Most Cited ICLR "microscopic imaging" Papers

What Do You See in Common? Learning Hierarchical Prototypes over Tree-of-Life to Discover Evolutionary Traits

Harish Babu Manogaran, M. Maruf, Arka Daw et al.

Learning Successor Features with Distributed Hebbian Temporal Memory

Evgenii Dzhivelikian, Petr Kuderov, Aleksandr Panov

L3Ms — Lagrange Large Language Models

Guneet Singh Dhillon, Xingjian Shi, Yee Whye Teh et al.

Accelerated training through iterative gradient propagation along the residual path

Erwan Fagnou, Paul Caillon, Blaise Delattre et al.

Feedback Schrödinger Bridge Matching

Panagiotis Theodoropoulos, Nikolaos Komianos, Vincent Pacelli et al.

Mind Control through Causal Inference: Predicting Clean Images from Poisoned Data

Mengxuan Hu, Zihan Guan, Yi Zeng et al.

Learning Robust Representations with Long-Term Information for Generalization in Visual Reinforcement Learning

Rui Yang, Jie Wang, Qijie Peng et al.

Proximal Mapping Loss: Understanding Loss Functions in Crowd Counting & Localization

Wei LIN, Jia Wan, Antoni Chan

Schur's Positive-Definite Network: Deep Learning in the SPD cone with structure

Can Pouliquen, Mathurin Massias, Titouan Vayer

PRDP: Progressively Refined Differentiable Physics

Kanishk Bhatia, Felix Koehler, Nils Thuerey

PolyhedronNet: Representation Learning for Polyhedra with Surface-attributed Graph

Dazhou Yu, Genpei Zhang, Liang Zhao

Learning Gain Map for Inverse Tone Mapping

yinuo liao, Yuanshen Guan, Ruikang Xu et al.

Distribution Backtracking Builds A Faster Convergence Trajectory for Diffusion Distillation

Shengyuan Zhang, Ling Yang, Zejian Li et al.

Analyzing Neural Scaling Laws in Two-Layer Networks with Power-Law Data Spectra

Roman Worschech, Bernd Rosenow

ADMM for Structured Fractional Minimization

Ganzhao Yuan

Revisiting text-to-image evaluation with Gecko: on metrics, prompts, and human rating

Olivia Wiles, Chuhan Zhang, Isabela Albuquerque et al.

Aligning Generative Denoising with Discriminative Objectives Unleashes Diffusion for Visual Perception

Ziqi Pang, Xin Xu, Yu-Xiong Wang

Bayesian Bi-clustering of Neural Spiking Activity with Latent Structures

Ganchao Wei

DyCAST: Learning Dynamic Causal Structure from Time Series

Yue Cheng, Bochen Lyu, Weiwei Xing et al.

Reinforcement Learning for Control of Non-Markovian Cellular Population Dynamics

Josiah Kratz, Jacob Adamczyk

Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making

Aliyah Hsu, Yeshwanth Cherapanamjeri, Briton Park et al.

Locally Connected Echo State Networks for Time Series Forecasting

Filip Matzner, František Mráz

Debiasing Federated Learning with Correlated Client Participation

Zhenyu Sun, Ziyang Zhang, Zheng Xu et al.

VOILA: Evaluation of MLLMs For Perceptual Understanding and Analogical Reasoning

Nilay Yilmaz, Maitreya Patel, Lawrence Luo et al.

Data Distillation for extrapolative protein design through exact preference optimization

Mostafa Karimi, Sharmi Banerjee, Tommi Jaakkola et al.

ConcreTizer: Model Inversion Attack via Occupancy Classification and Dispersion Control for 3D Point Cloud Restoration

Youngseok Kim, Sunwook Hwang, Hyung-Sin Kim et al.

SleepSMC: Ubiquitous Sleep Staging via Supervised Multimodal Coordination

Shuo Ma, Yingwei Zhang, Yiqiang Chen et al.

Training Large Language Models for Retrieval-Augmented Question Answering through Backtracking Correction

Huawen Feng, ZekunYao, Junhao Zheng et al.

