee, Doyoung Kim, Junhyeok Kang et al.
Conformal Generative Modeling with Improved Sample Efficiency through Sequential Greedy Filtering
Klaus-Rudolf Kladny, Bernhard Schölkopf, Michael Muehlebach
Constructing Confidence Intervals for Average Treatment Effects from Multiple Datasets
Yuxin Wang, Maresa Schröder, Dennis Frauen et al.
Understanding the Robustness of Multi-modal Contrastive Learning to Distribution Shift
Yihao Xue, Siddharth Joshi, Dang Nguyen et al.
Re-evaluating Open-ended Evaluation of Large Language Models
Si-Qi Liu, Ian Gemp, Luke Marris et al.
Exploring the Design Space of Visual Context Representation in Video MLLMs
Yifan Du, Yuqi Huo, Kun Zhou et al.
Many-Objective Multi-Solution Transport
Ziyue Li, Tian Li, Virginia Smith et al.
Black Sheep in the Herd: Playing with Spuriously Correlated Attributes for Vision-Language Recognition
Xinyu Tian, Shu Zou, Zhaoyuan Yang et al.
Structural Estimation of Partially Observed Linear Non-Gaussian Acyclic Model: A Practical Approach with Identifiability
Songyao Jin, Feng Xie, Guangyi Chen et al.
Incorporating Visual Correspondence into Diffusion Model for Virtual Try-On
Siqi Wan, Jingwen Chen, Yingwei Pan et al.
U-shaped and Inverted-U Scaling behind Emergent Abilities of Large Language Models
Tung-Yu Wu, Melody Lo
Unify ML4TSP: Drawing Methodological Principles for TSP and Beyond from Streamlined Design Space of Learning and Search
Yang Li, Jiale Ma, Wenzheng Pan et al.
Self-Updatable Large Language Models by Integrating Context into Model Parameters
Yu Wang, Xinshuang Liu, Xiusi Chen et al.
MaRS: A Fast Sampler for Mean Reverting Diffusion based on ODE and SDE Solvers
Ao Li, Wei Fang, Hongbo Zhao et al.
Context Clues: Evaluating Long Context Models for Clinical Prediction Tasks on EHR Data
Michael Wornow, Suhana Bedi, Miguel Angel Fuentes Hernandez et al.
Lightweight Predictive 3D Gaussian Splats
Junli Cao, Vidit Goel, Chaoyang Wang et al.
HALL-E: Hierarchical Neural Codec Language Model for Minute-Long Zero-Shot Text-to-Speech Synthesis
Yuto Nishimura, Takumi Hirose, Masanari Ohi et al.
SMI-Editor: Edit-based SMILES Language Model with Fragment-level Supervision
Kangjie Zheng, Siyue Liang, Junwei Yang et al.
Efficient Multi-agent Offline Coordination via Diffusion-based Trajectory Stitching
Lei Yuan, Yuqi Bian, Lihe Li et al.
Is Large-scale Pretraining the Secret to Good Domain Generalization?
Piotr Teterwak, Kuniaki Saito, Theodoros Tsiligkaridis et al.
VLMaterial: Procedural Material Generation with Large Vision-Language Models
Beichen Li, Rundi Wu, Armando Solar-Lezama et al.
HASARD: A Benchmark for Vision-Based Safe Reinforcement Learning in Embodied Agents
Tristan Tomilin, Meng Fang, Mykola Pechenizkiy
Manifold Induced Biases for Zero-shot and Few-shot Detection of Generated Images
Jonathan Brokman, Amit Giloni, Omer Hofman et al.
Towards Improving Exploration through Sibling Augmented GFlowNets
Kanika Madan, Alex Lamb, Emmanuel Bengio et al.
Wasserstein-Regularized Conformal Prediction under General Distribution Shift
Rui Xu, Chao Chen, Yue Sun et al.
NetFormer: An interpretable model for recovering dynamical connectivity in neuronal population dynamics
Ziyu Lu, Wuwei Zhang, Trung Le et al.
DenoiseVAE: Learning Molecule-Adaptive Noise Distributions for Denoising-based 3D Molecular Pre-training
Yurou Liu, Jiahao Chen, Rui Jiao et al.
Towards Homogeneous Lexical Tone Decoding from Heterogeneous Intracranial Recordings
Di Wu, Siyuan Li, Chen Feng et al.
Improving Large Language Model Planning with Action Sequence Similarity
Xinran Zhao, Hanie Sedghi, Bernd Bohnet et al.
A Simple Approach to Unifying Diffusion-based Conditional Generation
Xirui Li, Charles Herrmann, Kelvin Chan et al.
RaSA: Rank-Sharing Low-Rank Adaptation
Zhiwei He, Zhaopeng Tu, Xing Wang et al.
Exponential Topology-enabled Scalable Communication in Multi-agent Reinforcement Learning
Xinran Li, Xiaolu Wang, Chenjia Bai et al.
REValueD: Regularised Ensemble Value-Decomposition for Factorisable Markov Decision Processes
David Ireland, Giovanni Montana
SysBench: Can LLMs Follow System Message?
Yanzhao Qin, Tao Zhang, Tao Zhang et al.
Selective induction Heads: How Transformers Select Causal Structures in Context
Francesco D'Angelo, francesco croce, Nicolas Flammarion
Optimal Strong Regret and Violation in Constrained MDPs via Policy Optimization
Francesco Emanuele Stradi, Matteo Castiglioni, Alberto Marchesi et al.
