Most Cited 2025 "knowledge base uncertainty" Papers
22,274 papers found • Page 65 of 112
Conference
Exact Recovery of Sparse Binary Vectors from Generalized Linear Measurements
Arya Mazumdar, Neha Sangwan
Prediction-Powered Adaptive Shrinkage Estimation
Sida Li, Nikolaos Ignatiadis
Variational Counterfactual Intervention Planning to Achieve Target Outcomes
Xin Wang, Shengfei Lyu, Luo Chi et al.
Leveraging Sparsity for Sample-Efficient Preference Learning: A Theoretical Perspective
Yunzhen Yao, Lie He, Michael Gastpar
Measuring In-Context Computation Complexity via Hidden State Prediction
Vincent Herrmann, Róbert Csordás, Jürgen Schmidhuber
POQD: Performance-Oriented Query Decomposer for Multi-vector retrieval
Yaoyang Liu, Junlin Li, Yinjun Wu et al.
Concept-Centric Token Interpretation for Vector-Quantized Generative Models
Tianze Yang, Yucheng Shi, Mengnan Du et al.
Geometric Algebra Planes: Convex Implicit Neural Volumes
Irmak Sivgin, Sara Fridovich-Keil, Gordon Wetzstein et al.
LieRE: Lie Rotational Positional Encodings
Sophie Ostmeier, Brian Axelrod, Maya Varma et al.
scSSL-Bench: Benchmarking Self-Supervised Learning for Single-Cell Data
Olga Ovcharenko, Florian Barkmann, Philip Toma et al.
Broadband Ground Motion Synthesis by Diffusion Model with Minimal Condition
Jaeheun Jung, Jaehyuk Lee, ChangHae Jung et al.
Convergence of Consistency Model with Multistep Sampling under General Data Assumptions
Yiding Chen, Yiyi Zhang, Owen Oertell et al.
Mixed-curvature decision trees and random forests
Philippe Chlenski, Quentin Chu, Raiyan Khan et al.
Learning Distribution-wise Control in Representation Space for Language Models
Deng, Ruidi Chang, Hanjie Chen
A General Graph Spectral Wavelet Convolution via Chebyshev Order Decomposition
Nian Liu, Xiaoxin He, Thomas Laurent et al.
PAC Learning with Improvements
Idan Attias, Avrim Blum, Keziah Naggita et al.
Adaptive Elicitation of Latent Information Using Natural Language
Jimmy Wang, Tom Zollo, Richard Zemel et al.
RULEBREAKERS: Challenging LLMs at the Crossroads between Formal Logic and Human-like Reasoning
Jason Chan, Robert Gaizauskas, Zhixue Zhao
Neural Graph Matching Improves Retrieval Augmented Generation in Molecular Machine Learning
Runzhong Wang, Rui-Xi Wang, Mrunali Manjrekar et al.
Heterogeneous Data Game: Characterizing the Model Competition Across Multiple Data Sources
Renzhe Xu, Kang Wang, Bo Li
Tilted Sharpness-Aware Minimization
Tian Li, Tianyi Zhou, Jeff Bilmes
Empirical Privacy Variance
Yuzheng Hu, Fan Wu, Ruicheng Xian et al.
Machine Learning meets Algebraic Combinatorics: A Suite of Datasets Capturing Research-level Conjecturing Ability in Pure Mathematics
Herman Chau, Helen Jenne, Davis Brown et al.
Position: Solve Layerwise Linear Models First to Understand Neural Dynamical Phenomena (Neural Collapse, Emergence, Lazy/Rich Regime, and Grokking)
Yoonsoo Nam, Seok Hyeong Lee, Clémentine Dominé et al.
LLM Data Selection and Utilization via Dynamic Bi-level Optimization
Yang Yu, Kai Han, Hang Zhou et al.
Uniform Mean Estimation for Heavy-Tailed Distributions via Median-of-Means
Mikael Møller Høgsgaard, Andrea Paudice
Differentiable Quadratic Optimization For the Maximum Independent Set Problem
Ismail Alkhouri, Cedric Le Denmat, Yingjie Li et al.
Latent Mamba Operator for Partial Differential Equations
Karn Tiwari, Niladri Dutta, N M Anoop Krishnan et al.