Learning a Fast Mixing Exogenous Block MDP using a Single Trajectory

Alexander Levine, Peter Stone, Amy Zhang

Learning Structured Representations by Embedding Class Hierarchy with Fast Optimal Transport

Siqi Zeng, Sixian Du, Makoto Yamada et al.

Unsupervised Disentanglement of Content and Style via Variance-Invariance Constraints

Yuxuan Wu, Ziyu Wang, Bhiksha Raj et al.

Learning Randomized Algorithms with Transformers

Johannes von Oswald, Seijin Kobayashi, Yassir Akram et al.

Scale-aware Recognition in Satellite Images under Resource Constraints

Shreelekha Revankar, Cheng Perng Phoo, Utkarsh Kumar Mall et al.

ADAM Optimization with Adaptive Batch Selection

Gyu Yeol Kim, Min-hwan Oh

Entropy-based Activation Function Optimization: A Method on Searching Better Activation Functions

Haoyuan Sun, Zihao Wu, Bo Xia et al.

Adaptive Batch Size for Privately Finding Second-Order Stationary Points

Daogao Liu, Kunal Talwar

Towards Learning High-Precision Least Squares Algorithms with Sequence Models

Jerry Liu, Jessica Grogan, Owen Dugan et al.

Improving Graph Neural Networks by Learning Continuous Edge Directions

Seong Ho Pahng, Sahand Hormoz

Incremental Causal Effect for Time to Treatment Initialization

Andrew Ying, Zhichen Zhao, Ronghui Xu

Adversarial Latent Feature Augmentation for Fairness

Hoin Jung, Junyi Chai, Xiaoqian Wang

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression

Michael Crawshaw, Blake Woodworth, Mingrui Liu

R2Det: Exploring Relaxed Rotation Equivariance in 2D Object Detection

Zhiqiang Wu, Yingjie Liu, Hanlin Dong et al.

Associative memory and dead neurons

Vladimir Fanaskov, Ivan Oseledets

Linear Mode Connectivity in Differentiable Tree Ensembles

Ryuichi Kanoh, Mahito Sugiyama

Complementary Label Learning with Positive Label Guessing and Negative Label Enhancement

Yuhang Li, Zhuying Li, Yuheng Jia

Generalizability of Neural Networks Minimizing Empirical Risk Based on Expressive Power

Lijia Yu, Yibo Miao, Yifan Zhu et al.

RESfM: Robust Deep Equivariant Structure from Motion

Fadi Khatib, Yoni Kasten, Dror Moran et al.

Minimal Impact ControlNet: Advancing Multi-ControlNet Integration

Shikun Sun, Min Zhou, Zixuan Wang et al.

SAVA: Scalable Learning-Agnostic Data Valuation

Samuel Kessler, Tam Le, Vu Nguyen

Democratic Training Against Universal Adversarial Perturbations

Bing Sun, Jun Sun, Wei Zhao

Gaussian Splatting Lucas-Kanade

Liuyue Xie, Joel Julin, Koichiro Niinuma et al.

Boosting Perturbed Gradient Ascent for Last-Iterate Convergence in Games

Kenshi Abe, Mitsuki Sakamoto, Kaito Ariu et al.

The "Law'' of the Unconscious Contrastive Learner: Probabilistic Alignment of Unpaired Modalities

Yongwei Che, Benjamin Eysenbach

Event-Driven Online Vertical Federated Learning

Ganyu Wang, Boyu Wang, Bin Gu et al.

DUET: Decentralized Bilevel Optimization without Lower-Level Strong Convexity

Zhen Qin, Zhuqing Liu, Songtao Lu et al.

ELBOing Stein: Variational Bayes with Stein Mixture Inference

Ola Rønning, Eric Nalisnick, Christophe Ley et al.

Contrastive Learning from Synthetic Audio Doppelgängers

Manuel Cherep, Nikhil Singh

Exploring channel distinguishability in local neighborhoods of the model space in quantum neural networks

Sabrina Herbst, Sandeep Cranganore, Vincenzo De Maio et al.

Long-Context Linear System Identification

Oğuz Kaan Yüksel, Mathieu Even, Nicolas Flammarion

InversionGNN: A Dual Path Network for Multi-Property Molecular Optimization

Yifan Niu, Ziqi Gao, Tingyang Xu et al.

