Most Cited ICML "primitive number scheduling" Papers
5,975 papers found • Page 7 of 30
Conference
Prediction-powered Generalization of Causal Inferences
Ilker Demirel, Ahmed Alaa, Anthony Philippakis et al.
PILAF: Optimal Human Preference Sampling for Reward Modeling
Yunzhen Feng, Ariel Kwiatkowski, Kunhao Zheng et al.
LOCATE 3D: Real-World Object Localization via Self-Supervised Learning in 3D
Paul McVay, Sergio Arnaud, Ada Martin et al.
MapEval: A Map-Based Evaluation of Geo-Spatial Reasoning in Foundation Models
Mahir Labib Dihan, Tanvir Hassan, Md Tanvir Parvez et al.
ContPhy: Continuum Physical Concept Learning and Reasoning from Videos
Zhicheng Zheng, Xin Yan, Zhenfang Chen et al.
Position: Editing Large Language Models Poses Serious Safety Risks
Paul Youssef, Zhixue Zhao, Daniel Braun et al.
ExPLoRA: Parameter-Efficient Extended Pre-Training to Adapt Vision Transformers under Domain Shifts
Samar Khanna, Medhanie Irgau, David Lobell et al.
Autoformalizing Euclidean Geometry
Logan Murphy, Kaiyu Yang, Jialiang Sun et al.
How to Synthesize Text Data without Model Collapse?
Xuekai Zhu, Daixuan Cheng, Hengli Li et al.
RealRAG: Retrieval-augmented Realistic Image Generation via Self-reflective Contrastive Learning
Yuanhuiyi Lyu, Xu Zheng, Lutao Jiang et al.
How Compositional Generalization and Creativity Improve as Diffusion Models are Trained
Alessandro Favero, Antonio Sclocchi, Francesco Cagnetta et al.
A Hitchhiker's Guide to Scaling Law Estimation
Leshem Choshen, Yang Zhang, Jacob Andreas
Positional Knowledge is All You Need: Position-induced Transformer (PiT) for Operator Learning
Junfeng CHEN, Kailiang Wu
Position: Benchmarking is Limited in Reinforcement Learning Research
Scott Jordan, Adam White, Bruno da Silva et al.
Test-Time Degradation Adaptation for Open-Set Image Restoration
Yuanbiao Gou, Haiyu Zhao, Boyun Li et al.
Federated Optimization with Doubly Regularized Drift Correction
Xiaowen Jiang, Anton Rodomanov, Sebastian Stich
RLVF: Learning from Verbal Feedback without Overgeneralization
Moritz Stephan, Alexander Khazatsky, Eric Mitchell et al.
One Diffusion Step to Real-World Super-Resolution via Flow Trajectory Distillation
Jianze Li, Jiezhang Cao, Yong Guo et al.
The Double-Ellipsoid Geometry of CLIP
Meir Yossef Levi, Guy Gilboa
DCTdiff: Intriguing Properties of Image Generative Modeling in the DCT Space
Mang Ning, Mingxiao Li, Jianlin Su et al.
Rethinking Decision Transformer via Hierarchical Reinforcement Learning
Yi Ma, Jianye Hao, Hebin Liang et al.
Joint MoE Scaling Laws: Mixture of Experts Can Be Memory Efficient
Jan Ludziejewski, Maciej Pióro, Jakub Krajewski et al.
SPP: Sparsity-Preserved Parameter-Efficient Fine-Tuning for Large Language Models
Xudong LU, Aojun Zhou, Yuhui Xu et al.
A Manifold Perspective on the Statistical Generalization of Graph Neural Networks
Zhiyang Wang, Juan Cervino, Alejandro Ribeiro
BRIDGE: Bootstrapping Text to Control Time-Series Generation via Multi-Agent Iterative Optimization and Diffusion Modeling
Hao Li, Yu-Hao Huang, Chang Xu et al.
Domain Generalisation via Imprecise Learning
Anurag Singh, Siu Lun Chau, Shahine Bouabid 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.
DecisionNCE: Embodied Multimodal Representations via Implicit Preference Learning
Jianxiong Li, Jinliang Zheng, Yinan Zheng et al.