Goal-Oriented Skill Abstraction for Offline Multi-Task Reinforcement Learning
Jinmin He, Kai Li, Yifan Zang et al.
Fairness Overfitting in Machine Learning: An Information-Theoretic Perspective
Firas Laakom, Haobo Chen, Jürgen Schmidhuber et al.
Adaptive Sample Sharing for Multi Agent Linear Bandits
Hamza Cherkaoui, Merwan Barlier, Igor Colin
Prices, Bids, Values: One ML-Powered Combinatorial Auction to Rule Them All
Ermis Soumalias, Jakob Heiss, Jakob Weissteiner et al.
Multivariate Conformal Selection
Tian Bai, Yue Zhao, Xiang Yu et al.
PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs
Jianqing Zhang, Yang Liu, Jie Fu et al.
How Effective Can Dropout Be in Multiple Instance Learning ?
Wenhui Zhu, Peijie Qiu, Xiwen Chen et al.
The Importance of Being Lazy: Scaling Limits of Continual Learning
Jacopo Graldi, Alessandro Breccia, Giulia Lanzillotta et al.
Understanding Model Reprogramming for CLIP via Decoupling Visual Prompts
Chengyi Cai, Zesheng Ye, Lei Feng et al.
Stochastic Encodings for Active Feature Acquisition
Alexander Norcliffe, Changhee Lee, Fergus Imrie et al.
World Model Implanting for Test-time Adaptation of Embodied Agents
Minjong Yoo, Jinwoo Jang, Sihyung Yoon et al.
Position: All Current Generative Fidelity and Diversity Metrics are Flawed
Ossi Räisä, Boris van Breugel, Mihaela van der Schaar
No Free Lunch from Random Feature Ensembles: Scaling Laws and Near-Optimality Conditions
Benjamin Ruben, William Tong, Hamza Chaudhry et al.
Adversarial Inception Backdoor Attacks against Reinforcement Learning
Ethan Rathbun, Alina Oprea, Christopher Amato
Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity
Ningyuan Huang, Miguel Sarabia, Abhinav Moudgil et al.
Non-asymptotic Error Bounds in $\mathcal{W}_2$-Distance with Sqrt(d) Dimension Dependence and First Order Convergence for Langevin Monte Carlo beyond Log-Concavity
Bin Yang, Xiaojie Wang
SIMPLEMIX: Frustratingly Simple Mixing of Off- and On-policy Data in Language Model Preference Learning
Tianjian Li, Daniel Khashabi
FactTest: Factuality Testing in Large Language Models with Finite-Sample and Distribution-Free Guarantees
Fan Nie, Xiaotian Hou, Shuhang Lin et al.
Implicit Regularization for Tubal Tensor Factorizations via Gradient Descent
Santhosh Karnik, Anna Veselovska, Mark Iwen et al.
MoRAgent: Parameter Efficient Agent Tuning with Mixture-of-Roles
Jing Han, Binwei Yan, Tianyu Guo et al.
INRFlow: Flow Matching for INRs in Ambient Space
Yuyang Wang, Anurag Ranjan, Joshua M Susskind et al.
A Causal World Model Underlying Next Token Prediction: Exploring GPT in a Controlled Environment
Raanan Yehezkel Rohekar, Yaniv Gurwicz, Sungduk Yu et al.
OmniBal: Towards Fast Instruction-Tuning for Vision-Language Models via Omniverse Computation Balance
Yongqiang Yao, Jingru Tan, Feizhao Zhang et al.
Deep Reinforcement Learning from Hierarchical Preference Design
Alexander Bukharin, Yixiao Li, Pengcheng He et al.
Learning Representations of Instruments for Partial Identification of Treatment Effects
Jonas Schweisthal, Dennis Frauen, Maresa Schröder et al.
One Stone, Two Birds: Enhancing Adversarial Defense Through the Lens of Distributional Discrepancy
Jiacheng Zhang, Benjamin Rubinstein, Jingfeng Zhang et al.
Generalized Category Discovery via Reciprocal Learning and Class-Wise Distribution Regularization
Duo Liu, Zhiquan Tan, Linglan Zhao et al.
TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation
Ziang Zhou, Zhihao DING, Jieming Shi et al.
BOOD: Boundary-based Out-Of-Distribution Data Generation
Qilin Liao, Shuo Yang, Bo Zhao et al.