SINGER: Stochastic Network Graph Evolving Operator for High Dimensional PDEs

Mingquan Feng, Yixin Huang, Weixin Liao et al.

Neural Causal Graph for Interpretable and Intervenable Classification

Jiawei Wang, Shaofei Lu, Da Cao et al.

Learning mirror maps in policy mirror descent

Carlo Alfano, Sebastian Towers, Silvia Sapora et al.

Boosting Methods for Interval-censored Data with Regression and Classification

Yuan Bian, Grace Yi, Wenqing He

GALA: Geometry-Aware Local Adaptive Grids for Detailed 3D Generation

Dingdong Yang, Yizhi Wang, Konrad Schindler et al.

Elliptic Loss Regularization

Ali Hasan, Haoming Yang, Yuting Ng et al.

Training Robust Ensembles Requires Rethinking Lipschitz Continuity

Ali Ebrahimpour Boroojeny, Hari Sundaram, Varun Chandrasekaran

The Journey Matters: Average Parameter Count over Pre-training Unifies Sparse and Dense Scaling Laws

Tian Jin, Ahmed Imtiaz Humayun, Utku Evci et al.

Multi-agent cooperation through learning-aware policy gradients

Alexander Meulemans, Seijin Kobayashi, Johannes von Oswald et al.

Weighted Multi-Prompt Learning with Description-free Large Language Model Distillation

Sua Lee, Kyubum Shin, Jung Ho Park

Rethinking Self-Distillation: Label Averaging and Enhanced Soft Label Refinement with Partial Labels

Hyeonsu Jeong, Hye Won Chung

DLEFT-MKC: Dynamic Late Fusion Multiple Kernel Clustering with Robust Tensor Learning via Min-Max Optimization

Yi Zhang, Siwei Wang, Jiyuan Liu et al.

Conservative Contextual Bandits: Beyond Linear Representations

Rohan Deb, Mohammad Ghavamzadeh, Arindam Banerjee

Flat Minima in Linear Estimation and an Extended Gauss Markov Theorem

Simon Segert

Efficient and Trustworthy Causal Discovery with Latent Variables and Complex Relations

Xiuchuan Li, Tongliang Liu

InvestESG: A multi-agent reinforcement learning benchmark for studying climate investment as a social dilemma

Xiaoxuan Hou, Jiayi Yuan, Joel Z Leibo et al.

LiFT: Learning to Fine-Tune via Bayesian Parameter Efficient Meta Fine-Tuning

Minyoung Kim, Timothy Hospedales

MGCFNN: A Neural MultiGrid Solver with Novel Fourier Neural Network for High Wave Number Helmholtz Equations

Yan Xie, Minrui Lv, Chen-Song Zhang

Learning under Temporal Label Noise

Sujay Nagaraj, Walter Gerych, Sana Tonekaboni et al.

Revisiting Large-Scale Non-convex Distributionally Robust Optimization

Qi Zhang, Yi Zhou, Simon Khan et al.

Risk-Sensitive Variational Actor-Critic: A Model-Based Approach

Alonso Granados, Mohammadreza Ebrahimi, Jason Pacheco

Minimax Optimal Reinforcement Learning with Quasi-Optimism

Harin Lee, Min-hwan Oh

Zero-cost Proxy for Adversarial Robustness Evaluation

Yuqi Feng, Yuwei Ou, Jiahao Fan et al.

Self-supervised Monocular Depth Estimation Robust to Reflective Surface Leveraged by Triplet Mining

Wonhyeok Choi, Kyumin Hwang, Wei Peng et al.

Neural networks on Symmetric Spaces of Noncompact Type

Xuan Son Nguyen, Yang, Aymeric Histace

CR2PQ: Continuous Relative Rotary Positional Query for Dense Visual Representation Learning

Shaofeng Zhang, Qiang Zhou, Sitong Wu et al.

RAPPER: Reinforced Rationale-Prompted Paradigm for Natural Language Explanation in Visual Question Answering

Kai-Po Chang, Chi-Pin Huang, Wei-Yuan Cheng et al.

