Most Cited ICLR "lay summary generation" Papers
6,124 papers found • Page 28 of 31
Conference
Training Graph Transformers via Curriculum-Enhanced Attention Distillation
Yisong Huang, Jin Li, Xinlong Chen et al.
Project and Probe: Sample-Efficient Adaptation by Interpolating Orthogonal Features
Annie Chen, Yoonho Lee, Amrith Setlur et al.
BBCaL: Black-box Backdoor Detection under the Causality Lens
Zihan Guan, Junfeng Guo, Mengxuan Hu et al.
LUM-ViT: Learnable Under-sampling Mask Vision Transformer for Bandwidth Limited Optical Signal Acquisition
Lingfeng Liu, Dong Ni, Hangjie Yuan
CONDA: Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts
Jihye Choi, Jayaram Raghuram, Yixuan Li et al.
Accelerated Sampling with Stacked Restricted Boltzmann Machines
Jorge Fernandez-de-Cossio-Diaz, Clément Roussel, Simona Cocco et al.
On the Sample Complexity of Lipschitz Constant Estimation
Stephen Roberts, Julien Huang, Jan-Peter Calliess
Adaptive Transformer Programs: Bridging the Gap Between Performance and Interpretability in Transformers
Quoc-Vinh Lai-Dang, Taemin Kang, Seungah Son
Model-Agnostic Knowledge Guided Correction for Improved Neural Surrogate Rollout
Bharat Srikishan, Daniel O'Malley, Mohamed Mehana et al.
Meta-Learning Priors Using Unrolled Proximal Networks
Yilang Zhang, Georgios B Giannakis
Learning Diagrams: A Graphical Language for Compositional Training Regimes
Mason Lary, Richard Samuelson, Alexander Wilentz et al.
Singular Subspace Perturbation Bounds via Rectangular Random Matrix Diffusions
Peiyao Lai, Oren Mangoubi
Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional, Black-box Systems
Dan MacKinlay, Russell Tsuchida, Daniel Pagendam et al.
Policy Rehearsing: Training Generalizable Policies for Reinforcement Learning
Chengxing Jia, Chen-Xiao Gao, Hao Yin et al.
Beyond Worst-Case Dimensionality Reduction for Sparse Vectors
Sandeep Silwal, David Woodruff, Qiuyi (Richard) Zhang
Rethinking the Power of Graph Canonization in Graph Representation Learning with Stability
Zehao Dong, Muhan Zhang, Philip Payne et al.
Can Watermarks be Used to Detect LLM IP Infringement For Free?
Zhengyue Zhao, Xiaogeng Liu, Somesh Jha et al.
Laplace Sample Information: Data Informativeness Through a Bayesian Lens
Johannes Kaiser, Kristian Schwethelm, Daniel Rueckert et al.
Leveraging Variable Sparsity to Refine Pareto Stationarity in Multi-Objective Optimization
Zeou Hu, Yaoliang Yu
ModernTCN: A Modern Pure Convolution Structure for General Time Series Analysis
DongHao Luo, Xue Wang
Parameter-Efficient Multi-Task Model Fusion with Partial Linearization
Anke Tang, Li Shen, Yong Luo et al.
When do GFlowNets learn the right distribution?
Tiago Silva, Rodrigo Alves, Eliezer de Souza da Silva et al.
Towards a Complete Logical Framework for GNN Expressiveness
Tuo Xu
Wayward Concepts In Multimodal Models
Brandon Trabucco, Max Gurinas, Kyle Doherty et al.
Context is Environment
Sharut Gupta, Stefanie Jegelka, David Lopez-Paz et al.
On the Role of General Function Approximation in Offline Reinforcement Learning
Chenjie Mao, Qiaosheng Zhang, Zhen Wang et al.
CryoGEN: Generative Energy-based Models for Cryogenic Electron Tomography Reconstruction
Yunfei Teng, Yuxuan Ren, Kai Chen et al.
Forward $\chi^2$ Divergence Based Variational Importance Sampling
Chengrui Li, Yule Wang, Weihan Li et al.
Linear Multistep Solver Distillation for Fast Sampling of Diffusion Models
Yuchen Yuchen, Xiangzhong Fang, Hanting Chen et al.
