Most Cited ICLR "adaptive token generation" Papers
6,124 papers found • Page 13 of 31
Conference
Certifying Counterfactual Bias in LLMs
Isha Chaudhary, Qian Hu, Manoj Kumar et al.
Causal-StoNet: Causal Inference for High-Dimensional Complex Data
Yaxin Fang, Faming Liang
Convergence and Implicit Bias of Gradient Descent on Continual Linear Classification
Hyunji Jung, Hanseul Cho, Chulhee Yun
Stem-OB: Generalizable Visual Imitation Learning with Stem-Like Convergent Observation through Diffusion Inversion
Kaizhe Hu, Zihang Rui, Yao He et al.
Dataset Ownership Verification in Contrastive Pre-trained Models
Yuechen Xie, Jie Song, Mengqi Xue et al.
Second-Order Min-Max Optimization with Lazy Hessians
Lesi Chen, Chengchang Liu, Jingzhao Zhang
Time-Varying Propensity Score to Bridge the Gap between the Past and Present
Rasool Fakoor, Jonas Mueller, Zachary Lipton et al.
A Quadratic Synchronization Rule for Distributed Deep Learning
Xinran Gu, Kaifeng Lyu, Sanjeev Arora et al.
Kernel-based Optimally Weighted Conformal Time-Series Prediction
Jonghyeok Lee, Chen Xu, Yao Xie
Breaking the Reclustering Barrier in Centroid-based Deep Clustering
Lukas Miklautz, Timo Klein, Kevin Sidak et al.
Harnessing Joint Rain-/Detail-aware Representations to Eliminate Intricate Rains
Wu Ran, Peirong Ma, Zhiquan He et al.
Towards Establishing Guaranteed Error for Learned Database Operations
Sepanta Zeighami, Cyrus Shahabi
Extending Mercer's expansion to indefinite and asymmetric kernels
Sungwoo Jeong, Alex Townsend
eQMARL: Entangled Quantum Multi-Agent Reinforcement Learning for Distributed Cooperation over Quantum Channels
Alexander DeRieux, Walid Saad
Fine-tuning can Help Detect Pretraining Data from Large Language Models
Hengxiang Zhang, Songxin Zhang, Bingyi Jing et al.
Training-Free Dataset Pruning for Instance Segmentation
Yalun Dai, Lingao Xiao, Ivor Tsang et al.
Efficient and Accurate Explanation Estimation with Distribution Compression
Hubert Baniecki, Giuseppe Casalicchio, Bernd Bischl et al.
Beyond Interpretability: The Gains of Feature Monosemanticity on Model Robustness
Qi Zhang, Yifei Wang, Jingyi Cui et al.
Boosting Multiple Views for pretrained-based Continual Learning
Quyen Tran, Tung Lam Tran, Khanh Doan et al.
MamKO: Mamba-based Koopman operator for modeling and predictive control
Zhaoyang Li, Minghao Han, Xunyuan Yin
Nesterov acceleration in benignly non-convex landscapes
Kanan Gupta, Stephan Wojtowytsch
Polyrating: A Cost-Effective and Bias-Aware Rating System for LLM Evaluation
Jasper Dekoninck, Maximilian Baader, Martin Vechev
A Simple Framework for Open-Vocabulary Zero-Shot Segmentation
Thomas Stegmüller, Tim Lebailly, Nikola Đukić et al.
Feature-Based Online Bilateral Trade
Solenne Gaucher, Martino Bernasconi, Matteo Castiglioni et al.
Enhancing Graph Of Thought: Enhancing Prompts with LLM Rationales and Dynamic Temperature Control
Sunguk Shin, Youngjoon Kim
WardropNet: Traffic Flow Predictions via Equilibrium-Augmented Learning
Kai Jungel, Dario Paccagnan, Axel Parmentier et al.
Graph Neural Networks for Edge Signals: Orientation Equivariance and Invariance
Dominik Fuchsgruber, Tim Postuvan, Stephan Günnemann et al.
Learning Splitting Heuristics in Divide-and-Conquer SAT Solvers with Reinforcement Learning
Shumao Zhai, Ning Ge
Out-Of-Domain Unlabeled Data Improves Generalization
seyed amir hossein saberi, Amir Najafi, Alireza Heidari et al.