Achieving Sample and Computational Efficient Reinforcement Learning by Action Space Reduction via Grouping

Yining Li, Peizhong Ju, Ness Shroff

Benign Overfitting in Out-of-Distribution Generalization of Linear Models

Shange Tang, Jiayun Wu, Jianqing Fan et al.

Graph Neural Networks Gone Hogwild

Olga Solodova, Nick Richardson, Deniz Oktay et al.

Stochastic Bandits Robust to Adversarial Attacks

Xuchuang Wang, Maoli Liu, Jinhang Zuo et al.

Optimal Learning of Kernel Logistic Regression for Complex Classification Scenarios

Hongwei Wen, Annika Betken, Hanyuan Hang

Collapsed Language Models Promote Fairness

Jingxuan Xu, Wuyang Chen, Linyi Li et al.

Optimal Flow Transport and its Entropic Regularization: a GPU-friendly Matrix Iterative Algorithm for Flow Balance Satisfaction

Liangliang Shi, Yufeng Li, Kaipeng Zeng et al.

Finally Rank-Breaking Conquers MNL Bandits: Optimal and Efficient Algorithms for MNL Assortment

Aadirupa Saha, Pierre Gaillard

How Learnable Grids Recover Fine Detail in Low Dimensions: A Neural Tangent Kernel Analysis of Multigrid Parametric Encodings

Samuel Audia, Soheil Feizi, Matthias Zwicker et al.

Filtered not Mixed: Filtering-Based Online Gating for Mixture of Large Language Models

Raeid Saqur, Anastasis Kratsios, Florian Krach et al.

Selective Mixup Fine-Tuning for Optimizing Non-Decomposable Objectives

Shrinivas Ramasubramanian, Harsh Rangwani, Sho Takemori et al.

Generalized Behavior Learning from Diverse Demonstrations

Varshith Sreeramdass, Rohan Paleja, Letian Chen et al.

TDDBench: A Benchmark for Training data detection

Zhihao Zhu, Yi Yang, Defu Lian

Pedestrian Motion Reconstruction: A Large-scale Benchmark via Mixed Reality Rendering with Multiple Perspectives and Modalities

Yichen Wang, Yiyi Zhang, Xinhao Hu et al.

Generalized Video Moment Retrieval

Qin You, Qilong Wu, Yicong Li et al.

Understanding the Robustness of Randomized Feature Defense Against Query-Based Adversarial Attacks

Hung Quang Nguyen, Yingjie Lao, Tung Pham et al.

A Robust Method to Discover Causal or Anticausal Relation

Yu Yao, Yang Zhou, Bo Han et al.

TTVD: Towards a Geometric Framework for Test-Time Adaptation Based on Voronoi Diagram

Mingxi Lei, Chunwei Ma, Meng Ding et al.

Towards Empowerment Gain through Causal Structure Learning in Model-Based Reinforcement Learning

Hongye Cao, Fan Feng, Meng Fang et al.

SelKD: Selective Knowledge Distillation via Optimal Transport Perspective

Liangliang Shi, Zhengyan Shi, Junchi Yan

Trajectory-Class-Aware Multi-Agent Reinforcement Learning

Hyungho Na, Kwanghyeon Lee, Sumin Lee et al.

Neuron Platonic Intrinsic Representation From Dynamics Using Contrastive Learning

Wei Wu, Can Liao, Zizhen Deng et al.

Adaptive Energy Alignment for Accelerating Test-Time Adaptation

Wonjeong Choi, Do-Yeon Kim, Jungwuk Park et al.

FACTS: A Factored State-Space Framework for World Modelling

Li Nanbo, Firas Laakom, Yucheng XU et al.

Optimizing importance weighting in the presence of sub-population shifts

Floris Holstege, Bram Wouters, Noud Giersbergen et al.

Last Iterate Convergence of Incremental Methods as a Model of Forgetting

Xufeng Cai, Jelena Diakonikolas

ComLoRA: A Competitive Learning Approach for Enhancing LoRA

Qiushi Huang, Tom Ko, Lilian Tang et al.