Rethinking the Benefits of Steerable Features in 3D Equivariant Graph Neural Networks
Shih-Hsin Wang, Yung-Chang Hsu, Justin Baker et al.
Rethinking Shapley Value for Negative Interactions in Non-convex Games
Wonjoon Chang, Myeongjin Lee, Jaesik Choi
Achieving Fairness in Multi-Agent MDP Using Reinforcement Learning
Peizhong Ju, Arnob Ghosh, Ness Shroff
Piecewise Linear Parametrization of Policies: Towards Interpretable Deep Reinforcement Learning
Maxime Wabartha, Joelle Pineau
Re-Evaluating the Impact of Unseen-Class Unlabeled Data on Semi-Supervised Learning Model
Rundong He, Yicong Dong, Lan-Zhe Guo et al.
Matérn Kernels for Tunable Implicit Surface Reconstruction
Maximilian Weiherer, Bernhard Egger
SaNN: Simple Yet Powerful Simplicial-aware Neural Networks
Sravanthi Gurugubelli, Sundeep Prabhakar Chepuri
DMBP: Diffusion model-based predictor for robust offline reinforcement learning against state observation perturbations
Zhihe Yang, Yunjian Xu
Integrating Planning and Deep Reinforcement Learning via Automatic Induction of Task Substructures
Jung-Chun Liu, Chi-Hsien Chang, Shao-Hua Sun et al.
Examining Alignment of Large Language Models through Representative Heuristics: the case of political stereotypes
Sullam Jeoung, Yubin Ge, Haohan Wang et al.
In Search of the Engram in LLMs: A Neuroscience Perspective on the Memory Functions in AI Models
Minsung Kim, Jea Kwon, Dong-Kyum Kim et al.
Light-MILPopt: Solving Large-scale Mixed Integer Linear Programs with Lightweight Optimizer and Small-scale Training Dataset
Huigen Ye, Hua Xu, Hongyan Wang
AUC-CL: A Batchsize-Robust Framework for Self-Supervised Contrastive Representation Learning
Rohan Sharma, Kaiyi Ji, Zhiqiang Xu et al.
The Generative AI Paradox: “What It Can Create, It May Not Understand”
Peter West, Ximing Lu, Nouha Dziri et al.
Online-to-Offline RL for Agent Alignment
Xu Liu, Haobo Fu, Stefano V. Albrecht et al.
Fast, Expressive $\mathrm{SE}(n)$ Equivariant Networks through Weight-Sharing in Position-Orientation Space
Erik Bekkers, Sharvaree Vadgama, Rob Hesselink et al.
Transferring Labels to Solve Annotation Mismatches Across Object Detection Datasets
Yuan-Hong Liao, David Acuna, Rafid Mahmood et al.
Efficient Backpropagation with Variance Controlled Adaptive Sampling
Ziteng Wang, Jianfei Chen, Jun Zhu
Investigating Pattern Neurons in Urban Time Series Forecasting
Chengxin Wang, Yiran Zhao, shaofeng cai et al.
A Dynamical View of the Question of Why
Mehdi Fatemi, Sindhu Chatralinganadoddi Mariyappa Gowda
Estimation of single-cell and tissue perturbation effect in spatial transcriptomics via Spatial Causal Disentanglement
Stathis Megas, Daniel Chen, Krzysztof Polanski et al.
Competitive Fair Scheduling with Predictions
Tianming Zhao, Chunqiu xia, Xiaomin Chang et al.
Should VLMs be Pre-trained with Image Data?
Sedrick Keh, Jean Mercat, Samir Yitzhak Gadre et al.
MAESTRO: Masked Encoding Set Transformer with Self-Distillation
Matthew Lee, Jaesik Kim, Matei Ionita et al.
Towards Domain Adaptive Neural Contextual Bandits
Ziyan Wang, Xiaoming Huo, Hao Wang
dEBORA: Efficient Bilevel Optimization-based low-Rank Adaptation
Emanuele Zangrando, Sara Venturini, Francesco Rinaldi et al.
Leveraging augmented-Lagrangian techniques for differentiating over infeasible quadratic programs in machine learning
Antoine Bambade, Fabian Schramm, Adrien Taylor et al.