Infilling Score: A Pretraining Data Detection Algorithm for Large Language Models
Negin Raoof, Litu Rout, Giannis Daras et al.
Linear Bandits with Memory
Pierre Laforgue, Giulia Clerici, Nicolò Cesa-Bianchi
Spectrally Transformed Kernel Regression
Runtian Zhai, Rattana Pukdee, Roger Jin et al.
Fengbo: a Clifford Neural Operator pipeline for 3D PDEs in Computational Fluid Dynamics
Alberto Pepe, Mattia Montanari, Joan Lasenby
Precise Parameter Localization for Textual Generation in Diffusion Models
Łukasz Staniszewski, Bartosz Cywiński, Franziska Boenisch et al.
Neural Phylogeny: Fine-Tuning Relationship Detection among Neural Networks
Runpeng Yu, Xinchao Wang
CHAMP: Conformalized 3D Human Multi-Hypothesis Pose Estimators
Harry Zhang, Luca Carlone
Learning Color Equivariant Representations
Yulong Yang, Felix O'Mahony, Christine Allen-Blanchette
3DGS-Drag: Dragging Gaussians for Intuitive Point-Based 3D Editing
Jiahua Dong, Yu-Xiong Wang
Weakly Supervised Virus Capsid Detection with Image-Level Annotations in Electron Microscopy Images
Hannah Kniesel, Leon Sick, Tristan Payer et al.
ThunderKittens: Simple, Fast, and $\textit{Adorable}$ Kernels
Benjamin Spector, Simran Arora, Aaryan Singhal et al.
PETRA: Parallel End-to-end Training with Reversible Architectures
Stéphane Rivaud, Louis Fournier, Thomas Pumir et al.
MuHBoost: Multi-Label Boosting For Practical Longitudinal Human Behavior Modeling
Nguyen Thach, Patrick Habecker, Anika Eisenbraun et al.
Foundation Models Secretly Understand Neural Network Weights: Enhancing Hypernetwork Architectures with Foundation Models
Jeffrey Gu, Serena Yeung
Adaptive Pruning of Pretrained Transformer via Differential Inclusions
yizhuo Ding, Ke Fan, Yikai Wang et al.
Generalization Guarantees for Representation Learning via Data-Dependent Gaussian Mixture Priors
Milad Sefidgaran, Abdellatif Zaidi, Piotr Krasnowski
Improving Neural Optimal Transport via Displacement Interpolation
Jaemoo Choi, Yongxin Chen, Jaewoong Choi
Large (Vision) Language Models are Unsupervised In-Context Learners
Artyom Gadetsky, Andrei Atanov, Yulun Jiang et al.
Uncovering Latent Memories in Large Language Models
Sunny Duan, Mikail Khona, Abhiram Iyer et al.
A Theoretical Analysis of Self-Supervised Learning for Vision Transformers
Yu Huang, Zixin Wen, Yuejie Chi et al.
Bringing NeRFs to the Latent Space: Inverse Graphics Autoencoder
Antoine Schnepf, Karim Kassab, Jean-Yves Franceschi et al.
Make Haste Slowly: A Theory of Emergent Structured Mixed Selectivity in Feature Learning ReLU Networks
Devon Jarvis, Richard Klein, Benjamin Rosman et al.
LancBiO: Dynamic Lanczos-aided Bilevel Optimization via Krylov Subspace
Yan Yang, Bin Gao, Ya-xiang Yuan
Kronecker Mask and Interpretive Prompts are Language-Action Video Learners
Jingyi Yang, Zitong YU, Nixiuming et al.
Subtask-Aware Visual Reward Learning from Segmented Demonstrations
Changyeon Kim, Minho Heo, Doohyun Lee et al.
As Simple as Fine-tuning: LLM Alignment via Bidirectional Negative Feedback Loss
Xin Mao, Huimin Xu, Feng-Lin Li et al.
TAU-106K: A New Dataset for Comprehensive Understanding of Traffic Accident
Yixuan Zhou, Long Bai, Sijia Cai et al.
Representative Guidance: Diffusion Model Sampling with Coherence
Anh-Dung Dinh, Daochang Liu, Chang Xu
Adversarial Policy Optimization for Offline Preference-based Reinforcement Learning
Hyungkyu Kang, Min-hwan Oh
Distribution-Free Data Uncertainty for Neural Network Regression
Domokos M. Kelen, Ádám Jung, Péter Kersch et al.