SGD with memory: fundamental properties and stochastic acceleration

Dmitry Yarotsky, Maksim Velikanov

EvA: Erasing Spurious Correlations with Activations

Qiyuan He, Kai Xu, Angela Yao

Systems with Switching Causal Relations: A Meta-Causal Perspective

Moritz Willig, Tim Tobiasch, Florian Busch et al.

Three Mechanisms of Feature Learning in a Linear Network

Yizhou Xu, Liu Ziyin

Towards Scalable Topological Regularizers

Wong Hiu-Tung, Darrick Lee, Hong Yan

Rethinking and Extending the Probabilistic Inference Capacity of GNNs

Tuo Xu, Lei Zou

Satisficing Regret Minimization in Bandits

Qing Feng, Tianyi Ma, Ruihao Zhu

Discrete Latent Plans via Semantic Skill Abstractions

Haobin Jiang, Wang, Zongqing Lu

Centrality-guided Pre-training for Graph

Bin Liang, Shiwei Chen, Lin Gui et al.

3DIS: Depth-Driven Decoupled Image Synthesis for Universal Multi-Instance Generation

Dewei Zhou, Ji Xie, Zongxin Yang et al.

Utilitarian Algorithm Configuration for Infinite Parameter Spaces

Devon Graham, Kevin Leyton-Brown

GeoILP: A Synthetic Dataset to Guide Large-Scale Rule Induction

Si Chen, Richong Zhang, Xu Zhang

Metric-Driven Attributions for Vision Transformers

Chase Walker, Sumit Jha, Rickard Ewetz

Scalable Universal T-Cell Receptor Embeddings from Adaptive Immune Repertoires

Paidamoyo Chapfuwa, Ilker Demirel, Lorenzo Pisani et al.

Safety Representations for Safer Policy Learning

Kaustubh Mani, Vincent Mai, Charlie Gauthier et al.

Residual Kernel Policy Network: Enhancing Stability and Robustness in RKHS-Based Reinforcement Learning

Yixian Zhang, Huaze Tang, Huijing Lin et al.

Execution-guided within-prompt search for programming-by-example

Gust Verbruggen, Ashish Tiwari, Mukul Singh et al.

ToddlerDiffusion: Interactive Structured Image Generation with Cascaded Schrödinger Bridge

Eslam Abdelrahman, Liangbing Zhao, Tao Hu et al.

HADAMRNN: BINARY AND SPARSE TERNARY ORTHOGONAL RNNS

Armand Foucault, Francois Malgouyres, Franck Mamalet

Towards Explaining the Power of Constant-depth Graph Neural Networks for Structured Linear Programming

Qian Li, Minghui Ouyang, Tian Ding et al.

Beyond Random Augmentations: Pretraining with Hard Views

Fabio Ferreira, Ivo Rapant, Jörg Franke et al.

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On the Benefits of Attribute-Driven Graph Domain Adaptation

Ruiyi Fang, Bingheng Li, zhao kang et al.

Port-Hamiltonian Architectural Bias for Long-Range Propagation in Deep Graph Networks

Simon Heilig, Alessio Gravina, Alessandro Trenta et al.

From an LLM Swarm to a PDDL-empowered Hive: Planning Self-executed Instructions in a Multi-modal Jungle

Kaustubh Vyas, Damien Graux, Yijun Yang et al.

Contextual Self-paced Learning for Weakly Supervised Spatio-Temporal Video Grounding

Akash Kumar, Zsolt Kira, Yogesh S Rawat

Repurposing in AI: A Distinct Approach or an Extension of Creative Problem Solving?

Aissatou Diallo, Antonis Bikakis, Luke Dickens et al.

Compute-Optimal LLMs Provably Generalize Better with Scale

Marc Finzi, Sanyam Kapoor, Diego Granziol et al.

CodeMMLU: A Multi-Task Benchmark for Assessing Code Understanding & Reasoning Capabilities of CodeLLMs

Dung Nguyen, Thang Phan, Nam Le Hai et al.

Decoupled Subgraph Federated Learning

Javad Aliakbari, Johan Östman, Alexandre Graell i Amat

Everything, Everywhere, All at Once: Is Mechanistic Interpretability Identifiable?