FedDA: Faster Adaptive Gradient Methods for Federated Constrained Optimization
Junyi Li, Feihu Huang, Heng Huang
Boosting Graph Anomaly Detection with Adaptive Message Passing
Jingyan Chen, Guanghui Zhu, Chunfeng Yuan et al.
Multi-session, multi-task neural decoding from distinct cell-types and brain regions
Mehdi Azabou, Krystal Pan, Vinam Arora et al.
$\alpha$TC-VAE: On the relationship between Disentanglement and Diversity
Cristian Meo, Louis Mahon, Anirudh Goyal et al.
Neuralized Markov Random Field for Interaction-Aware Stochastic Human Trajectory Prediction
Zilin Fang, David Hsu, Gim H Lee
CAS: A Probability-Based Approach for Universal Condition Alignment Score
Chunsan Hong, ByungHee Cha, Tae-Hyun Oh
On the Analysis of GAN-based Image-to-Image Translation with Gaussian Noise Injection
Chaohua Shi, Kexin Huang, Lu Gan et al.
SEMDICE: Off-policy State Entropy Maximization via Stationary Distribution Correction Estimation
Jongmin Lee, Meiqi Sun, Pieter Abbeel
Open-CK: A Large Multi-Physics Fields Coupling benchmarks in Combustion Kinetics
Zaige Fei, Fan Xu, Junyuan Mao et al.
Improving the Convergence of Dynamic NeRFs via Optimal Transport
Sameera Ramasinghe, Violetta Shevchenko, Gil Avraham et al.
A Discretization Framework for Robust Contextual Stochastic Optimization
Rares Cristian, Georgia Perakis
Intricacies of Feature Geometry in Large Language Models
Satvik Golechha, Lucius Bushnaq, Euan Ong et al.
Leveraging Generative Models for Unsupervised Alignment of Neural Time Series Data
Ayesha Vermani, Il Memming Park, Josue Nassar
PiCO: Peer Review in LLMs based on Consistency Optimization
Kun-Peng Ning, Shuo Yang, Yuyang Liu et al.
Pacmann: Efficient Private Approximate Nearest Neighbor Search
Mingxun Zhou, Elaine Shi, Giulia Fanti
Mixture-of-Experts Meets Instruction Tuning: A Winning Combination for Large Language Models
Sheng Shen, Le Hou, Yanqi Zhou et al.
What's New in My Data? Novelty Exploration via Contrastive Generation
Masaru Isonuma, Ivan Titov
CameraCtrl: Enabling Camera Control for Video Diffusion Models
Hao He, Yinghao Xu, Yuwei Guo et al.
The Cost of Scaling Down Large Language Models: Reducing Model Size Affects Memory before In-context Learning
Tian Jin, Nolan Clement, Xin Dong et al.
Learning model uncertainty as variance-minimizing instance weights
Nishant Jain, Karthikeyan Shanmugam, Pradeep Shenoy
Shape as Line Segments: Accurate and Flexible Implicit Surface Representation
Siyu Ren, Junhui Hou
Fewer May Be Better: Enhancing Offline Reinforcement Learning with Reduced Dataset
Yiqin Yang, Quanwei Wang, Chenghao Li et al.
Continuity-Preserving Convolutional Autoencoders for Learning Continuous Latent Dynamical Models from Images
Aiqing Zhu, Yuting Pan, Qianxiao Li
Why RoPE Struggles to Maintain Long-Term Decay in Long Sequences?
Wei Shen, Chao Yin, Yuliang Liu et al.
Test-time Adaptation against Multi-modal Reliability Bias
Mouxing Yang, Yunfan Li, Changqing Zhang et al.
LLaVA-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models
Feng Li, Renrui Zhang, Hao Zhang et al.
Enhancing Contrastive Learning for Ordinal Regression via Ordinal Content Preserved Data Augmentation
Jiyang Zheng, Yu Yao, Bo Han et al.
SPDER: Semiperiodic Damping-Enabled Object Representation
Kathan Shah, Chawin Sitawarin
pMoE: Prompting Diverse Experts Together Wins More in Visual Adaptation
Shentong Mo, Xufang Luo, Dongsheng Li
ParFam -- (Neural Guided) Symbolic Regression via Continuous Global Optimization
Philipp Scholl, Katharina Bieker, Hillary Hauger et al.