Understanding the Emergence of Multimodal Representation Alignment
Megan Tjandrasuwita, Chanakya Ekbote, Liu Ziyin et al.
Multi-Sender Persuasion: A Computational Perspective
Safwan Hossain, Tonghan Wang, Tao Lin et al.
Attention Meets Post-hoc Interpretability: A Mathematical Perspective
Gianluigi Lopardo, Frederic Precioso, Damien Garreau
CROW: Eliminating Backdoors from Large Language Models via Internal Consistency Regularization
Nay Myat Min, Long H. Pham, Yige Li et al.
Reward-Guided Iterative Refinement in Diffusion Models at Test-Time with Applications to Protein and DNA Design
Masatoshi Uehara, su, Yulai Zhao et al.
Verifying message-passing neural networks via topology-based bounds tightening
Christopher Hojny, Shiqiang Zhang, Juan Campos et al.
Beyond Sensor Data: Foundation Models of Behavioral Data from Wearables Improve Health Predictions
Eray Erturk, Fahad Kamran, Salar Abbaspourazad et al.
GRAM: A Generative Foundation Reward Model for Reward Generalization
Chenglong Wang, Yang Gan, Yifu Huo et al.
Rejuvenating image-GPT as Strong Visual Representation Learners
Sucheng Ren, Zeyu Wang, Hongru Zhu et al.
How to Escape Sharp Minima with Random Perturbations
Kwangjun Ahn, Ali Jadbabaie, Suvrit Sra
On The Complexity of First-Order Methods in Stochastic Bilevel Optimization
Jeongyeol Kwon, Dohyun Kwon, Hanbaek Lyu
SimPro: A Simple Probabilistic Framework Towards Realistic Long-Tailed Semi-Supervised Learning
Chaoqun Du, Yizeng Han, Gao Huang
Size-invariance Matters: Rethinking Metrics and Losses for Imbalanced Multi-object Salient Object Detection
Feiran Li, Qianqian Xu, Shilong Bao et al.
The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling
Jiajun Ma, Shuchen Xue, Tianyang Hu et al.
HyperFields: Towards Zero-Shot Generation of NeRFs from Text
Sudarshan Babu, Richard Liu, Zi Yu Zhou et al.
BayOTIDE: Bayesian Online Multivariate Time Series Imputation with Functional Decomposition
Shikai Fang, Qingsong Wen, Yingtao Luo et al.
DPCore: Dynamic Prompt Coreset for Continual Test-Time Adaptation
Yunbei Zhang, Akshay Mehra, Shuaicheng Niu et al.
Hyperspherical Normalization for Scalable Deep Reinforcement Learning
Hojoon Lee, Youngdo Lee, Takuma Seno et al.
Interpreting and Improving Diffusion Models from an Optimization Perspective
Frank Permenter, Chenyang Yuan
SAM as the Guide: Mastering Pseudo-Label Refinement in Semi-Supervised Referring Expression Segmentation
Danni Yang, Jiayi Ji, Yiwei Ma et al.
BOtied: Multi-objective Bayesian optimization with tied multivariate ranks
Ji Won Park, Natasa Tagasovska, Michael Maser et al.
Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing
Han Jiang, Xiaoyuan Yi, Zhihua Wei et al.
Trainable Transformer in Transformer
Abhishek Panigrahi, Sadhika Malladi, Mengzhou Xia et al.
Prompt-guided Precise Audio Editing with Diffusion Models
Manjie Xu, Chenxing Li, Duzhen Zhang et al.
Let Go of Your Labels with Unsupervised Transfer
Artyom Gadetsky, Yulun Jiang, Maria Brbic
Discovering Bias in Latent Space: An Unsupervised Debiasing Approach
Dyah Adila, Shuai Zhang, Boran Han et al.
AlphaDPO: Adaptive Reward Margin for Direct Preference Optimization
Junkang Wu, xue wang, Zhengyi Yang et al.
Enhancing Adversarial Robustness in SNNs with Sparse Gradients
Yujia Liu, Tong Bu, Ding Jianhao et al.