Convergence of Distributed Adaptive Optimization with Local Updates
Ziheng Cheng, Margalit Glasgow
Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling
Jasmine Bayrooti, Carl Ek, Amanda Prorok
D-FINE: Redefine Regression Task of DETRs as Fine-grained Distribution Refinement
Yansong Peng, Hebei Li, Peixi Wu et al.
Learning High-Degree Parities: The Crucial Role of the Initialization
Emmanuel Abbe, Elisabetta Cornacchia, Jan Hązła et al.
GSBA$^K$: $top$-$K$ Geometric Score-based Black-box Attack
Md Farhamdur Reza, Richeng Jin, Tianfu Wu et al.
Neural Spacetimes for DAG Representation Learning
Haitz Sáez de Ocáriz Borde, Anastasis Kratsios, Marc T Law et al.
Training Free Exponential Context Extension via Cascading KV Cache
Jeff Willette, Heejun Lee, Youngwan Lee et al.
Improving Generalization and Robustness in SNNs Through Signed Rate Encoding and Sparse Encoding Attacks
Bhaskar Mukhoty, Hilal AlQuabeh, Bin Gu
Data Center Cooling System Optimization Using Offline Reinforcement Learning
Xianyuan Zhan, Xiangyu Zhu, Peng Cheng et al.
Representational Similarity via Interpretable Visual Concepts
Neehar Kondapaneni, Oisin Mac Aodha, Pietro Perona
Learning to Solve Differential Equation Constrained Optimization Problems
Vincenzo Di Vito Francesco, Mostafa Mohammadian, Kyri Baker et al.
SigDiffusions: Score-Based Diffusion Models for Time Series via Log-Signature Embeddings
Barbora Barancikova, Zhuoyue Huang, Cristopher Salvi
MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object Detection
Zhuoxiao Chen, Junjie Meng, Mahsa Baktashmotlagh et al.
Towards Out-of-Modal Generalization without Instance-level Modal Correspondence
Zhuo Huang, Gang Niu, Bo Han et al.
Topological Zigzag Spaghetti for Diffusion-based Generation and Prediction on Graphs
Yuzhou Chen, Yulia Gel
RTop-K: Ultra-Fast Row-Wise Top-K Selection for Neural Network Acceleration on GPUs
Xi Xie, Yuebo Luo, Hongwu Peng et al.
Re-Aligning Language to Visual Objects with an Agentic Workflow
Yuming Chen, Jiangyan Feng, Haodong Zhang et al.
Leveraging Driver Field-of-View for Multimodal Ego-Trajectory Prediction
M. Eren Akbiyik, Nedko Savov, Danda Pani Paudel et al.
Causal Information Prioritization for Efficient Reinforcement Learning
Hongye Cao, Fan Feng, Tianpei Yang et al.
SIM: Surface-based fMRI Analysis for Inter-Subject Multimodal Decoding from Movie-Watching Experiments
Simon Dahan, Gabriel Bénédict, Logan Williams et al.
Shadow Cones: A Generalized Framework for Partial Order Embeddings
Tao Yu, Toni Liu, Albert Tseng et al.
Approximation algorithms for combinatorial optimization with predictions
Antonios Antoniadis, Marek Elias, Adam Polak et al.
Reinforcement Learning from Imperfect Corrective Actions and Proxy Rewards
Zhaohui JIANG, Xuening Feng, Paul Weng et al.
Learning Hierarchical Polynomials of Multiple Nonlinear Features
Hengyu Fu, Zihao Wang, Eshaan Nichani et al.
Charting the Design Space of Neural Graph Representations for Subgraph Matching
Vaibhav Raj, Indradyumna Roy, Ashwin Ramachandran et al.
Transformer Encoder Satisfiability: Complexity and Impact on Formal Reasoning
Marco Sälzer, Eric Alsmann, Martin Lange
Decodable and Sample Invariant Continuous Object Encoder
Dehao Yuan, Furong Huang, Cornelia Fermuller et al.