Neuron-Enhanced AutoEncoder Matrix Completion and Collaborative Filtering: Theory and Practice
Jicong Fan, Rui Chen, Zhao Zhang et al.
NExUME: Adaptive Training and Inference for DNNs under Intermittent Power Environments
Cyan Subhra Mishra, Deeksha Chaudhary, Jack Sampson et al.
Mind Your Augmentation: The Key to Decoupling Dense Self-Supervised Learning
Congpei Qiu, Tong Zhang, Yanhao Wu et al.
Diff-2-in-1: Bridging Generation and Dense Perception with Diffusion Models
Shuhong Zheng, Zhipeng Bao, Ruoyu Zhao et al.
Root Cause Analysis of Anomalies in Multivariate Time Series through Granger Causal Discovery
Xiao Han, Saima Absar, Lu Zhang et al.
Exposing and Addressing Cross-Task Inconsistency in Unified Vision-Language Models
Aniruddha Kembhavi, Mohit Bansal, Amita Kamath et al.
PIN: Prolate Spheroidal Wave Function-based Implicit Neural Representations
Viraj Dhananjaya Bandara Jayasundara Jayasundara Mudiyanselage, Heng Zhao, Demetrio Labate et al.
ODE-based Smoothing Neural Network for Reinforcement Learning Tasks
Yinuo Wang, Wenxuan Wang, Xujie Song et al.
General Stability Analysis for Zeroth-Order Optimization Algorithms
Xinyue Liu, Hualin Zhang, Bin Gu et al.
Neural Polynomial Gabor Fields for Macro Motion Analysis
Chen Geng, Koven Yu, Sida Peng et al.
Learning Nash Equilibria in Rank-1 Games
Nikolas Patris, Ioannis Panageas
GTMGC: Using Graph Transformer to Predict Molecule’s Ground-State Conformation
Guikun Xu, Yongquan Jiang, PengChuan Lei et al.
Scaling Laws for Adversarial Attacks on Language Model Activations and Tokens
Stanislav Fort
Mentored Learning: Improving Generalization and Convergence of Student Learner
Xiaofeng Cao, Yaming Guo, Heng Tao Shen et al.
Consistent Multi-Class Classification from Multiple Unlabeled Datasets
Zixi Wei, Senlin Shu, Yuzhou Cao et al.
Edge-aware Image Smoothing with Relative Wavelet Domain Representation
Huiqing Qi, Xiaoliu Luo, Tingting Li et al.
Accelerating Neural ODEs: A Variational Formulation-based Approach
Hongjue Zhao, Yuchen Wang, Hairong Qi et al.
Streaming Algorithms For $\ell_p$ Flows and $\ell_p$ Regression
Amit Chakrabarti, Jeffrey Jiang, David Woodruff et al.
Scalable and Effective Implicit Graph Neural Networks on Large Graphs
Juncheng Liu, Bryan Hooi, Kenji Kawaguchi et al.
Rethinking Branching on Exact Combinatorial Optimization Solver: The First Deep Symbolic Discovery Framework
Yufei Kuang, Jie Wang, Haoyang Liu et al.
GraphPulse: Topological representations for temporal graph property prediction
Kiarash Shamsi, Farimah Poursafaei, Shenyang(Andy) Huang et al.
BrainLM: A foundation model for brain activity recordings
Josue Ortega Caro, Antonio Henrique de Oliveira Fonseca, Syed Rizvi et al.
Reassessing EMNLP 2024’s Best Paper: Does Divergence-Based Calibration for MIAs Hold Up?
Pratyush Maini, Anshuman Suri
VersVideo: Leveraging Enhanced Temporal Diffusion Models for Versatile Video Generation
Jinxi Xiang, Ricong Huang, Jun Zhang et al.
Dictionary Contrastive Learning for Efficient Local Supervision without Auxiliary Networks
Suhwan Choi, Myeongho Jeon, Yeonjung Hwang et al.
