Most Cited 2024 "gui agents" Papers

Efficient Multi-agent Reinforcement Learning by Planning

Qihan Liu, Jianing Ye, Xiaoteng Ma et al.

DSPy: Compiling Declarative Language Model Calls into State-of-the-Art Pipelines

Omar Khattab, Arnav Singhvi, Paridhi Maheshwari et al.

On the Stability of Iterative Retraining of Generative Models on their own Data

Quentin Bertrand, Joey Bose, Alexandre Duplessis et al.

Fine-Tuned Language Models Generate Stable Inorganic Materials as Text

Nate Gruver, Anuroop Sriram, Andrea Madotto et al.

Adapting to Distribution Shift by Visual Domain Prompt Generation

Zhixiang Chi, Li Gu, Tao Zhong et al.

ImplicitSLIM and How it Improves Embedding-based Collaborative Filtering

Ilya Shenbin, Sergey Nikolenko

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Navigating Complexity: Toward Lossless Graph Condensation via Expanding Window Matching

Yuchen Zhang, Tianle Zhang, Kai Wang et al.

Relaxing the Accurate Imputation Assumption in Doubly Robust Learning for Debiased Collaborative Filtering

Haoxuan Li, Chunyuan Zheng, Shuyi Wang et al.

Model-based Reinforcement Learning for Confounded POMDPs

Mao Hong, Zhengling Qi, Yanxun Xu

Position: A Call for Embodied AI

Giuseppe Paolo, Jonas Gonzalez-Billandon, Balázs Kégl

Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference

Wei-Lin Chiang, Lianmin Zheng, Ying Sheng et al.

LLM and Simulation as Bilevel Optimizers: A New Paradigm to Advance Physical Scientific Discovery

Pingchuan Ma, Johnson Tsun-Hsuan Wang, Minghao Guo et al.

InfoNet: Neural Estimation of Mutual Information without Test-Time Optimization

Zhengyang Hu, Song Kang, Qunsong Zeng et al.

Calibration Bottleneck: Over-compressed Representations are Less Calibratable

Deng-Bao Wang, Min-Ling Zhang

Discovering Environments with XRM

Mohammad Pezeshki, Diane Bouchacourt, Mark Ibrahim et al.

Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality

Tri Dao, Albert Gu

Combinatorial Approximations for Cluster Deletion: Simpler, Faster, and Better

Vicente Balmaseda, Ying Xu, Yixin Cao et al.

Distribution Alignment Optimization through Neural Collapse for Long-tailed Classification

Jintong Gao, He Zhao, Dandan Guo et al.

Fool Your (Vision and) Language Model with Embarrassingly Simple Permutations

Yongshuo Zong, Tingyang Yu, Ruchika Chavhan et al.

DRED: Zero-Shot Transfer in Reinforcement Learning via Data-Regularised Environment Design

Samuel Garcin, James Doran, Shangmin Guo et al.

Balanced Data, Imbalanced Spectra: Unveiling Class Disparities with Spectral Imbalance

Chiraag Kaushik, Ran Liu, Chi-Heng Lin et al.

Active Preference Learning for Large Language Models

William Muldrew, Peter Hayes, Mingtian Zhang et al.

Variational Partial Group Convolutions for Input-Aware Partial Equivariance of Rotations and Color-Shifts

Hyunsu Kim, Ye Gon Kim, Hongseok Yang et al.

Position: Why We Must Rethink Empirical Research in Machine Learning

Moritz Herrmann, F. Julian D. Lange, Katharina Eggensperger et al.

Q-value Regularized Transformer for Offline Reinforcement Learning

Shengchao Hu, Ziqing Fan, Chaoqin Huang et al.

Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints

Yunsheng Tian, Ane Zuniga, Xinwei Zhang et al.

Understanding Reasoning Ability of Language Models From the Perspective of Reasoning Paths Aggregation

Xinyi Wang, Alfonso Amayuelas, Kexun Zhang et al.