Robust Conformal Prediction with a Single Binary Certificate
Soroush H. Zargarbashi, Aleksandar Bojchevski
Understanding the Stability-based Generalization of Personalized Federated Learning
Yingqi Liu, Qinglun Li, Jie Tan et al.
MELODI: Exploring Memory Compression for Long Contexts
Yinpeng Chen, DeLesley Hutchins, Aren Jansen et al.
Efficient Discovery of Pareto Front for Multi-Objective Reinforcement Learning
Ruohong Liu, Yuxin Pan, Linjie Xu et al.
Bridging Jensen Gap for Max-Min Group Fairness Optimization in Recommendation
Chen Xu, Yuxin Li, Wenjie Wang et al.
Probabilistic Geometric Principal Component Analysis with application to neural data
Han-Lin Hsieh, Maryam Shanechi
A Policy-Gradient Approach to Solving Imperfect-Information Games with Best-Iterate Convergence
Mingyang Liu, Gabriele Farina, Asuman Ozdaglar
A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery
Yingyu Lin, Yuxing Huang, Wenqin Liu et al.
Unsupervised Meta-Learning via In-Context Learning
Anna Vettoruzzo, Lorenzo Braccaioli, Joaquin Vanschoren et al.
Vision CNNs trained to estimate spatial latents learned similar ventral-stream-aligned representations
Yudi Xie, Weichen Huang, Esther Alter et al.
Stabilized Neural Prediction of Potential Outcomes in Continuous Time
Konstantin Hess, Stefan Feuerriegel
Causal Graph Transformer for Treatment Effect Estimation Under Unknown Interference
Anpeng Wu, Haiyi Qiu, Zhengming Chen et al.
From GNNs to Trees: Multi-Granular Interpretability for Graph Neural Networks
Jie Yang, Yuwen Wang, Kaixuan Chen et al.
No Need to Talk: Asynchronous Mixture of Language Models
Anastasiia Filippova, Angelos Katharopoulos, David Grangier et al.
Dimension Agnostic Neural Processes
Hyungi Lee, Chaeyun Jang, Dong Bok Lee et al.
Exploiting Distribution Constraints for Scalable and Efficient Image Retrieval
Mohammad Omama, Po-han Li, Sandeep Chinchali
FedLWS: Federated Learning with Adaptive Layer-wise Weight Shrinking
Changlong Shi, Jinmeng Li, He Zhao et al.
Less or More From Teacher: Exploiting Trilateral Geometry For Knowledge Distillation
Chengming Hu, Haolun Wu, Xuan Li et al.
Selective Label Enhancement Learning for Test-Time Adaptation
Yihao Hu, Congyu Qiao, Xin Geng et al.
Towards Calibrated Deep Clustering Network
Yuheng Jia, Jianhong Cheng, Hui LIU et al.
Weighted Point Set Embedding for Multimodal Contrastive Learning Toward Optimal Similarity Metric
Toshimitsu Uesaka, Taiji Suzuki, Yuhta Takida et al.
Language Models Are Implicitly Continuous
Samuele Marro, Davide Evangelista, X. Huang et al.
Online Reinforcement Learning in Non-Stationary Context-Driven Environments
Pouya Hamadanian, Arash Nasr-Esfahany, Malte Schwarzkopf et al.
Optimal Brain Apoptosis
Mingyuan Sun, Zheng Fang, Jiaxu Wang et al.
ReGen: Generative Robot Simulation via Inverse Design
Peter (Phat) Nguyen, Johnson (Tsun-Hsuan) Wang, Zhang-Wei Hong et al.
Scalable Decision-Making in Stochastic Environments through Learned Temporal Abstraction
Baiting Luo, Ava Pettet, Aron Laszka et al.
LoCA: Location-Aware Cosine Adaptation for Parameter-Efficient Fine-Tuning
Zhekai Du, Yinjie Min, Jingjing Li et al.
Reflexive Guidance: Improving OoDD in Vision-Language Models via Self-Guided Image-Adaptive Concept Generation
Jihyo Kim, Seulbi Lee, Sangheum Hwang
Learning the Complexity of Weakly Noisy Quantum States
Yusen Wu, Bujiao Wu, Yanqi Song et al.