An Instrumental Value for Data Production and its Application to Data Pricing
Rui Ai, Boxiang Lyu, Zhaoran Wang et al.
Fishers for Free? Approximating the Fisher Information Matrix by Recycling the Squared Gradient Accumulator
YuXin Li, Felix Dangel, Derek Tam et al.
Making Hard Problems Easier with Custom Data Distributions and Loss Regularization: A Case Study in Modular Arithmetic
Eshika Saxena, Alberto Alfarano, Emily Wenger et al.
Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation
Da Long, Zhitong Xu, Guang Yang et al.
Generalization in Federated Learning: A Conditional Mutual Information Framework
Ziqiao Wang, Cheng Long, Yongyi Mao
Falsification of Unconfoundedness by Testing Independence of Causal Mechanisms
Rickard K.A. Karlsson, Jesse H. Krijthe
Do Not Mimic My Voice : Speaker Identity Unlearning for Zero-Shot Text-to-Speech
Taesoo Kim, Jinju Kim, Dongchan Kim et al.
PAC-Bayes Analysis for Recalibration in Classification
Masahiro Fujisawa, Futoshi Futami
Preference Learning for AI Alignment: a Causal Perspective
Katarzyna Kobalczyk, Mihaela van der Schaar
Radio: Rate–Distortion Optimization for Large Language Model Compression
Sean I. Young
Explicit Preference Optimization: No Need for an Implicit Reward Model
Xiangkun Hu, Lemin Kong, Tong He et al.
Learning multivariate Gaussians with imperfect advice
Arnab Bhattacharyya, Davin Choo, Philips George John et al.
Fully Heteroscedastic Count Regression with Deep Double Poisson Networks
Spencer Young, Porter Jenkins, Longchao Da et al.
Masked Generative Nested Transformers with Decode Time Scaling
Sahil Goyal, Debapriya Tula, Gagan Jain et al.
A Square Peg in a Square Hole: Meta-Expert for Long-Tailed Semi-Supervised Learning
Yaxin Hou, Yuheng Jia
Unisoma: A Unified Transformer-based Solver for Multi-Solid Systems
Shilong Tao, Zhe Feng, Haonan Sun et al.
Optimal Task Order for Continual Learning of Multiple Tasks
Ziyan Li, Naoki Hiratani
QuanONet: Quantum Neural Operator with Application to Differential Equation
Ruocheng Wang, Zhuo Xia, Ge Yan et al.
WildChat-50M: A Deep Dive Into the Role of Synthetic Data in Post-Training
Benjamin Feuer, Chinmay Hegde
DragSolver: A Multi-Scale Transformer for Real-World Automotive Drag Coefficient Estimation
Ye Liu, Yuntian Chen
Banyan: Improved Representation Learning with Explicit Structure
Mattia Opper, Siddharth N
Testing Conditional Mean Independence Using Generative Neural Networks
Yi Zhang, Linjun Huang, Yun Yang et al.
FlexiReID: Adaptive Mixture of Expert for Multi-Modal Person Re-Identification
Zhen Sun, Lei Tan, Yunhang Shen et al.
Sanity Checking Causal Representation Learning on a Simple Real-World System
Juan L. Gamella, Simon Bing, Jakob Runge
Unsupervised Learning for Class Distribution Mismatch
Pan Du, Zhao, Xinai Lu et al.
On the Duality between Gradient Transformations and Adapters
Lucas Torroba Hennigen, Hunter Lang, Han Guo et al.
The Limits of Tractable Marginalization
Oliver Broadrick, Sanyam Agarwal, Guy Van den Broeck et al.
Riemann Tensor Neural Networks: Learning Conservative Systems with Physics-Constrained Networks
Anas Jnini, Lorenzo Breschi, Flavio Vella
On the Dynamic Regret of Following the Regularized Leader: Optimism with History Pruning
Naram Mhaisen, George Iosifidis
Tensor-Var: Efficient Four-Dimensional Variational Data Assimilation
Yiming Yang, Xiaoyuan Cheng, Daniel Giles et al.
Representation Surgery in Model Merging with Probabilistic Modeling
Qi Wei, Shuo He, Enneng Yang et al.
MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition
Sungnyun Kim, Kangwook Jang, Sangmin Bae et al.
Low-Dimension-to-High-Dimension Generalization and Its Implications for Length Generalization
Yang Chen, Long Yang, Yitao Liang et al.
A Near-Optimal Single-Loop Stochastic Algorithm for Convex Finite-Sum Coupled Compositional Optimization
Bokun Wang, Tianbao Yang
From Jack of All Trades to Master of One: Specializing LLM-based Autoraters to a Test Set
Mara Finkelstein, Daniel Deutsch, Parker Riley et al.
Pareto-frontier Entropy Search with Variational Lower Bound Maximization
Masanori Ishikura, Masayuki Karasuyama
When to retrain a machine learning model
Florence Regol, Leo Schwinn, Kyle Sprague et al.
Curriculum Learning for Biological Sequence Prediction: The Case of De Novo Peptide Sequencing
Xiang Zhang, Jiaqi Wei, Zijie Qiu et al.
UniSim: A Unified Simulator for Time-Coarsened Dynamics of Biomolecules
Ziyang Yu, Wenbing Huang, Yang Liu
Improving Continual Learning Performance and Efficiency with Auxiliary Classifiers
Filip Szatkowski, Yaoyue Zheng, Fei Yang et al.
Aequa: Fair Model Rewards in Collaborative Learning via Slimmable Networks
Nurbek Tastan, Samuel Horváth, Karthik Nandakumar
Non-stationary Online Learning for Curved Losses: Improved Dynamic Regret via Mixability
Yu-Jie Zhang, Peng Zhao, Masashi Sugiyama
Stochastic Poisson Surface Reconstruction with One Solve using Geometric Gaussian Processes
Sidhanth Holalkere, David S Bindel, Silvia Sellán et al.
Directly Forecasting Belief for Reinforcement Learning with Delays
Qingyuan Wu, Yuhui Wang, Simon Zhan et al.
Fast Inference with Kronecker-Sparse Matrices
Antoine Gonon, Léon Zheng, Pascal Carrivain et al.
Model Steering: Learning with a Reference Model Improves Generalization Bounds and Scaling Laws
Xiyuan Wei, Ming Lin, Fanjiang Ye et al.
Learning with Selectively Labeled Data from Multiple Decision-makers
Jian Chen, Zhehao Li, Xiaojie Mao
Explanatory Instructions: Towards Unified Vision Tasks Understanding and Zero-shot Generalization
Yang Shen, Xiu-Shen Wei, Yifan Sun et al.
Inducing, Detecting and Characterising Neural Modules: A Pipeline for Functional Interpretability in Reinforcement Learning
Anna Soligo, Pietro Ferraro, David Boyle
Score Matching with Missing Data
Josh Givens, Song Liu, Henry Reeve
The Value of Prediction in Identifying the Worst-Off
Unai Fischer Abaigar, Christoph Kern, Juan Perdomo
Sassha: Sharpness-aware Adaptive Second-order Optimization with Stable Hessian Approximation
Dahun Shin, Dongyeop Lee, Jinseok Chung et al.
Compositional Causal Reasoning Evaluation in Language Models
Jacqueline Maasch, Alihan Hüyük, Xinnuo Xu et al.
IL-SOAR : Imitation Learning with Soft Optimistic Actor cRitic
Stefano Viel, Luca Viano, Volkan Cevher
Confidential Guardian: Cryptographically Prohibiting the Abuse of Model Abstention
Stephan Rabanser, Ali Shahin Shamsabadi, Olive Franzese et al.
Learning Time-Varying Multi-Region Brain Communications via Scalable Markovian Gaussian Processes
Weihan Li, Yule Wang, Chengrui Li et al.
Understanding the Statistical Accuracy-Communication Trade-off in Personalized Federated Learning with Minimax Guarantees
Xin Yu, Zelin He, Ying Sun et al.
Soup-of-Experts: Pretraining Specialist Models via Parameters Averaging
Pierre Ablin, Angelos Katharopoulos, Skyler Seto et al.
Discovering Global False Negatives On the Fly for Self-supervised Contrastive Learning
Vicente Balmaseda, Bokun Wang, Lin et al.