Peeking with PEAK: Sequential, Nonparametric Composite Hypothesis Tests for Means of Multiple Data Streams

Brian Cho, Kyra Gan, Nathan Kallus

From Vision to Audio and Beyond: A Unified Model for Audio-Visual Representation and Generation

Kun Su, Xiulong Liu, Eli Shlizerman

Fast Decision Boundary based Out-of-Distribution Detector

Litian Liu, Yao Qin

RL-VLM-F: Reinforcement Learning from Vision Language Foundation Model Feedback

Yufei Wang, Zhanyi Sun, Jesse Zhang et al.

Identification and Estimation for Nonignorable Missing Data: A Data Fusion Approach

Zixiao Wang, AmirEmad Ghassami, Ilya Shpitser

Encodings for Prediction-based Neural Architecture Search

Yash Akhauri, Mohamed Abdelfattah

Chain of Code: Reasoning with a Language Model-Augmented Code Emulator

Chengshu Li, Jacky Liang, Andy Zeng et al.

Conditional Common Entropy for Instrumental Variable Testing and Partial Identification

Ziwei Jiang, Murat Kocaoglu

On PI Controllers for Updating Lagrange Multipliers in Constrained Optimization

Motahareh Sohrabi, Juan Ramirez, Tianyue Zhang et al.

Online Matrix Completion: A Collaborative Approach with Hott Items

Dheeraj Baby, Soumyabrata Pal

Scaling Laws for Fine-Grained Mixture of Experts

Jan Ludziejewski, Jakub Krajewski, Kamil Adamczewski et al.

NeWRF: A Deep Learning Framework for Wireless Radiation Field Reconstruction and Channel Prediction

Haofan Lu, Christopher Vattheuer, Baharan Mirzasoleiman et al.

Efficient PAC Learnability of Dynamical Systems Over Multilayer Networks

Zirou Qiu, Abhijin Adiga, Madhav Marathe et al.

How Language Model Hallucinations Can Snowball

Muru Zhang, Ofir Press, William Merrill et al.

Prediction Accuracy of Learning in Games : Follow-the-Regularized-Leader meets Heisenberg

Yi Feng, Georgios Piliouras, Xiao Wang

PARCv2: Physics-aware Recurrent Convolutional Neural Networks for Spatiotemporal Dynamics Modeling

Phong Nguyen, Xinlun Cheng, Shahab Azarfar et al.

Unsupervised Concept Discovery Mitigates Spurious Correlations

Md Rifat Arefin, Yan Zhang, Aristide Baratin et al.

Model Assessment and Selection under Temporal Distribution Shift

Elise Han, Chengpiao Huang, Kaizheng Wang

The Fundamental Limits of Least-Privilege Learning

Theresa Stadler, Bogdan Kulynych, Michael Gastpar et al.

Sequential Disentanglement by Extracting Static Information From A Single Sequence Element

Nimrod Berman, Ilan Naiman, Idan Arbiv et al.

Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models

Louis Sharrock, Jack Simons, Song Liu et al.

Subgoal-based Demonstration Learning for Formal Theorem Proving

Xueliang Zhao, Wenda Li, Lingpeng Kong

Vector Quantization Pretraining for EEG Time Series with Random Projection and Phase Alignment

Haokun Gui, Xiucheng Li, Xinyang Chen

Emergence of In-Context Reinforcement Learning from Noise Distillation

Ilya Zisman, Vladislav Kurenkov, Alexander Nikulin et al.

Towards Modular LLMs by Building and Reusing a Library of LoRAs

Oleksiy Ostapenko, Zhan Su, Edoardo Ponti et al.

ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy

Kirill Vishniakov, Zhiqiang Shen, Zhuang Liu

Consistent Diffusion Meets Tweedie: Training Exact Ambient Diffusion Models with Noisy Data

Giannis Daras, Alexandros Dimakis, Constantinos Daskalakis

Optimally Improving Cooperative Learning in a Social Setting

Shahrzad Haddadan, Cheng Xin, Jie Gao

SiT: Symmetry-invariant Transformers for Generalisation in Reinforcement Learning

Matthias Weissenbacher, Rishabh Agarwal, Yoshinobu Kawahara

On Positivity Condition for Causal Inference

Inwoo Hwang, Yesong Choe, Yeahoon Kwon et al.