Maxime Méloux, Silviu Maniu, François Portet et al.

Diffusion Bridge Implicit Models

Kaiwen Zheng, Guande He, Jianfei Chen et al.

Beyond Worst-Case Dimensionality Reduction for Sparse Vectors

Sandeep Silwal, David Woodruff, Qiuyi (Richard) Zhang

Elucidating the Preconditioning in Consistency Distillation

Kaiwen Zheng, Guande He, Jianfei Chen et al.

Improving Data Efficiency via Curating LLM-Driven Rating Systems

Jinlong Pang, Jiaheng Wei, Ankit Parag Shah et al.

Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization

Zhe Li, Bicheng Ying, Zidong Liu et al.

Chain-of-Thought Provably Enables Learning the (Otherwise) Unlearnable

Chenxiao Yang, Zhiyuan Li, David Wipf

Understanding Warmup-Stable-Decay Learning Rates: A River Valley Loss Landscape View

Kaiyue Wen, Zhiyuan Li, Jason Wang et al.

nGPT: Normalized Transformer with Representation Learning on the Hypersphere

Ilya Loshchilov, Cheng-Ping Hsieh, Simeng Sun et al.

A Coefficient Makes SVRG Effective

Yida Yin, Zhiqiu Xu, Zhiyuan Li et al.

Homomorphism Counts as Structural Encodings for Graph Learning

Linus Bao, Emily Jin, Michael Bronstein et al.

PhysPDE: Rethinking PDE Discovery and a Physical HYpothesis Selection Benchmark

Mingquan Feng, Yixin Huang, Yizhou Liu et al.

Adam Exploits $\ell_\infty$-geometry of Loss Landscape via Coordinate-wise Adaptivity

Shuo Xie, Mohamad Amin Mohamadi, Zhiyuan Li

Near-Optimal Policy Identification in Robust Constrained Markov Decision Processes via Epigraph Form

Toshinori Kitamura, Tadashi Kozuno, Wataru Kumagai et al.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression

Juno Kim, Dimitri Meunier, Arthur Gretton et al.

TC-MoE: Augmenting Mixture of Experts with Ternary Expert Choice

Shen Yan, Xingyan Bin, Sijun Zhang et al.

Remove Symmetries to Control Model Expressivity and Improve Optimization

Liu Ziyin, Yizhou Xu, Isaac Chuang

JPEG Inspired Deep Learning

Ahmed Hussien Salamah, Kaixiang Zheng, Yiwen Liu et al.

ChatQA 2: Bridging the Gap to Proprietary LLMs in Long Context and RAG Capabilities

Peng Xu, Wei Ping, Xianchao Wu et al.

gRNAde: Geometric Deep Learning for 3D RNA inverse design

Chaitanya Joshi, Arian Jamasb, Ramon Viñas et al.

Boltzmann priors for Implicit Transfer Operators

Juan Viguera Diez, Mathias Schreiner, Ola Engkvist et al.

Biologically Constrained Barrel Cortex Model Integrates Whisker Inputs and Replicates Key Brain Network Dynamics

Tianfang Zhu, Dongli Hu, Jiandong Zhou et al.

Pairwise Elimination with Instance-Dependent Guarantees for Bandits with Cost Subsidy

Ishank Juneja, Carlee Joe-Wong, Osman Yagan

In-Context Editing: Learning Knowledge from Self-Induced Distributions

Siyuan Qi, Bangcheng Yang, Kailin Jiang et al.

Towards Understanding the Universality of Transformers for Next-Token Prediction

Michael Sander, Gabriel Peyré

Learning Task Belief Similarity with Latent Dynamics for Meta-Reinforcement Learning

Menglong Zhang, Fuyuan Qian, Quanying Liu

CryoGEN: Generative Energy-based Models for Cryogenic Electron Tomography Reconstruction

Yunfei Teng, Yuxuan Ren, Kai Chen et al.

KAN: Kolmogorov–Arnold Networks

Ziming Liu, Yixuan Wang, Sachin Vaidya et al.

Online Clustering with Nearly Optimal Consistency

T-H. Hubert Chan, Shaofeng Jiang, Tianyi Wu et al.