$\phi$-Update: A Class of Policy Update Methods with Policy Convergence Guarantee
Wenye Li, Jiacai Liu, Ke Wei
BLEND: Behavior-guided Neural Population Dynamics Modeling via Privileged Knowledge Distillation
Zhengrui Guo, Fangxu Zhou, Wei Wu et al.
Joint Graph Rewiring and Feature Denoising via Spectral Resonance
Jonas Linkerhägner, Cheng Shi, Ivan Dokmanić
Multi-Accurate CATE is Robust to Unknown Covariate Shifts
Angela Zhou, Christoph Kern, Michael Kim
$F^3Set$: Towards Analyzing Fast, Frequent, and Fine-grained Events from Videos
Zhaoyu Liu, Kan Jiang, Murong Ma et al.
econSG: Efficient and Multi-view Consistent Open-Vocabulary 3D Semantic Gaussians
Can Zhang, Gim H Lee
Dist Loss: Enhancing Regression in Few-Shot Region through Distribution Distance Constraint
Guangkun Nie, Gongzheng Tang, Shenda Hong
Predictive Uncertainty Quantification for Bird's Eye View Segmentation: A Benchmark and Novel Loss Function
Linlin Yu, Bowen Yang, Tianhao Wang et al.
Physics-aligned field reconstruction with diffusion bridge
Zeyu Li, Hongkun Dou, Shen Fang et al.
PEARL: Towards Permutation-Resilient LLMs
Liang CHEN, Li Shen, Yang Deng et al.
Selective Unlearning via Representation Erasure Using Domain Adversarial Training
Nazanin Sepahvand, Eleni Triantafillou, Hugo Larochelle et al.
ECD: A Machine Learning Benchmark for Predicting Enhanced-Precision Electronic Charge Density in Crystalline Inorganic Materials
Pin Chen, Zexin Xu, Qing Mo et al.
Soft Mixture Denoising: Beyond the Expressive Bottleneck of Diffusion Models
Yangming Li, Boris van Breugel, Mihaela van der Schaar
Exact Computation of Any-Order Shapley Interactions for Graph Neural Networks
Maximilian Muschalik, Fabian Fumagalli, Paolo Frazzetto et al.
Expected Return Symmetries
Darius Muglich, Johannes Forkel, Elise van der Pol et al.
EFFICIENT JAILBREAK ATTACK SEQUENCES ON LARGE LANGUAGE MODELS VIA MULTI-ARMED BANDIT-BASED CONTEXT SWITCHING
Aditya Ramesh, Shivam Bhardwaj, Aditya Saibewar et al.
Demystifying Online Clustering of Bandits: Enhanced Exploration Under Stochastic and Smoothed Adversarial Contexts
Zhuohua Li, Maoli Liu, Xiangxiang Dai et al.
NL-Eye: Abductive NLI For Images
Mor Ventura, Michael Toker, Nitay Calderon et al.
FIG: Flow with Interpolant Guidance for Linear Inverse Problems
Yici Yan, Yichi Zhang, XIANGMING MENG et al.
Complexity Lower Bounds of Adaptive Gradient Algorithms for Non-convex Stochastic Optimization under Relaxed Smoothness
Michael Crawshaw, Mingrui Liu
Narrowing Information Bottleneck Theory for Multimodal Image-Text Representations Interpretability
Zhiyu Zhu, Zhibo Jin, Jiayu Zhang et al.
GNeRP: Gaussian-guided Neural Reconstruction of Reflective Objects with Noisy Polarization Priors
LI Yang, RUIZHENG WU, Jiyong Li et al.
The Labyrinth of Links: Navigating the Associative Maze of Multi-modal LLMs
HONG LI, Nanxi Li, Yuanjie Chen et al.
Let the Code LLM Edit Itself When You Edit the Code
Zhenyu He, Jun Zhang, Shengjie Luo et al.
PaCA: Partial Connection Adaptation for Efficient Fine-Tuning
Sunghyeon Woo, Sol Namkung, SunWoo Lee et al.
BEEM: Boosting Performance of Early Exit DNNs using Multi-Exit Classifiers as Experts
Divya Jyoti Bajpai, Manjesh Kumar Hanawal
BANGS: Game-theoretic Node Selection for Graph Self-Training
Fangxin Wang, Kay Liu, Sourav Medya et al.
Towards Self-Supervised Covariance Estimation in Deep Heteroscedastic Regression
Megh Shukla, Aziz Shameem, Mathieu Salzmann et al.