LlavaGuard: An Open VLM-based Framework for Safeguarding Vision Datasets and Models
Lukas Helff, Felix Friedrich, Manuel Brack et al.
DeepPolar: Inventing Nonlinear Large-Kernel Polar Codes via Deep Learning
Ashwin Hebbar, Sravan Kumar Ankireddy, Hyeji Kim et al.
MIB: A Mechanistic Interpretability Benchmark
Aaron Mueller, Atticus Geiger, Sarah Wiegreffe et al.
SelfCite: Self-Supervised Alignment for Context Attribution in Large Language Models
Yung-Sung Chuang, Benjamin Cohen-Wang, Shannon Shen et al.
Principled Preferential Bayesian Optimization
Wenjie Xu, Wenbin Wang, Yuning Jiang et al.
SECOND: Mitigating Perceptual Hallucination in Vision-Language Models via Selective and Contrastive Decoding
Woohyeon Park, Woojin Kim, Jaeik Kim et al.
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training
Chen Liu, Zhichao Huang, Mathieu Salzmann et al.
Arrows of Time for Large Language Models
Vassilis Papadopoulos, Jérémie Wenger, Clement Hongler
AdaptiveStep: Automatically Dividing Reasoning Step through Model Confidence
Yuliang Liu, Junjie Lu, Chaofeng Qu et al.
Integrating Multimodal Data for Joint Generative Modeling of Complex Dynamics
Manuel Brenner, Florian Hess, Georgia Koppe et al.
Improving Gradient-Guided Nested Sampling for Posterior Inference
Pablo Lemos, Nikolay Malkin, Will Handley et al.
What is the Long-Run Distribution of Stochastic Gradient Descent? A Large Deviations Analysis
Waïss Azizian, Franck Iutzeler, Jérôme Malick et al.
Policy Learning for Balancing Short-Term and Long-Term Rewards
Peng Wu, Ziyu Shen, Feng Xie et al.
SITCOM: Step-wise Triple-Consistent Diffusion Sampling For Inverse Problems
Ismail Alkhouri, Shijun Liang, Cheng-Han Huang et al.
Variational Rectified Flow Matching
Pengsheng Guo, Alex Schwing
MiraGe: Editable 2D Images using Gaussian Splatting
Joanna Waczyńska, Tomasz Szczepanik, Piotr Borycki et al.
Accelerating PDE Data Generation via Differential Operator Action in Solution Space
huanshuo dong, Hong Wang, Haoyang Liu et al.
Open-Vocabulary Calibration for Fine-tuned CLIP
Shuoyuan Wang, Jindong Wang, Guoqing Wang et al.
Contextual Bandits for Unbounded Context Distributions
Puning Zhao, Rongfei Fan, Shaowei Wang et al.
Robust Stable Spiking Neural Networks
Ding Jianhao, Zhiyu Pan, Yujia Liu et al.
Expand-and-Cluster: Parameter Recovery of Neural Networks
Flavio Martinelli, Berfin Simsek, Wulfram Gerstner et al.
Editable Concept Bottleneck Models
Lijie Hu, Chenyang Ren, Zhengyu Hu et al.
Deliberation in Latent Space via Differentiable Cache Augmentation
Luyang Liu, Jonas Pfeiffer, Jiaxing Wu et al.
QuEST: Stable Training of LLMs with 1-Bit Weights and Activations
Andrei Panferov, Jiale Chen, Rush Tabesh et al.
ProSec: Fortifying Code LLMs with Proactive Security Alignment
Xiangzhe Xu, Zian Su, Jinyao Guo et al.
Lexico: Extreme KV Cache Compression via Sparse Coding over Universal Dictionaries
Junhyuck Kim, Jongho Park, Jaewoong Cho et al.
ETTA: Elucidating the Design Space of Text-to-Audio Models
Sang-gil Lee, Zhifeng Kong, ARUSHI GOEL et al.
A Circuit Domain Generalization Framework for Efficient Logic Synthesis in Chip Design
Zhihai Wang, Lei Chen, Jie Wang et al.
Geometry Informed Tokenization of Molecules for Language Model Generation
Xiner Li, Limei Wang, Youzhi Luo et al.