Deep Bayesian Filter for Bayes-Faithful Data Assimilation
Yuta Tarumi, Keisuke Fukuda, Shin-ichi Maeda
Improving the Variance of Differentially Private Randomized Experiments through Clustering
Adel Javanmard, Vahab Mirrokni, Jean Pouget-Abadie
The Butterfly Effect: Neural Network Training Trajectories Are Highly Sensitive to Initial Conditions
Gül Sena Altıntaş, Devin Kwok, Colin Raffel et al.
Counting in Small Transformers: The Delicate Interplay between Attention and Feed-Forward Layers
Freya Behrens, Luca Biggio, Lenka Zdeborová
FuseUNet: A Multi-Scale Feature Fusion Method for U-like Networks
Quansong He, Xiangde Min, Kaishen Wang et al.
Accelerating Spectral Clustering under Fairness Constraints
Francesco Tonin, Alex Lambert, Johan Suykens et al.
Two Tickets are Better than One: Fair and Accurate Hiring Under Strategic LLM Manipulations
Lee Cohen, Connie Hong, Jack Hsieh et al.
AuPair: Golden Example Pairs for Code Repair
Aditi Mavalankar, Hassan Mansoor, Zita Marinho et al.
Improving Consistency Models with Generator-Augmented Flows
Thibaut Issenhuth, Sangchul Lee, Ludovic Dos Santos et al.
The Noisy Laplacian: a Threshold Phenomenon for Non-Linear Dimension Reduction
Alex Kokot, Octavian-Vlad Murad, Marina Meila
Unveiling Markov heads in Pretrained Language Models for Offline Reinforcement Learning
Wenhao Zhao, Qiushui Xu, Linjie Xu et al.
Imitation Learning from a Single Temporally Misaligned Video
William Huey, Yuki (Huaxiaoyue) Wang, Anne Wu et al.
Average Certified Radius is a Poor Metric for Randomized Smoothing
Chenhao Sun, Yuhao Mao, Mark Müller et al.
Exploring Large Action Sets with Hyperspherical Embeddings using von Mises-Fisher Sampling
Walid Bendada, Guillaume Salha-Galvan, Romain Hennequin et al.
Preference Adaptive and Sequential Text-to-Image Generation
Ofir Nabati, Guy Tennenholtz, Chih-wei Hsu et al.
Statistical Query Hardness of Multiclass Linear Classification with Random Classification Noise
Ilias Diakonikolas, Mingchen Ma, Lisheng Ren et al.
Designing Cyclic Peptides via Harmonic SDE with Atom-Bond Modeling
Xiangxin Zhou, Mingyu Li, xiao yi et al.
Topological Signatures of Adversaries in Multimodal Alignments
Minh Vu, Geigh Zollicoffer, Huy Mai et al.
Overcoming Vocabulary Mismatch: Vocabulary-agnostic Teacher Guided Language Modeling
Haebin Shin, Lei Ji, Xiao Liu et al.
Quantum Speedups in Regret Analysis of Infinite Horizon Average-Reward Markov Decision Processes
Bhargav Ganguly, Yang Xu, Vaneet Aggarwal
Teaching Physical Awareness to LLMs through Sounds
Weiguo Wang, Andy Nie, Wenrui Zhou et al.
MoMa: Modulating Mamba for Adapting Image Foundation Models to Video Recognition
Yuhuan Yang, Chaofan Ma, Zhenjie Mao et al.
Can We Predict Performance of Large Models across Vision-Language Tasks?
Qinyu Zhao, Ming Xu, Kartik Gupta et al.
Clustering via Self-Supervised Diffusion
Roy Uziel, Irit Chelly, Oren Freifeld et al.
Ab Initio Nonparametric Variable Selection for Scalable Symbolic Regression with Large $p$
Shengbin Ye, Meng Li
Improving Memory Efficiency for Training KANs via Meta Learning
Zhangchi Zhao, Jun Shu, Deyu Meng et al.
All-atom inverse protein folding through discrete flow matching
Kai Yi, Kiarash Jamali, Sjors Scheres
Progressively Label Enhancement for Large Language Model Alignment
Biao Liu, Ning Xu, Xin Geng
Graph-Assisted Stitching for Offline Hierarchical Reinforcement Learning
Seungho Baek, Taegeon Park, Jongchan Park et al.