Dynamic Memory Compression: Retrofitting LLMs for Accelerated Inference

Piotr Nawrot, Adrian Łańcucki, Marcin Chochowski et al.

Linguistic Calibration of Long-Form Generations

Neil Band, Xuechen Li, Tengyu Ma et al.

A Unified Framework for Learning with Nonlinear Model Classes from Arbitrary Linear Samples

Ben Adcock, Juan Cardenas, Nick Dexter

Scalable High-Resolution Pixel-Space Image Synthesis with Hourglass Diffusion Transformers

Katherine Crowson, Stefan Baumann, Alex Birch et al.

Towards Optimal Adversarial Robust Q-learning with Bellman Infinity-error

Haoran Li, Zicheng Zhang, Wang Luo et al.

A Tale of Tails: Model Collapse as a Change of Scaling Laws

Elvis Dohmatob, Yunzhen Feng, Pu Yang et al.

Adversarial Attacks on Combinatorial Multi-Armed Bandits

Rishab Balasubramanian, Jiawei Li, Tadepalli Prasad et al.

Practical Hamiltonian Monte Carlo on Riemannian Manifolds via Relativity Theory

Kai Xu, Hong Ge

A Dynamic Algorithm for Weighted Submodular Cover Problem

Kiarash Banihashem, Samira Goudarzi, MohammadTaghi Hajiaghayi et al.

On The Fairness Impacts of Hardware Selection in Machine Learning

Sree Harsha Nelaturu, Nishaanth Kanna, Cuong Tran et al.

Graph Attention Retrospective

Kimon Fountoulakis, Amit Levi, Shenghao Yang et al.

A Mechanistic Understanding of Alignment Algorithms: A Case Study on DPO and Toxicity

Andrew Lee, Xiaoyan Bai, Itamar Pres et al.

Parameterized Physics-informed Neural Networks for Parameterized PDEs

Woojin Cho, Minju Jo, Haksoo Lim et al.

Safe Exploration in Dose Finding Clinical Trials with Heterogeneous Participants

Isabel Chien, Wessel Bruinsma, Javier Gonzalez et al.

High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise

Eduard Gorbunov, Abdurakhmon Sadiev, Marina Danilova et al.

A Unified Recipe for Deriving (Time-Uniform) PAC-Bayes Bounds

Ben Chugg, Hongjian Wang, Aaditya Ramdas

RankSEG: A Consistent Ranking-based Framework for Segmentation

Ben Dai, Chunlin Li

PruNeRF: Segment-Centric Dataset Pruning via 3D Spatial Consistency

Yeonsung Jung, Heecheol Yun, Joonhyung Park et al.

Bridging discrete and continuous state spaces: Exploring the Ehrenfest process in time-continuous diffusion models

Ludwig Winkler, Lorenz Richter, Manfred Opper

Learning to Continually Learn with the Bayesian Principle

Soochan Lee, Hyeonseong Jeon, Jaehyeon Son et al.

Benign Overfitting in Two-Layer ReLU Convolutional Neural Networks for XOR Data

Xuran Meng, Difan Zou, Yuan Cao

Repoformer: Selective Retrieval for Repository-Level Code Completion

Di Wu, Wasi Ahmad, Dejiao Zhang et al.

Zero-Sum Positional Differential Games as a Framework for Robust Reinforcement Learning: Deep Q-Learning Approach

Anton Plaksin, Vitaly Kalev

On the Generalization of Stochastic Gradient Descent with Momentum

Ali Ramezani-Kebrya, Kimon Antonakopoulos, Volkan Cevher et al.

A Geometric Explanation of the Likelihood OOD Detection Paradox

Hamidreza Kamkari, Brendan Ross, Jesse Cresswell et al.