Instruction-Following Pruning for Large Language Models
Bairu Hou, Qibin Chen, Jianyu Wang et al.
Provable Multi-Task Representation Learning by Two-Layer ReLU Neural Networks
Liam Collins, Hamed Hassani, Mahdi Soltanolkotabi et al.
Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference
JIAN XU, Delu Zeng, John Paisley
Knowledge Transfer from Vision Foundation Models for Efficient Training of Small Task-specific Models
Raviteja Vemulapalli, Hadi Pouransari, Fartash Faghri et al.
Locality-Sensitive Hashing-Based Efficient Point Transformer with Applications in High-Energy Physics
Siqi Miao, Zhiyuan Lu, Mia Liu et al.
Superposition Prompting: Improving and Accelerating Retrieval-Augmented Generation
Thomas Merth, Qichen Fu, Mohammad Rastegari et al.
Tuning-Free Stochastic Optimization
Ahmed Khaled, Chi Jin
Liger: Linearizing Large Language Models to Gated Recurrent Structures
Disen Lan, Weigao Sun, Jiaxi Hu et al.
Community-Invariant Graph Contrastive Learning
Shiyin Tan, Dongyuan Li, Renhe Jiang et al.
Adaptive Advantage-Guided Policy Regularization for Offline Reinforcement Learning
Tenglong Liu, Yang Li, Yixing Lan et al.
OSSCAR: One-Shot Structured Pruning in Vision and Language Models with Combinatorial Optimization
Xiang Meng, Shibal Ibrahim, Kayhan Behdin et al.
EvTexture: Event-driven Texture Enhancement for Video Super-Resolution
Dachun Kai, Jiayao Lu, Yueyi Zhang et al.
Listenable Maps for Audio Classifiers
Francesco Paissan, Mirco Ravanelli, Cem Subakan
Latent Action Learning Requires Supervision in the Presence of Distractors
Alexander Nikulin, Ilya Zisman, Denis Tarasov et al.
Improving LLM Video Understanding with 16 Frames Per Second
Yixuan Li, Changli Tang, Jimin Zhuang et al.
PDE-Controller: LLMs for Autoformalization and Reasoning of PDEs
Mauricio Soroco, Jialin Song, Mengzhou Xia et al.
An Image is Worth Multiple Words: Discovering Object Level Concepts using Multi-Concept Prompt Learning
Chen Jin, Ryutaro Tanno, Amrutha Saseendran et al.
Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks
Dongyoung Lim, Sotirios Sabanis
Cost-efficient Collaboration between On-device and Cloud Language Models
Avanika Narayan, Dan Biderman, Sabri Eyuboglu et al.
Taylor Videos for Action Recognition
Lei Wang, Xiuyuan Yuan, Tom Gedeon et al.
Zero-Shot Reinforcement Learning via Function Encoders
Tyler Ingebrand, Amy Zhang, Ufuk Topcu
CHAI: Clustered Head Attention for Efficient LLM Inference
Saurabh Agarwal, Bilge Acun, Basil Hosmer et al.
Simplifying DINO via Coding Rate Regularization
Ziyang Wu, Jingyuan Zhang, Druv Pai et al.
Sample-specific Masks for Visual Reprogramming-based Prompting
Chengyi Cai, Zesheng Ye, Lei Feng et al.
Coarse-to-Fine Highlighting: Reducing Knowledge Hallucination in Large Language Models
Qitan Lv, Jie Wang, Hanzhu Chen et al.
Can Classic GNNs Be Strong Baselines for Graph-level Tasks? Simple Architectures Meet Excellence
Yuankai Luo, Lei Shi, Xiao-Ming Wu
Beyond Matryoshka: Revisiting Sparse Coding for Adaptive Representation
Tiansheng Wen, Yifei Wang, Zequn Zeng et al.
Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs
Langzhang Liang, Sunwoo Kim, Kijung Shin et al.
SAPG: Split and Aggregate Policy Gradients
Jayesh Singla, Ananye Agarwal, Deepak Pathak
Direct Discriminative Optimization: Your Likelihood-Based Visual Generative Model is Secretly a GAN Discriminator
Kaiwen Zheng, Yongxin Chen, Huayu Chen et al.