Sample-specific Noise Injection for Diffusion-based Adversarial Purification
Yuhao Sun, Jiacheng Zhang, Zesheng Ye et al.
The Synergy of LLMs & RL Unlocks Offline Learning of Generalizable Language-Conditioned Policies with Low-fidelity Data
Thomas Pouplin, Katarzyna Kobalczyk, Hao Sun et al.
Learning to Stop: Deep Learning for Mean Field Optimal Stopping
Lorenzo Magnino, Yuchen Zhu, Mathieu Lauriere
Learning without Isolation: Pathway Protection for Continual Learning
Zhikang Chen, Abudukelimu Wuerkaixi, Sen Cui et al.
Conformal Prediction with Cellwise Outliers: A Detect-then-Impute Approach
Qian Peng, Yajie Bao, Haojie Ren et al.
Scaffold with Stochastic Gradients: New Analysis with Linear Speed-Up
Paul Mangold, Alain Oliviero Durmus, Aymeric Dieuleveut et al.
Polynomial Time Learning Augmented Algorithms for NP-hard Permutation Problems
Evripidis Bampis, Bruno Escoffier, Dimitris Fotakis et al.
SPHINX: Structural Prediction using Hypergraph Inference Network
Iulia Duta, Pietro Lió
Understanding Overadaptation in Supervised Fine-Tuning: The Role of Ensemble Methods
Yifan HAO, xingyuan pan, Hanning Zhang et al.
Test-Time Multimodal Backdoor Detection by Contrastive Prompting
Yuwei Niu, Shuo He, Qi Wei et al.
Hierarchical Reinforcement Learning with Uncertainty-Guided Diffusional Subgoals
Vivienne Huiling Wang, Tinghuai Wang, Joni Pajarinen
Emergence and Effectiveness of Task Vectors in In-Context Learning: An Encoder Decoder Perspective
Seungwook Han, Jinyeop Song, Jeff Gore et al.
Overcoming Spurious Solutions in Semi-Dual Neural Optimal Transport: A Smoothing Approach for Learning the Optimal Transport Plan
Jaemoo Choi, Jaewoong Choi, Dohyun Kwon
An Entropy-Based Model for Hierarchical Learning
Amir R. Asadi
CostFilter-AD: Enhancing Anomaly Detection through Matching Cost Filtering
Zhe Zhang, Mingxiu Cai, Hanxiao Wang et al.
Flexibility-conditioned protein structure design with flow matching
Vsevolod Viliuga, Leif Seute, Nicolas Wolf et al.
Heavy-Tailed Linear Bandits: Huber Regression with One-Pass Update
Jing Wang, Yu-Jie Zhang, Peng Zhao et al.
TeLoGraF: Temporal Logic Planning via Graph-encoded Flow Matching
Yue Meng, Chuchu Fan
Towards the Causal Complete Cause of Multi-Modal Representation Learning
Jingyao Wang, Siyu Zhao, Wenwen Qiang et al.
Robust ML Auditing using Prior Knowledge
Jade Garcia Bourrée, Augustin Godinot, Sayan Biswas et al.
Exogenous Isomorphism for Counterfactual Identifiability
Yikang Chen, Dehui du
Learning from others' mistakes: Finetuning machine translation models with span-level error annotations
Lily Zhang, Hamid Dadkhahi, Mara Finkelstein et al.
Strategic A/B testing via Maximum Probability-driven Two-armed Bandit
Yu Zhang, Shanshan Zhao, Bokui Wan et al.
Optimal Sensor Scheduling and Selection for Continuous-Discrete Kalman Filtering with Auxiliary Dynamics
Mohamad Al Ahdab, john leth, Zheng-Hua Tan
LapSum - One Method to Differentiate Them All: Ranking, Sorting and Top-k Selection
Łukasz Struski, Michal Bednarczyk, Igor Podolak et al.
FIC-TSC: Learning Time Series Classification with Fisher Information Constraint
Xiwen Chen, Wenhui Zhu, Peijie Qiu et al.
Flow-of-Options: Diversified and Improved LLM Reasoning by Thinking Through Options
Lakshmi Nair, Ian Trase, J. Kim
TAROT: Targeted Data Selection via Optimal Transport
Lan Feng, Fan Nie, Yuejiang Liu et al.