ClimaQA: An Automated Evaluation Framework for Climate Question Answering Models
Veeramakali Vignesh Manivannan, Yasaman Jafari, Srikar Eranky et al.
HG-Adapter: Improving Pre-Trained Heterogeneous Graph Neural Networks with Dual Adapters
YUJIE MO, Runpeng Yu, Xiaofeng Zhu et al.
Agent Skill Acquisition for Large Language Models via CycleQD
So Kuroki, Taishi Nakamura, Takuya Akiba et al.
Computationally Efficient RL under Linear Bellman Completeness for Deterministic Dynamics
Runzhe Wu, Ayush Sekhari, Akshay Krishnamurthy et al.
Rethinking Classifier Re-Training in Long-Tailed Recognition: Label Over-Smooth Can Balance
Siyu Sun, Han Lu, Jiangtong Li et al.
$InterLCM$: Low-Quality Images as Intermediate States of Latent Consistency Models for Effective Blind Face Restoration
Senmao Li, Kai Wang, Joost van de Weijer et al.
Enhancing Learning with Label Differential Privacy by Vector Approximation
Puning Zhao, Jiafei Wu, Zhe Liu et al.
Uni$^2$Det: Unified and Universal Framework for Prompt-Guided Multi-dataset 3D Detection
Yubin Wang, Zhikang Zou, Xiaoqing Ye et al.
SWAP: Sparse Entropic Wasserstein Regression for Robust Network Pruning
Lei You, Hei Victor Cheng
PEAR: Primitive Enabled Adaptive Relabeling for Boosting Hierarchical Reinforcement Learning
Utsav Singh, Vinay Purushothaman Namboodiri
Improved Sampling Of Diffusion Models In Fluid Dynamics With Tweedie's Formula
Youssef Shehata, Benjamin Holzschuh, Nils Thuerey
Enhancing Robust Fairness via Confusional Spectral Regularization
Gaojie Jin, Sihao Wu, Jiaxu Liu et al.
Drama: Mamba-Enabled Model-Based Reinforcement Learning Is Sample and Parameter Efficient
Wenlong Wang, Ivana Dusparic, Yucheng Shi et al.
AugKD: Ingenious Augmentations Empower Knowledge Distillation for Image Super-Resolution
Yun Zhang, Wei Li, Simiao Li et al.
Machine Unlearning via Simulated Oracle Matching
Kristian G Georgiev, Roy Rinberg, Sam Park et al.
Indirect Gradient Matching for Adversarial Robust Distillation
Hongsin Lee, Seungju Cho, Changick Kim
HShare: Fast LLM Decoding by Hierarchical Key-Value Sharing
Huaijin Wu, Lianqiang Li, Hantao Huang et al.
Calibrating LLMs with Information-Theoretic Evidential Deep Learning
Yawei Li, David Rügamer, Bernd Bischl et al.
Efficient Action-Constrained Reinforcement Learning via Acceptance-Rejection Method and Augmented MDPs
Wei Hung, Shao-Hua Sun, Ping-Chun Hsieh
Steering Protein Family Design through Profile Bayesian Flow
Jingjing Gong, Yu Pei, Siyu Long et al.
Mufu: Multilingual Fused Learning for Low-Resource Translation with LLM
Zheng Wei Lim, Nitish Gupta, Honglin Yu et al.
From Models to Microtheories: Distilling a Model's Topical Knowledge for Grounded Question-Answering
Nathaniel Weir, Bhavana Dalvi Mishra, Orion Weller et al.
ALBAR: Adversarial Learning approach to mitigate Biases in Action Recognition
Joseph Fioresi, Ishan Rajendrakumar Dave, Mubarak Shah
Homomorphism Expressivity of Spectral Invariant Graph Neural Networks
Jingchu Gai, Yiheng Du, Bohang Zhang et al.
Exact Certification of (Graph) Neural Networks Against Label Poisoning
Mahalakshmi Sabanayagam, Lukas Gosch, Stephan Günnemann et al.