Byzantine-Robust Federated Learning: Impact of Client Subsampling and Local Updates
Youssef Allouah, Sadegh Farhadkhani, Rachid Guerraoui et al.
OmniAudio: Generating Spatial Audio from 360-Degree Video
Huadai Liu, Tianyi Luo, Kaicheng Luo et al.
What is Dataset Distillation Learning?
William Yang, Ye Zhu, Zhiwei Deng et al.
Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning
Idan Achituve, Idit Diamant, Arnon Netzer et al.
Optimal Hessian/Jacobian-Free Nonconvex-PL Bilevel Optimization
Feihu Huang
Active Evaluation Acquisition for Efficient LLM Benchmarking
Yang Li, Jie Ma, Miguel Ballesteros et al.
Training a Generally Curious Agent
Fahim Tajwar, Yiding Jiang, Abitha Thankaraj et al.
Epsilon-VAE: Denoising as Visual Decoding
Long Zhao, Sanghyun Woo, Ziyu Wan et al.
Latent Thought Models with Variational Bayes Inference-Time Computation
Deqian Kong, Minglu Zhao, Dehong Xu et al.
Learning High-Order Relationships of Brain Regions
Weikang Qiu, Huangrui Chu, Selena Wang et al.
High-Fidelity Simultaneous Speech-To-Speech Translation
Tom Labiausse, Laurent Mazaré, Edouard Grave et al.
Inverse problems with experiment-guided AlphaFold
Sai Advaith Maddipatla, Nadav Bojan, Meital Bojan et al.
Unveiling Privacy, Memorization, and Input Curvature Links
Deepak Ravikumar, Efstathia Soufleri, Abolfazl Hashemi et al.
Retrieval-Augmented Score Distillation for Text-to-3D Generation
Junyoung Seo, Susung Hong, Wooseok Jang et al.
Restoring balance: principled under/oversampling of data for optimal classification
Emanuele Loffredo, Mauro Pastore, Simona Cocco et al.
The Relative Value of Prediction in Algorithmic Decision Making
Juan Perdomo
LLMs on the Line: Data Determines Loss-to-Loss Scaling Laws
Prasanna Mayilvahanan, Thaddäus Wiedemer, Sayak Mallick et al.
Recurrent Early Exits for Federated Learning with Heterogeneous Clients
Royson Lee, Javier Fernandez-Marques, Xu Hu et al.
UPOCR: Towards Unified Pixel-Level OCR Interface
Dezhi Peng, Zhenhua Yang, Jiaxin Zhang et al.
Realistic Unsupervised CLIP Fine-tuning with Universal Entropy Optimization
Jian Liang, Sheng, Zhengbo Wang et al.
X-Transfer Attacks: Towards Super Transferable Adversarial Attacks on CLIP
Hanxun Huang, Sarah Erfani, Yige Li et al.
Deeper or Wider: A Perspective from Optimal Generalization Error with Sobolev Loss
Yahong Yang, Juncai He
Offline Multi-Objective Optimization
Ke Xue, Rong-Xi Tan, Xiaobin Huang et al.
Proactive Agents for Multi-Turn Text-to-Image Generation Under Uncertainty
Meera Hahn, Wenjun Zeng, Nithish Kannen et al.
Random Masking Finds Winning Tickets for Parameter Efficient Fine-tuning
Jing Xu, Jingzhao Zhang
Recovering the Pre-Fine-Tuning Weights of Generative Models
Eliahu Horwitz, Jonathan Kahana, Yedid Hoshen
Policy Filtration for RLHF to Mitigate Noise in Reward Models
Chuheng Zhang, Wei Shen, Li Zhao et al.
Non-convex Stochastic Composite Optimization with Polyak Momentum
Yuan Gao, Anton Rodomanov, Sebastian Stich
A Neural-Guided Dynamic Symbolic Network for Exploring Mathematical Expressions from Data
Wenqiang Li, Weijun Li, Lina Yu et al.
How Contaminated Is Your Benchmark? Measuring Dataset Leakage in Large Language Models with Kernel Divergence
Hyeong Kyu Choi, Maxim Khanov, Hongxin Wei et al.