Learning-Guided Rolling Horizon Optimization for Long-Horizon Flexible Job-Shop Scheduling
Sirui Li, Wenbin Ouyang, Yining Ma et al.
Metamizer: A Versatile Neural Optimizer for Fast and Accurate Physics Simulations
Nils Wandel, Stefan Schulz, Reinhard Klein
AutoCLIP: Auto-tuning Zero-Shot Classifiers for Vision-Language Models
Jan Metzen, Piyapat Saranrittichai, Chaithanya Kumar Mummadi
ECHOPulse: ECG Controlled Echocardio-gram Video Generation
Yiwei Li, Sekeun Kim, Zihao Wu et al.
Anti-Exposure Bias in Diffusion Models
Junyu Zhang, Daochang Liu, Eunbyung Park et al.
How to Probe: Simple Yet Effective Techniques for Improving Post-hoc Explanations
Siddhartha Gairola, Moritz Böhle, Francesco Locatello et al.
On Speeding Up Language Model Evaluation
Jin Zhou, Christian Belardi, Ruihan Wu et al.
High-Precision Dichotomous Image Segmentation via Probing Diffusion Capacity
Qian Yu, Peng-Tao Jiang, Hao Zhang et al.
Strategic Classification With Externalities
Safwan Hossain, Evi Micha, Yiling Chen et al.
Robust Barycenter Estimation using Semi-Unbalanced Neural Optimal Transport
Milena Gazdieva, Jaemoo Choi, Alexander Kolesov et al.
Uncertainty and Influence aware Reward Model Refinement for Reinforcement Learning from Human Feedback
Zexu Sun, Yiju Guo, Yankai Lin et al.
Hessian-Free Online Certified Unlearning
Xinbao Qiao, Meng Zhang, Ming Tang et al.
SEPARATE: A Simple Low-rank Projection for Gradient Compression in Modern Large-scale Model Training Process
Hanzhen Zhao, Xingyu Xie, Cong Fang et al.
Reconsidering Faithfulness in Regular, Self-Explainable and Domain Invariant GNNs
Steve Azzolin, Antonio Longa, Stefano Teso et al.
TODO: Enhancing LLM Alignment with Ternary Preferences
Yuxiang Guo, Lu Yin, Bo Jiang et al.
Finding Shared Decodable Concepts and their Negations in the Brain
Cory Efird, Alex Murphy, Joel Zylberberg et al.
Faster Inference of Flow-Based Generative Models via Improved Data-Noise Coupling
Aram Davtyan, Leello Dadi, Volkan Cevher et al.
Fictitious Synthetic Data Can Improve LLM Factuality via Prerequisite Learning
Yujian Liu, Shiyu Chang, Tommi Jaakkola et al.
Temporal Flexibility in Spiking Neural Networks: Towards Generalization Across Time Steps and Deployment Friendliness
Kangrui Du, Yuhang Wu, Shikuang Deng et al.
How to Verify Any (Reasonable) Distribution Property: Computationally Sound Argument Systems for Distributions
Tal Herman, Guy Rothblum
Horizon Generalization in Reinforcement Learning
Vivek Myers, Catherine Ji, Benjamin Eysenbach
Hierarchical Uncertainty Estimation for Learning-based Registration in Neuroimaging
Xiaoling Hu, Karthik Gopinath, Peirong Liu et al.
Revisiting Source-Free Domain Adaptation: a New Perspective via Uncertainty Control
Gezheng Xu, Hui GUO, Li Yi et al.
Lift Your Molecules: Molecular Graph Generation in Latent Euclidean Space
Mohamed Amine Ketata, Nicholas Gao, Johanna Sommer et al.
MrSteve: Instruction-Following Agents in Minecraft with What-Where-When Memory
Junyeong Park, Junmo Cho, Sungjin Ahn
Towards Robust Multimodal Open-set Test-time Adaptation via Adaptive Entropy-aware Optimization
Hao Dong, Eleni Chatzi, Olga Fink
Risk-Controlling Model Selection via Guided Bayesian Optimization
Adam Fisch, Regina Barzilay, Bracha Laufer-Goldshtein et al.
DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction
Xinwei Zhang, Zhiqi Bu, Borja Balle et al.
Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces
Omer Nahum, Gali Noti, David Parkes et al.
OASIS Uncovers: High-Quality T2I Models, Same Old Stereotypes
Sepehr Dehdashtian, Gautam Sreekumar, Vishnu Boddeti
Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning
Md Rifat Arefin, Gopeshh Raaj Subbaraj, Nicolas Gontier et al.
Composable Interventions for Language Models
Arinbjörn Kolbeinsson, Kyle O'Brien, Tianjin Huang et al.
Latent Radiance Fields with 3D-aware 2D Representations
Chaoyi Zhou, Xi Liu, Feng Luo et al.
Severing Spurious Correlations with Data Pruning
Varun Mulchandani, Jung-Eun Kim
Interpreting Language Reward Models via Contrastive Explanations
Junqi Jiang, Tom Bewley, Saumitra Mishra et al.
When Selection Meets Intervention: Additional Complexities in Causal Discovery
Haoyue Dai, Ignavier Ng, Jianle Sun et al.
Pre-training LiDAR-based 3D Object Detectors through Colorization
Tai-Yu Pan, Chenyang Ma, Tianle Chen et al.
Calibrating Expressions of Certainty
Peiqi Wang, Barbara Lam, Yingcheng Liu et al.
Disentangling Representations through Multi-task Learning
Pantelis Vafidis, Aman Bhargava, Antonio Rangel