Structural Inference with Dynamics Encoding and Partial Correlation Coefficients
Aoran Wang, Jun Pang
PRISM: Privacy-Preserving Improved Stochastic Masking for Federated Generative Models
Kyeongkook Seo, Dong-Jun Han, Jaejun Yoo
Lines of Thought in Large Language Models
Raphaël Sarfati, Toni Liu, Nicolas Boulle et al.
Perceptual Group Tokenizer: Building Perception with Iterative Grouping
Zhiwei Deng, Ting Chen, Yang Li
Deep Incomplete Multi-view Learning via Cyclic Permutation of VAEs
Xin Gao, Jian Pu
Exploring a Principled Framework for Deep Subspace Clustering
Xianghan Meng, Zhiyuan Huang, Wei He et al.
Aligning Visual Contrastive learning models via Preference Optimization
Amirabbas Afzali, Borna khodabandeh, Ali Rasekh et al.
Chunk-Distilled Language Modeling
Yanhong Li, Karen Livescu, Jiawei Zhou
Qinco2: Vector Compression and Search with Improved Implicit Neural Codebooks
Théophane Vallaeys, Matthew J Muckley, Jakob Verbeek et al.
Regulatory DNA Sequence Design with Reinforcement Learning
Zhao Yang, Bing Su, Chuan Cao et al.
Diffusion Transformers for Tabular Data Time Series Generation
Fabrizio Garuti, Enver Sangineto, Simone Luetto et al.
Global Convergence in Neural ODEs: Impact of Activation Functions
Tianxiang Gao, Siyuan Sun, Hailiang Liu et al.
Random Is All You Need: Random Noise Injection on Feature Statistics for Generalizable Deep Image Denoising
Zhengwei Yin, Hongjun Wang, Guixu Lin et al.
DICE: Data Influence Cascade in Decentralized Learning
Tongtian Zhu, Wenhao Li, Can Wang et al.
ChroKnowledge: Unveiling Chronological Knowledge of Language Models in Multiple Domains
Yein Park, Chanwoong Yoon, Jungwoo Park et al.
From Promise to Practice: Realizing High-performance Decentralized Training
Zesen Wang, Jiaojiao Zhang, Xuyang Wu et al.
Large Language Models can Become Strong Self-Detoxifiers
Ching-Yun Ko, Pin-Yu Chen, Payel Das et al.
Generalization Bounds for Canonicalization: A Comparative Study with Group Averaging
Behrooz Tahmasebi, Stefanie Jegelka
No Free Lunch: Fundamental Limits of Learning Non-Hallucinating Generative Models
Changlong Wu, Ananth Grama, Wojciech Szpankowski
Higher-Order Graphon Neural Networks: Approximation and Cut Distance
Daniel Herbst, Stefanie Jegelka
Metalic: Meta-Learning In-Context with Protein Language Models
Jacob Beck, Shikha Surana, Manus McAuliffe et al.
Regretful Decisions under Label Noise
Sujay Nagaraj, Yang Liu, Flavio Calmon et al.
An Effective Theory of Bias Amplification
Arjun Subramonian, Samuel Bell, Levent Sagun et al.
SC-OmniGS: Self-Calibrating Omnidirectional Gaussian Splatting
Huajian Huang, Yingshu Chen, Longwei Li et al.
Designing Mechanical Meta-Materials by Learning Equivariant Flows
Mehran Mirramezani, Anne Meeussen, Katia Bertoldi et al.
Revisiting Mode Connectivity in Neural Networks with Bezier Surface
Jie Ren, Pin-Yu Chen, Ren Wang
Progressive Fourier Neural Representation for Sequential Video Compilation
Haeyong Kang, Jaehong Yoon, DaHyun Kim et al.
FOSP: Fine-tuning Offline Safe Policy through World Models
Chenyang Cao, Yucheng Xin, Silang Wu et al.
Test-Time Ensemble via Linear Mode Connectivity: A Path to Better Adaptation
Byungjai Kim, Chanho Ahn, Wissam Baddar et al.
ClawMachine: Learning to Fetch Visual Tokens for Referential Comprehension
Tianren Ma, Lingxi Xie, Yunjie Tian et al.
Mechanism and Emergence of Stacked Attention Heads in Multi-Layer Transformers
Tiberiu Mușat
Moner: Motion Correction in Undersampled Radial MRI with Unsupervised Neural Representation
Qing Wu, Chenhe Du, Xuanyu Tian et al.