Distributional Diffusion Models with Scoring Rules
Valentin De Bortoli, Alexandre Galashov, J Swaroop Guntupalli et al.
One Example Shown, Many Concepts Known! Counterexample-Driven Conceptual Reasoning in Mathematical LLMs
Yinghui Li, Jiayi Kuang, Haojing Huang et al.
MusicFlow: Cascaded Flow Matching for Text Guided Music Generation
Prajwal K R, Bowen Shi, Matthew Le et al.
Recurrent Distance Filtering for Graph Representation Learning
Yuhui Ding, Antonio Orvieto, Bobby He et al.
Rethinking Generative Large Language Model Evaluation for Semantic Comprehension
Fangyun Wei, Xi Chen, Lin Luo
Large Language-Geometry Model: When LLM meets Equivariance
Zongzhao Li, Jiacheng Cen, Bing Su et al.
MindLLM: A Subject-Agnostic and Versatile Model for fMRI-to-text Decoding
Weikang Qiu, Zheng Huang, Haoyu Hu et al.
A Memory Efficient Randomized Subspace Optimization Method for Training Large Language Models
Yiming Chen, yuan zhang, Yin Liu et al.
Adaptive Proximal Gradient Methods Are Universal Without Approximation
Konstantinos Oikonomidis, Emanuel Laude, Puya Latafat et al.
Learning the RoPEs: Better 2D and 3D Position Encodings with STRING
Connor Schenck, Isaac Reid, Mithun Jacob et al.
Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling
Brooks(Ruijia) Niu, Dongxia Wu, Kai Kim et al.
Safe Delta: Consistently Preserving Safety when Fine-Tuning LLMs on Diverse Datasets
Ning LU, Shengcai Liu, Jiahao Wu et al.
Improving Neural Additive Models with Bayesian Principles
Kouroche Bouchiat, Alexander Immer, Hugo Yèche et al.
FADAS: Towards Federated Adaptive Asynchronous Optimization
Yujia Wang, Shiqiang Wang, Songtao Lu et al.
PIDformer: Transformer Meets Control Theory
Tam Nguyen, Cesar Uribe, Tan Nguyen et al.
Improving Token-Based World Models with Parallel Observation Prediction
Lior Cohen, Kaixin Wang, Bingyi Kang et al.
Harmony in Diversity: Merging Neural Networks with Canonical Correlation Analysis
Stefan Horoi, Albert Manuel Orozco Camacho, Eugene Belilovsky et al.
Black-Box Adversarial Attacks on LLM-Based Code Completion
Slobodan Jenko, Niels Mündler, Jingxuan He et al.
Topological Neural Networks go Persistent, Equivariant, and Continuous
Yogesh Verma, Amauri Souza, Vikas Garg
Taming Knowledge Conflicts in Language Models
Gaotang Li, Yuzhong Chen, Hanghang Tong
Unlocking the Capabilities of Large Vision-Language Models for Generalizable and Explainable Deepfake Detection
Peipeng Yu, Jianwei Fei, Hui Gao et al.
Otter: Generating Tests from Issues to Validate SWE Patches
Toufique Ahmed, Jatin Ganhotra, Rangeet Pan et al.
EquiAV: Leveraging Equivariance for Audio-Visual Contrastive Learning
Jongsuk Kim, Hyeongkeun Lee, Kyeongha Rho et al.
DUPLEX: Dual GAT for Complex Embedding of Directed Graphs
Zhaoru Ke, Hang Yu, Jianguo Li et al.
Conditioning Diffusions Using Malliavin Calculus
Jakiw Pidstrigach, Elizabeth Baker, Carles Domingo i Enrich et al.
Replicable Learning of Large-Margin Halfspaces
Alkis Kalavasis, Amin Karbasi, Kasper Green Larsen et al.
MoEQuant: Enhancing Quantization for Mixture-of-Experts Large Language Models via Expert-Balanced Sampling and Affinity Guidance
Zhixuan Chen, Xing Hu, Dawei Yang et al.
Strategy Coopetition Explains the Emergence and Transience of In-Context Learning
Aaditya Singh, Ted Moskovitz, Sara Dragutinović et al.