Label-Focused Inductive Bias over Latent Object Features in Visual Classification
Ilmin Kang, HyounYoung Bae, Kangil Kim
Dissecting learning and forgetting in language model finetuning
Xiao Zhang, Ji Wu
Revisit the Open Nature of Open Vocabulary Semantic Segmentation
Qiming Huang, Han Hu, Jianbo Jiao
Deep Geodesic Canonical Correlation Analysis for Covariance-Based Neuroimaging Data
Ce Ju, Reinmar Kobler, Liyao Tang et al.
Differentiable Integer Linear Programming
Zijie Geng, Jie Wang, Xijun Li et al.
DeepTAGE: Deep Temporal-Aligned Gradient Enhancement for Optimizing Spiking Neural Networks
Wei Liu, Li Yang, Mingxuan Zhao et al.
Zero-Shot Robotic Manipulation with Pre-Trained Image-Editing Diffusion Models
Kevin Black, Mitsuhiko Nakamoto, Pranav Atreya et al.
Tangent Transformers for Composition,Privacy and Removal
Tian Yu Liu, Aditya Golatkar, Stefano Soatto
ContraDiff: Planning Towards High Return States via Contrastive Learning
Yixiang Shan, Zhengbang Zhu, Ting Long et al.
CONGO: Compressive Online Gradient Optimization
Jeremy Carleton, Prathik Vijaykumar, Divyanshu Saxena et al.
Class Distribution-induced Attention Map for Open-vocabulary Semantic Segmentations
Dong Un Kang, Hayeon Kim, Se Young Chun
Extendable and Iterative Structure Learning Strategy for Bayesian Networks
Hamid Kalantari, Russell Greiner, Pouria Ramazi
Bridging the Gap Between f-divergences and Bayes Hilbert Spaces
Linus Lach, Alexander Fottner, Yarema Okhrin
Reconstruction-Guided Policy: Enhancing Decision-Making through Agent-Wise State Consistency
Qifan Liang, Yixiang Shan, Haipeng Liu et al.
Kernelised Normalising Flows
Eshant English, Matthias Kirchler, Christoph Lippert
Candidate Label Set Pruning: A Data-centric Perspective for Deep Partial-label Learning
Shuo He, Chaojie Wang, Guowu Yang et al.
Disentangling 3D Animal Pose Dynamics with Scrubbed Conditional Latent Variables
Joshua Wu, Hari Koneru, James Ravenel et al.
LaMPlace: Learning to Optimize Cross-Stage Metrics in Macro Placement
Zijie Geng, Jie Wang, Ziyan Liu et al.
Efficient Continual Finite-Sum Minimization
Ioannis Mavrothalassitis, Stratis Skoulakis, Leello Dadi et al.
A Simple Romance Between Multi-Exit Vision Transformer and Token Reduction
Dongyang Liu, Meina Kan, Shiguang Shan et al.
Periodicity Decoupling Framework for Long-term Series Forecasting
Tao Dai, Beiliang Wu, Peiyuan Liu et al.
Diffusion-based Decoupled Deterministic and Uncertain Framework for Probabilistic Multivariate Time Series Forecasting
Qi Li, Zhenyu Zhang, Lei Yao et al.
On Stationary Point Convergence of PPO-Clip
Ruinan Jin, Shuai Li, Baoxiang Wang
KinFormer: Generalizable Dynamical Symbolic Regression for Catalytic Organic Reaction Kinetics
Jindou Chen, Jidong Tian, Liang Wu et al.
GrabS: Generative Embodied Agent for 3D Object Segmentation without Scene Supervision
Zihui Zhang, Yafei YANG, Hongtao Wen et al.
RandLoRA: Full rank parameter-efficient fine-tuning of large models
Paul Albert, Frederic Zhang, Hemanth Saratchandran et al.
Searching for Optimal Solutions with LLMs via Bayesian Optimization
Dhruv Agarwal, Manoj Ghuhan Arivazhagan, Rajarshi Das et al.
Models trained with unnormalized density functions: A need for a course correction
Rishal Aggarwal, Daniel Penaherrera, Justin Shao et al.
REMEDY: Recipe Merging Dynamics in Large Vision-Language Models
Didi Zhu, Yibing Song, tao shen et al.
Discovering Clone Negatives via Adaptive Contrastive Learning for Image-Text Matching
Renjie Pan, Jihao Dong, Hua Yang
TSVD: Bridging Theory and Practice in Continual Learning with Pre-trained Models
Liangzu Peng, Juan Elenter, Joshua Agterberg et al.