Layer-wise Alignment: Examining Safety Alignment Across Image Encoder Layers in Vision Language Models
Saketh Bachu, Erfan Shayegani, Rohit Lal et al.
Occult: Optimizing Collaborative Communications across Experts for Accelerated Parallel MoE Training and Inference
Shuqing Luo, Pingzhi Li, Jie Peng et al.
LRA-QViT: Integrating Low-Rank Approximation and Quantization for Robust and Efficient Vision Transformers
Beom Jin Kang, NamJoon Kim, Hyun Kim
WATCH: Adaptive Monitoring for AI Deployments via Weighted-Conformal Martingales
Drew Prinster, Xing Han, Anqi Liu et al.
Upcycling Text-to-Image Diffusion Models for Multi-Task Capabilities
Ruchika Chavhan, Abhinav Mehrotra, Malcolm Chadwick et al.
A Variational Framework for Improving Naturalness in Generative Spoken Language Models
Li-Wei Chen, Takuya Higuchi, Zakaria Aldeneh et al.
Position: In-House Evaluation Is Not Enough. Towards Robust Third-Party Evaluation and Flaw Disclosure for General-Purpose AI
Shayne Longpre, Kevin Klyman, Ruth Elisabeth Appel et al.
CoMemo: LVLMs Need Image Context with Image Memory
Shi Liu, Weijie Su, Xizhou Zhu et al.
Deep Ridgelet Transform and Unified Universality Theorem for Deep and Shallow Joint-Group-Equivariant Machines
Sho Sonoda, Yuka Hashimoto, Isao Ishikawa et al.
Tackling Dimensional Collapse toward Comprehensive Universal Domain Adaptation
Hung-Chieh Fang, Po-Yi Lu, Hsuan-Tien (Tien) Lin
SMART-PC: Skeletal Model Adaptation for Robust Test-Time Training in Point Clouds
Ali Bahri, Moslem Yazdanpanah, Sahar Dastani Oghani et al.
Optimal Transfer Learning for Missing Not-at-Random Matrix Completion
Akhil Jalan, Yassir Jedra, Arya Mazumdar et al.
Enhancing Treatment Effect Estimation via Active Learning: A Counterfactual Covering Perspective
Hechuan Wen, Tong Chen, Mingming Gong et al.
A Unified Framework for Entropy Search and Expected Improvement in Bayesian Optimization
Nuojin Cheng, Leonard Papenmeier, Stephen Becker et al.
Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals
Junyan Liu, ARNAB MAITI, Artin Tajdini et al.
Identifying biological perturbation targets through causal differential networks
Menghua Wu, Umesh Padia, Sean Murphy et al.
RestoreGrad: Signal Restoration Using Conditional Denoising Diffusion Models with Jointly Learned Prior
Ching-Hua Lee, Chouchang Yang, Jaejin Cho et al.
Differentially Private Space-Efficient Algorithms for Counting Distinct Elements in the Turnstile Model
Rachel Cummings, Alessandro Epasto, Jieming Mao et al.
A Theory for Conditional Generative Modeling on Multiple Data Sources
Rongzhen Wang, Yan Zhang, Chenyu Zheng et al.
Edge-Colored Clustering in Hypergraphs: Beyond Minimizing Unsatisfied Edges
Alex Crane, Thomas Stanley, Blair D. Sullivan et al.
Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering and Manipulating Human Perceptual Variability
Chen Wei, Chi Zhang, Jiachen Zou et al.
A Rescaling-Invariant Lipschitz Bound Based on Path-Metrics for Modern ReLU Network Parameterizations
Antoine Gonon, Nicolas Brisebarre, Elisa Riccietti et al.
Learning Latent Graph Structures and their Uncertainty
Alessandro Manenti, Daniele Zambon, Cesare Alippi
Super Deep Contrastive Information Bottleneck for Multi-modal Clustering
Zhengzheng Lou, Ke Zhang, Yucong Wu et al.
ConText: Driving In-context Learning for Text Removal and Segmentation
Fei Zhang, Pei Zhang, Baosong Yang et al.
Finite-Time Analysis of Discrete-Time Stochastic Interpolants
Yuhao Liu, Yu Chen, Rui Hu et al.
Large Continual Instruction Assistant
Jingyang Qiao, zhizhong zhang, Xin Tan et al.