Metastable Dynamics of Chain-of-Thought Reasoning: Provable Benefits of Search, RL and Distillation
Juno Kim, Denny Wu, Jason Lee et al.
A Universal Class of Sharpness-Aware Minimization Algorithms
Behrooz Tahmasebi, Ashkan Soleymani, Dara Bahri et al.
REST: Efficient and Accelerated EEG Seizure Analysis through Residual State Updates
Arshia Afzal, Grigorios Chrysos, Volkan Cevher et al.
Learning Adversarial MDPs with Stochastic Hard Constraints
Francesco Emanuele Stradi, Matteo Castiglioni, Alberto Marchesi et al.
RODEO: Robust Outlier Detection via Exposing Adaptive Out-of-Distribution Samples
Hossein Mirzaei, Mohammad Jafari Varnousfaderani, Hamid Reza Dehbashi et al.
DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection
Zhi Zhou, Ming Yang, Jiang-Xin Shi et al.
Performative Prediction with Bandit Feedback: Learning through Reparameterization
Yatong Chen, Wei Tang, Chien-Ju Ho et al.
Emergent Equivariance in Deep Ensembles
Jan Gerken, Pan Kessel
Exploring and Mitigating Adversarial Manipulation of Voting-Based Leaderboards
Yangsibo Huang, Milad Nasr, Anastasios Angelopoulos et al.
Online Algorithms with Uncertainty-Quantified Predictions
Bo Sun, Jerry Huang, Nicolas Christianson et al.
Conformalized Adaptive Forecasting of Heterogeneous Trajectories
Yanfei Zhou, Lars Lindemann, Matteo Sesia
CAD-Editor: A Locate-then-Infill Framework with Automated Training Data Synthesis for Text-Based CAD Editing
Yu Yuan, Shizhao Sun, Qi Liu et al.
Mixture of Experts Made Intrinsically Interpretable
Xingyi Yang, Constantin Venhoff, Ashkan Khakzar et al.
Sparse is Enough in Fine-tuning Pre-trained Large Language Models
Weixi Song, Zuchao Li, Lefei Zhang et al.
Compositional Image Decomposition with Diffusion Models
Jocelin Su, Nan Liu, Yanbo Wang et al.
Using AI Uncertainty Quantification to Improve Human Decision-Making
Laura Marusich, Jonathan Bakdash, Yan Zhou et al.
The Energy Loss Phenomenon in RLHF: A New Perspective on Mitigating Reward Hacking
Yuchun Miao, Sen Zhang, Liang Ding et al.
TimeDART: A Diffusion Autoregressive Transformer for Self-Supervised Time Series Representation
Daoyu Wang, Mingyue Cheng, Zhiding Liu et al.
Scaling Inference-Efficient Language Models
Song Bian, Minghao Yan, Shivaram Venkataraman
Scaling Laws for Differentially Private Language Models
Ryan McKenna, Yangsibo Huang, Amer Sinha et al.
Characterizing Overfitting in Kernel Ridgeless Regression Through the Eigenspectrum
Tin Sum Cheng, Aurelien Lucchi, Anastasis Kratsios et al.
Why Do Animals Need Shaping? A Theory of Task Composition and Curriculum Learning
Jin Hwa Lee, Stefano Mannelli, Andrew Saxe
Improving Interpretation Faithfulness for Vision Transformers
Lijie Hu, Yixin Liu, Ninghao Liu et al.
NTPP: Generative Speech Language Modeling for Dual-Channel Spoken Dialogue via Next-Token-Pair Prediction
Qichao Wang, Ziqiao Meng, Wenqian Cui et al.
Towards Graph Foundation Models: Learning Generalities Across Graphs via Task-Trees
Zehong Wang, Zheyuan Zhang, Tianyi MA et al.
Diffuse Everything: Multimodal Diffusion Models on Arbitrary State Spaces
Kevin Rojas, Yuchen Zhu, Sichen Zhu et al.
Tripod: Three Complementary Inductive Biases for Disentangled Representation Learning
Kyle Hsu, Jubayer Ibn Hamid, Kaylee Burns et al.