Learning No-Regret Sparse Generalized Linear Models with Varying Observation(s)
Diyang Li, Charles Ling, Zhiqiang Xu et al.
Coreset Spectral Clustering
Ben Jourdan, Gregory Schwartzman, Peter Macgregor et al.
Exploiting Hankel-Toeplitz Structures for Fast Computation of Kernel Precision Matrices
Frida Viset, Frederiek Wesel, Arno Solin et al.
Start Smart: Leveraging Gradients For Enhancing Mask-based XAI Methods
Buelent Uendes, Shujian Yu, Mark Hoogendoorn
Neural Wave Equation for Irregularly Sampled Sequence Data
Arkaprava Majumdar, M Anand Krishna, P. K. Srijith
Analysing The Spectral Biases in Generative Models
Amitoj Miglani, Shweta Singh, Vidit Aggarwal
Joint Fine-tuning and Conversion of Pretrained Speech and Language Models towards Linear Complexity
Mutian He, Philip N. Garner
Rethinking Graph Prompts: Unraveling the Power of Data Manipulation in Graph Neural Networks
Chenyi Zi, Bowen LIU, Xiangguo SUN et al.
Positional Embeddings in Transformer Models: Evolution from Text to Vision Domains
Abhinav Kumar, Adesh Gupta, Shivank Garg et al.
Efficient Heterogeneous Meta-Learning via Channel Shuffling Modulation
Minh Hoang, Carl Kingsford
Unsupervised Order Learning
Seon-Ho Lee, Nyeong-Ho Shin, Chang-Su Kim
Latent Trajectory Learning for Limited Timestamps under Distribution Shift over Time
Qiuhao Zeng, Changjian Shui, Long-Kai Huang et al.
A General Framework for Off-Policy Learning with Partially-Observed Reward
Rikiya Takehi, Masahiro Asami, Kosuke Kawakami et al.
Boundary constrained Gaussian processes for robust physics-informed machine learning of linear partial differential equations
David Dalton, Alan Lazarus, Hao Gao et al.
MixSATGEN: Learning Graph Mixing for SAT Instance Generation
Xinyan Chen, Yang Li, Runzhong Wang et al.
POTEC: Off-Policy Contextual Bandits for Large Action Spaces via Policy Decomposition
Yuta Saito, Jihan Yao, Thorsten Joachims
Enhancing Transferable Adversarial Attacks on Vision Transformers through Gradient Normalization Scaling and High-Frequency Adaptation
Zhiyu Zhu, Xinyi Wang, Zhibo Jin et al.
Gradual Domain Adaptation via Gradient Flow
Zhan ZHUANG, Yu Zhang, Ying Wei
Empirical Likelihood for Fair Classification
Pangpang Liu, Yichuan Zhao
ReNovo: Retrieval-Based \emph{De Novo} Mass Spectrometry Peptide Sequencing
Shaorong Chen, Jun Xia, Jingbo Zhou et al.
Conformalized Survival Analysis for General Right-Censored Data
Hen Davidov, Shai Feldman, Gil Shamai et al.
Bayesian Regularization of Latent Representation
Chukwudi Paul Obite, Zhi Chang, Keyan Wu et al.
Generating Likely Counterfactuals Using Sum-Product Networks
Jiří Němeček, Tomáš Pevný, Jakub Marecek
Meta Continual Learning Revisited: Implicitly Enhancing Online Hessian Approximation via Variance Reduction
Yichen Wu, Long-Kai Huang, Renzhen Wang et al.
Data Debugging with Shapley Importance over Machine Learning Pipelines
Bojan Karlaš, David Dao, Matteo Interlandi et al.
CLAP: Collaborative Adaptation for Patchwork Learning
Sen Cui, Abudukelimu Wuerkaixi, Weishen Pan et al.
A Lightweight Method for Tackling Unknown Participation Statistics in Federated Averaging
Shiqiang Wang, Mingyue Ji
Rethinking the symmetry-preserving circuits for constrained variational quantum algorithms
Ge Yan, Hongxu Chen, Kaisen Pan et al.