Leveraging Attractor Dynamics in Spatial Navigation for Better Language Parsing

Xiaolong Zou, Xingxing Cao, Xiaojiao Yang et al.

Disparate Impact on Group Accuracy of Linearization for Private Inference

Saswat Das, Marco Romanelli, Ferdinando Fioretto

SqueezeLLM: Dense-and-Sparse Quantization

Sehoon Kim, Coleman Hooper, Amir Gholaminejad et al.

Closing the Gap: Achieving Global Convergence (Last Iterate) of Actor-Critic under Markovian Sampling with Neural Network Parametrization

Mudit Gaur, Amrit Singh Bedi, Di Wang et al.

An LLM Compiler for Parallel Function Calling

Sehoon Kim, Suhong Moon, Ryan Tabrizi et al.

Unbiased Multi-Label Learning from Crowdsourced Annotations

Mingxuan Xia, Zenan Huang, Runze Wu et al.

Irregular Multivariate Time Series Forecasting: A Transformable Patching Graph Neural Networks Approach

Weijia Zhang, Chenlong Yin, Hao Liu et al.

Simplicity Bias via Global Convergence of Sharpness Minimization

Khashayar Gatmiry, Zhiyuan Li, Sashank J. Reddi et al.

An Intrinsic Vector Heat Network

Alexander Gao, Maurice Chu, Mubbasir Kapadia et al.

Stochastic Quantum Sampling for Non-Logconcave Distributions and Estimating Partition Functions

Guneykan Ozgul, Xiantao Li, Mehrdad Mahdavi et al.

Enabling Uncertainty Estimation in Iterative Neural Networks

Nikita Durasov, Doruk Oner, Jonathan Donier et al.

MultiMax: Sparse and Multi-Modal Attention Learning

Yuxuan Zhou, Mario Fritz, Margret Keuper

Improving Neural Additive Models with Bayesian Principles

Kouroche Bouchiat, Alexander Immer, Hugo Yèche et al.

Averaging $n$-step Returns Reduces Variance in Reinforcement Learning

Brett Daley, Martha White, Marlos C. Machado

Implicit meta-learning may lead language models to trust more reliable sources

Dmitrii Krasheninnikov, Egor Krasheninnikov, Bruno Mlodozeniec et al.

Multi-Track Message Passing: Tackling Oversmoothing and Oversquashing in Graph Learning via Preventing Heterophily Mixing

Hongbin Pei, Yu Li, Huiqi Deng et al.

Residual-Conditioned Optimal Transport: Towards Structure-Preserving Unpaired and Paired Image Restoration

Xiaole Tang, Hu Xin, Xiang Gu et al.

Do Models Explain Themselves? Counterfactual Simulatability of Natural Language Explanations

Yanda Chen, Ruiqi Zhong, Narutatsu Ri et al.

Total Variation Distance Meets Probabilistic Inference

Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel et al.

A3S: A General Active Clustering Method with Pairwise Constraints

Xun Deng, Junlong Liu, Han Zhong et al.

An Online Optimization Perspective on First-Order and Zero-Order Decentralized Nonsmooth Nonconvex Stochastic Optimization

Emre Sahinoglu, Shahin Shahrampour

Learning a Diffusion Model Policy from Rewards via Q-Score Matching

Michael Psenka, Alejandro Escontrela, Pieter Abbeel et al.

Online Cascade Learning for Efficient Inference over Streams

Lunyiu Nie, Zhimin Ding, Erdong Hu et al.

Scaling Speech Technology to 1,000+ Languages

Vineel Pratap Konduru, Andros Tjandra, Bowen Shi et al.

Robustness of Nonlinear Representation Learning

Simon Buchholz, Bernhard Schölkopf

Symmetry Induces Structure and Constraint of Learning

Liu Ziyin

A Dynamical Model of Neural Scaling Laws

Blake Bordelon, Alexander Atanasov, Cengiz Pehlevan

Adaptive Learning of Density Ratios in RKHS

Werner Zellinger, Stefan Kindermann, Sergei V. Pereverzyev

Adaptively Perturbed Mirror Descent for Learning in Games

Kenshi Abe, Kaito Ariu, Mitsuki Sakamoto et al.

Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning

Idan Achituve, Idit Diamant, Arnon Netzer et al.

FrameQuant: Flexible Low-Bit Quantization for Transformers

Harshavardhan Adepu, Zhanpeng Zeng, Li Zhang et al.

Optimal Coresets for Low-Dimensional Geometric Median

Peyman Afshani, Chris Schwiegelshohn

Learning to Play Atari in a World of Tokens

Pranav Agarwal, Sheldon Andrews, Samira Ebrahimi Kahou

LeaPformer: Enabling Linear Transformers for Autoregressive and Simultaneous Tasks via Learned Proportions

Victor Agostinelli III, Sanghyun Hong, Lizhong Chen

How to Escape Sharp Minima with Random Perturbations

Kwangjun Ahn, Ali Jadbabaie, Suvrit Sra

Not all distributional shifts are equal: Fine-grained robust conformal inference

Jiahao Ai, Zhimei Ren

Nonlinear Filtering with Brenier Optimal Transport Maps

Mohammad Al-Jarrah, Niyizhen Jin, Bamdad Hosseini et al.

Gaussian Processes on Cellular Complexes

Mathieu Alain, So Takao, Brooks Paige et al.

No Dimensional Sampling Coresets for Classification

Meysam Alishahi, Jeff Phillips

Robust and Conjugate Gaussian Process Regression

Matias Altamirano, Francois-Xavier Briol, Jeremias Knoblauch

Hyperbolic Optimizer as a Dynamical System

Nico Alvarado, Hans Lobel

Stationarity without mean reversion in improper Gaussian processes

Luca Ambrogioni

Fast Algorithms for Hypergraph PageRank with Applications to Semi-Supervised Learning

Konstantinos Ameranis, Adela DePavia, Lorenzo Orecchia et al.

Scalable Online Exploration via Coverability

Philip Amortila, Dylan Foster, Akshay Krishnamurthy

Adaptive Hierarchical Certification for Segmentation using Randomized Smoothing

Alaa Anani, Tobias Lorenz, Bernt Schiele et al.

Online conformal prediction with decaying step sizes

Anastasios Angelopoulos, Rina Barber, Stephen Bates

Causal Action Influence Aware Counterfactual Data Augmentation

Núria Armengol Urpí, Marco Bagatella, Marin Vlastelica et al.

Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages

Hilal Asi, Vitaly Feldman, Jelani Nelson et al.

How Free is Parameter-Free Stochastic Optimization?

Amit Attia, Tomer Koren

Bipartite Matching in Massive Graphs: A Tight Analysis of EDCS

Amir Azarmehr, Soheil Behnezhad, Mohammad Roghani

Simulation of Graph Algorithms with Looped Transformers

Artur Back de Luca, Kimon Fountoulakis

On the Complexity of Finite-Sum Smooth Optimization under the Polyak–Łojasiewicz Condition

Yunyan Bai, Yuxing Liu, Luo Luo

Constrained Ensemble Exploration for Unsupervised Skill Discovery

Chenjia Bai, Rushuai Yang, Qiaosheng Zhang et al.

On the Identifiability of Switching Dynamical Systems

Carles Balsells-Rodas, Yixin Wang, Yingzhen Li

VNN: Verification-Friendly Neural Networks with Hard Robustness Guarantees

Anahita Baninajjar, Ahmed Rezine, Amir Aminifar

Monotone Individual Fairness

Yahav Bechavod

Standardized Interpretable Fairness Measures for Continuous Risk Scores

Ann-Kristin Becker, Oana Dumitrasc, Klaus Broelemann

Neural Networks Learn Statistics of Increasing Complexity

Nora Belrose, Quintin Pope, Lucia Quirke et al.

The Role of Learning Algorithms in Collective Action

Omri Ben-Dov, Jake Fawkes, Samira Samadi et al.