Simplifying, Stabilizing and Scaling Continuous-time Consistency Models

Cheng Lu, Yang Song

The Geometry of Categorical and Hierarchical Concepts in Large Language Models

Kiho Park, Yo Joong Choe, Yibo Jiang et al.

Adversarial Training Can Provably Improve Robustness: Theoretical Analysis of Feature Learning Process Under Structured Data

Binghui Li, Yuanzhi Li

TRENDy: Temporal Regression of Effective Nonlinear Dynamics

Matthew Ricci, Guy Pelc, Zoe Piran et al.

Regularized Proportional Fairness Mechanism for Resource Allocation Without Money

Sujay Bhatt, Alec Koppel, Sumitra Ganesh et al.

Dynamic Neural Fortresses: An Adaptive Shield for Model Extraction Defense

Siyu Luan, Zhenyi Wang, Li Shen et al.

Protein Language Model Fitness is a Matter of Preference

Cade Gordon, Amy Lu, Pieter Abbeel

Watch Less, Do More: Implicit Skill Discovery for Video-Conditioned Policy

Wang, Zongqing Lu

Learning and aligning single-neuron invariance manifolds in visual cortex

Mohammad Bashiri, Luca Baroni, Ján Antolík et al.

From Pixels to Tokens: Byte-Pair Encoding on Quantized Visual Modalities

Wanpeng Zhang, Zilong Xie, Yicheng Feng et al.

Cross-Domain Offline Policy Adaptation with Optimal Transport and Dataset Constraint

Jiafei Lyu, Mengbei Yan, Zhongjian Qiao et al.

Robustness Inspired Graph Backdoor Defense

Zhiwei Zhang, Minhua Lin, Junjie Xu et al.

Do You Keep an Eye on What I Ask? Mitigating Multimodal Hallucination via Attention-Guided Ensemble Decoding

Yeongjae Cho, Keonwoo Kim, Taebaek Hwang et al.

Lost in Prediction: Why Social Media Narratives Don't Help Macroeconomic Forecasting?

Almog Gueta, Roi Reichart, Amir Feder et al.

Improving Probabilistic Diffusion Models With Optimal Diagonal Covariance Matching

Zijing Ou, Mingtian Zhang, Andi Zhang et al.

TetSphere Splatting: Representing High-Quality Geometry with Lagrangian Volumetric Meshes

Minghao Guo, Bohan Wang, Kaiming He et al.

Procedural Synthesis of Synthesizable Molecules

Michael Sun, Alston Lo, Minghao Guo et al.

Dynamic-SUPERB Phase-2: A Collaboratively Expanding Benchmark for Measuring the Capabilities of Spoken Language Models with 180 Tasks

Chien-yu Huang, Wei-Chih Chen, Shu-wen Yang et al.

LOIRE: LifelOng learning on Incremental data via pre-trained language model gRowth Efficiently

Xue Han, Yitong Wang, Junlan Feng et al.

Conditional Testing based on Localized Conformal $p$-values

Xiaoyang Wu, Lin Lu, Zhaojun Wang et al.

Occlusion-aware Non-Rigid Point Cloud Registration via Unsupervised Neural Deformation Correntropy

Mingyang Zhao, Gaofeng Meng, Dong-ming Yan

3DitScene: Editing Any Scene via Language-guided Disentangled Gaussian Splatting

Qihang Zhang, Yinghao Xu, Chaoyang Wang et al.

On Disentangled Training for Nonlinear Transform in Learned Image Compression

Han Li, Shaohui Li, Wenrui Dai et al.

Navigating Neural Space: Revisiting Concept Activation Vectors to Overcome Directional Divergence

Frederik Pahde, Maximilian Dreyer, Moritz Weckbecker et al.

Optimality of Matrix Mechanism on $\ell_p^p$-metric

Zongrui Zou, Jingcheng Liu, Jalaj Upadhyay

Adversarial Mixup Unlearning

Zhuoyi Peng, Yixuan Tang, Yi Yang

Time-to-Event Pretraining for 3D Medical Imaging

Zepeng Frazier Huo, Jason Fries, Alejandro Lozano et al.