Continual Learning in the Presence of Spurious Correlations: Analyses and a Simple Baseline
Donggyu Lee, Sangwon Jung, Taesup Moon
Invariance-based Learning of Latent Dynamics
Kai Lagemann, Christian Lagemann, Sach Mukherjee
Addressing Signal Delay in Deep Reinforcement Learning
Wei Wang, Dongqi Han, Xufang Luo et al.
Revolutionizing EMCCD Denoising through a Novel Physics-Based Learning Framework for Noise Modeling
Haiyang Jiang, Tetsuichi Wazawa, Imari Sato et al.
$\mathbb{D}^2$ Pruning: Message Passing for Balancing Diversity & Difficulty in Data Pruning
Adyasha Maharana, Prateek Yadav, Mohit Bansal
Steering LLMs' Behavior with Concept Activation Vectors
Ruixuan HUANG, Shuai Wang
Learning vector fields of differential equations on manifolds with geometrically constrained operator-valued kernels
Daning Huang, Hanyang He, John Harlim et al.
DEPfold: RNA Secondary Structure Prediction as Dependency Parsing.
Ke Wang, Shay B Cohen
VQ-TR: Vector Quantized Attention for Time Series Forecasting
Kashif Rasul, Andrew Bennett, Pablo Vicente et al.
KW-Design: Pushing the Limit of Protein Design via Knowledge Refinement
Zhangyang Gao, Cheng Tan, Xingran Chen et al.
Open-Source vs Close-Source: The Context Utilization Challenge
Litu Ou
Aligning Relational Learning with Lipschitz Fairness
Yaning Jia, Chunhui Zhang, Soroush Vosoughi
Online Stabilization of Spiking Neural Networks
Yaoyu Zhu, Jianhao Ding, Tiejun Huang et al.
Variational Bayesian Pseudo-Coreset
Hyungi Lee, Seungyoo Lee, Juho Lee
Scaling up the Banded Matrix Factorization Mechanism for Large Scale Differentially Private ML
Ryan McKenna
The Value of Sensory Information to a Robot
Arjun Krishna, Edward Hu, Dinesh Jayaraman
Gyrogroup Batch Normalization
Ziheng Chen, Yue Song, Xiaojun Wu et al.
LLaMA-Adapter: Efficient Fine-tuning of Large Language Models with Zero-initialized Attention
Renrui Zhang, Jiaming Han, Chris Liu et al.
BoneMet: An Open Large-Scale Multi-Modal Murine Dataset for Breast Cancer Bone Metastasis Diagnosis and Prognosis
Tiankuo Chu, Fudong Lin, Shubo Wang et al.
Heterogeneous Personalized Federated Learning by Local-Global Updates Mixing via Convergence Rate
Meirui Jiang, Anjie Le, Xiaoxiao Li et al.
On the Humanity of Conversational AI: Evaluating the Psychological Portrayal of LLMs
Jen-tse Huang, Wenxuan Wang, Eric John Li et al.
Biologically Constrained Barrel Cortex Model Integrates Whisker Inputs and Replicates Key Brain Network Dynamics
Tianfang Zhu, Dongli Hu, Jiandong Zhou et al.
Mitigating Spurious Correlations in Zero-Shot Multimodal Models
Shenyu Lu, Junyi Chai, Xiaoqian Wang
Towards Transparent Time Series Forecasting
Krzysztof Kacprzyk, Tennison Liu, Mihaela van der Schaar
Sketch2Diagram: Generating Vector Diagrams from Hand-Drawn Sketches
Itsumi Saito, Haruto Yoshida, Keisuke Sakaguchi
Size-Generalizable RNA Structure Evaluation by Exploring Hierarchical Geometries
Zongzhao Li, Jiacheng Cen, Wenbing Huang et al.
MambaExtend: A Training-Free Approach to Improve Long Context Extension of Mamba
Seyedarmin Azizi, Souvik Kundu, Mohammad Sadeghi et al.
Robust Classification via Regression for Learning with Noisy Labels
Erik Englesson, Hossein Azizpour
An Effective Manifold-based Optimization Method for Distributionally Robust Classification
Jiawei Huang, Hu Ding
GNNBoundary: Towards Explaining Graph Neural Networks through the Lens of Decision Boundaries
Xiaoqi Wang, Han Wei Shen