CoLoRA: Continuous low-rank adaptation for reduced implicit neural modeling of parameterized partial differential equations

Jules Berman, Benjamin Peherstorfer

By Tying Embeddings You Are Assuming the Distributional Hypothesis

Bertolotti Francesco, Walter Cazzola

Controlling Behavioral Diversity in Multi-Agent Reinforcement Learning

Matteo Bettini, Ryan Kortvelesy, Amanda Prorok

Guiding LLMs The Right Way: Fast, Non-Invasive Constrained Generation

Luca Beurer-Kellner, Marc Fischer, Martin Vechev

Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features

Aleksandr Beznosikov, David Dobre, Gauthier Gidel

Why do Variational Autoencoders Really Promote Disentanglement?

Pratik Bhowal, Achint Soni, Sirisha Rambhatla

Best of Both Worlds Guarantees for Smoothed Online Quadratic Optimization

Neelkamal Bhuyan, Debankur Mukherjee, Adam Wierman

Naive Bayes Classifiers over Missing Data: Decision and Poisoning

Song Bian, Xiating Ouyang, ZHIWEI FAN et al.

Position: Explain to Question not to Justify

Przemyslaw Biecek, Wojciech Samek

Dynamic Survival Analysis with Controlled Latent States

Linus Bleistein, Van NGUYEN, Adeline Fermanian et al.

Shifted Interpolation for Differential Privacy

Jinho Bok, Weijie Su, Jason Altschuler

Towards Understanding the Word Sensitivity of Attention Layers: A Study via Random Features

Simone Bombari, Marco Mondelli

On dimensionality of feature vectors in MPNNs

César Bravo, Alexander Kozachinskiy, Cristobal Rojas

Private Gradient Descent for Linear Regression: Tighter Error Bounds and Instance-Specific Uncertainty Estimation

Gavin Brown, Krishnamurthy Dvijotham, Georgina Evans et al.

Provably Neural Active Learning Succeeds via Prioritizing Perplexing Samples

Dake Bu, Wei Huang, Taiji Suzuki et al.

Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More

Fanchen Bu, Hyeonsoo Jo, Soo Yong Lee et al.

Differentially Private Bias-Term Fine-tuning of Foundation Models

Zhiqi Bu, Yu-Xiang Wang, Sheng Zha et al.

How Uniform Random Weights Induce Non-uniform Bias: Typical Interpolating Neural Networks Generalize with Narrow Teachers

Gon Buzaglo, Itamar Harel, Mor Shpigel Nacson et al.

Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads

Tianle Cai, Yuhong Li, Zhengyang Geng et al.

Enhancing Cross-Modal Fine-Tuning with Gradually Intermediate Modality Generation

Lincan Cai, Shuang Li, Wenxuan Ma et al.

Accelerated Algorithms for Constrained Nonconvex-Nonconcave Min-Max Optimization and Comonotone Inclusion

Yang Cai, Argyris Oikonomou, Weiqiang Zheng

Sample-specific Masks for Visual Reprogramming-based Prompting

Chengyi Cai, Zesheng Ye, Lei Feng et al.

Predictive Dynamic Fusion

Bing Cao, Yinan Xia, Yi Ding et al.

AI Alignment with Changing and Influenceable Reward Functions

Micah Carroll, Davis Foote, Anand Siththaranjan et al.

Online Learning under Budget and ROI Constraints via Weak Adaptivity

Matteo Castiglioni, Andrea Celli, Christian Kroer

Simple Ingredients for Offline Reinforcement Learning

Edoardo Cetin, Andrea Tirinzoni, Matteo Pirotta et al.

Auditing Private Prediction

Karan Chadha, Matthew Jagielski, Nicolas Papernot et al.

Scribble-Supervised Semantic Segmentation with Prototype-based Feature Augmentation

Guiyang Chan, Pengcheng Zhang, Hai Dong et al.

Inferring Dynamic Networks from Marginals with Iterative Proportional Fitting

Serina Chang, Frederic Koehler, Zhaonan Qu et al.

How Interpretable Are Interpretable Graph Neural Networks?

Yongqiang Chen, Yatao Bian, Bo Han et al.

Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal Explanation

Xuexin Chen, Ruichu Cai, Zhengting Huang et al.

Robust Classification via a Single Diffusion Model

Huanran Chen, Yinpeng Dong, Zhengyi Wang et al.

Relational Learning in Pre-Trained Models: A Theory from Hypergraph Recovery Perspective

Yang Chen, Cong Fang, Zhouchen Lin et al.

RigorLLM: Resilient Guardrails for Large Language Models against Undesired Content

Zhuowen Yuan, Zidi Xiong, Yi Zeng et al.

Probabilistic Forecasting with Stochastic Interpolants and Föllmer Processes

Yifan Chen, Mark Goldstein, Mengjian Hua et al.

CogDPM: Diffusion Probabilistic Models via Cognitive Predictive Coding

Kaiyuan Chen, Xingzhuo Guo, Yu Zhang et al.

Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy

Wei-Ning Chen, Berivan Isik, Peter Kairouz et al.

Efficient Pareto Manifold Learning with Low-Rank Structure

Weiyu CHEN, James Kwok

EE-LLM: Large-Scale Training and Inference of Early-Exit Large Language Models with 3D Parallelism

Yanxi Chen, Xuchen Pan, Yaliang Li et al.

Recovering Labels from Local Updates in Federated Learning

Huancheng Chen, Haris Vikalo

Locally Differentially Private Decentralized Stochastic Bilevel Optimization with Guaranteed Convergence Accuracy

Ziqin Chen, Yongqiang Wang

Subequivariant Reinforcement Learning in 3D Multi-Entity Physical Environments

Runfa Chen, Ling Wang, Yu Du et al.

A General Framework for Learning from Weak Supervision

Hao Chen, Jindong Wang, Lei Feng et al.

Diffusion Model-Augmented Behavioral Cloning

Shang-Fu Chen, Hsiang-Chun Wang, Ming-Hao Hsu et al.

In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation

Shiqi Chen, Miao Xiong, Junteng Liu et al.

Split-Ensemble: Efficient OOD-aware Ensemble via Task and Model Splitting

Anthony Chen, Huanrui Yang, Yulu Gan et al.

DRCT: Diffusion Reconstruction Contrastive Training towards Universal Detection of Diffusion Generated Images

Baoying Chen, Jishen Zeng, Jianquan Yang et al.

FedMBridge: Bridgeable Multimodal Federated Learning

Jiayi Chen, Aidong Zhang

Revealing the Dark Secrets of Extremely Large Kernel ConvNets on Robustness

Honghao Chen, Zhang Yurong, xiaokun Feng et al.

Diffusive Gibbs Sampling

Wenlin Chen, Mingtian Zhang, Brooks Paige et al.

Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation

Yu Chen, XiangCheng Zhang, Siwei Wang et al.

RICE: Breaking Through the Training Bottlenecks of Reinforcement Learning with Explanation

Zelei Cheng, Xian Wu, Jiahao Yu et al.

RIME: Robust Preference-based Reinforcement Learning with Noisy Preferences

Jie Cheng, Gang Xiong, Xingyuan Dai et al.

Leveraging (Biased) Information: Multi-armed Bandits with Offline Data

Wang Chi Cheung, Lixing Lyu

Expert Proximity as Surrogate Rewards for Single Demonstration Imitation Learning

Chia-Cheng Chiang, Li-Cheng Lan, Wei-Fang Sun et al.

Enhancing Trajectory Prediction through Self-Supervised Waypoint Distortion Prediction

Pranav Singh Chib, Pravendra Singh

How Flawed Is ECE? An Analysis via Logit Smoothing

Muthu Chidambaram, Holden Lee, Colin McSwiggen et al.

Neurodegenerative Brain Network Classification via Adaptive Diffusion with Temporal Regularization

Hyuna Cho, Jaeyoon Sim, Guorong Wu et al.