Most Cited ICLR "dialog systems" Papers
6,124 papers found • Page 26 of 31
Conference
Robust Root Cause Diagnosis using In-Distribution Interventions
Lokesh Nagalapatti, Ashutosh Srivastava, Sunita Sarawagi et al.
DynAlign: Unsupervised Dynamic Taxonomy Alignment for Cross-Domain Segmentation
HAN SUN, Rui Gong, Ismail Nejjar et al.
L3Ms — Lagrange Large Language Models
Guneet Singh Dhillon, Xingjian Shi, Yee Whye Teh et al.
Intelligent Switching for Reset-Free RL
Darshan Patil, Janarthanan Rajendran, Glen Berseth et al.
DOCS: Quantifying Weight Similarity for Deeper Insights into Large Language Models
Zeping Min, Xinshang Wang
Event-Driven Online Vertical Federated Learning
Ganyu Wang, Boyu Wang, Bin Gu et al.
Robust Representation Consistency Model via Contrastive Denoising
jiachen lei, Julius Berner, Jiongxiao Wang et al.
Robustness Reprogramming for Representation Learning
Zhichao Hou, MohamadAli Torkamani, Hamid Krim et al.
Scale-aware Recognition in Satellite Images under Resource Constraints
Shreelekha Revankar, Cheng Perng Phoo, Utkarsh Kumar Mall et al.
The Journey Matters: Average Parameter Count over Pre-training Unifies Sparse and Dense Scaling Laws
Tian Jin, Ahmed Imtiaz Humayun, Utku Evci et al.
Alchemy: Amplifying Theorem-Proving Capability Through Symbolic Mutation
Shaonan Wu, Shuai Lu, Yeyun Gong et al.
Generalized Video Moment Retrieval
Qin You, Qilong Wu, Yicong Li et al.
Trajectory-Class-Aware Multi-Agent Reinforcement Learning
Hyungho Na, Kwanghyeon Lee, Sumin Lee et al.
ComLoRA: A Competitive Learning Approach for Enhancing LoRA
Qiushi Huang, Tom Ko, Lilian Tang et al.
Revisiting Large-Scale Non-convex Distributionally Robust Optimization
Qi Zhang, Yi Zhou, Simon Khan et al.
Centrality-guided Pre-training for Graph
Bin Liang, Shiwei Chen, Lin Gui et al.
Metric-Driven Attributions for Vision Transformers
Chase Walker, Sumit Jha, Rickard Ewetz
Execution-guided within-prompt search for programming-by-example
Gust Verbruggen, Ashish Tiwari, Mukul Singh et al.
Towards Explaining the Power of Constant-depth Graph Neural Networks for Structured Linear Programming
Qian Li, Minghui Ouyang, Tian Ding et al.
Beyond single neurons: population response geometry in digital twins of mouse visual cortex
Dario Liscai, Emanuele Luconi, Alessandro Marin Vargas et al.
Interactive Adjustment for Human Trajectory Prediction with Individual Feedback
Jianhua Sun, Yuxuan Li, Liang Chai et al.
Predicate Hierarchies Improve Few-Shot State Classification
Emily Jin, Joy Hsu, Jiajun Wu
Node Similarities under Random Projections: Limits and Pathological Cases
Tvrtko Tadić, Cassiano O Becker, Jennifer Neville
A Large-scale Training Paradigm for Graph Generative Models
Yu Wang, Ryan Rossi, Namyong Park et al.
Learning Conditional Invariances through Non-Commutativity
Abhra Chaudhuri, Serban Georgescu, Anjan Dutta
Decoupled Finetuning for Domain Generalizable Semantic Segmentation
Jaehyun Pahk, Donghyeon Kwon, Seong Joon Oh et al.
SINGER: Stochastic Network Graph Evolving Operator for High Dimensional PDEs
Mingquan Feng, Yixin Huang, Weixin Liao et al.
Selective Mixup Fine-Tuning for Optimizing Non-Decomposable Objectives
Shrinivas Ramasubramanian, Harsh Rangwani, Sho Takemori et al.
RECAST: Reparameterized, Compact weight Adaptation for Sequential Tasks
Nazia Tasnim, Bryan Plummer
PRDP: Progressively Refined Differentiable Physics
Kanishk Bhatia, Felix Koehler, Nils Thuerey
Local Graph Clustering with Noisy Labels
Artur Back de Luca, Kimon Fountoulakis, Shenghao Yang
Multimodal Unsupervised Domain Generalization by Retrieving Across the Modality Gap
Christopher Liao, Christian So, Theodoros Tsiligkaridis et al.
CoMRes: Semi-Supervised Time Series Forecasting Utilizing Consensus Promotion of Multi-Resolution
Yunju Cho, Jay-Yoon Lee
MixMax: Distributional Robustness in Function Space via Optimal Data Mixtures
Anvith Thudi, Chris Maddison
On the Price of Differential Privacy for Hierarchical Clustering
Chengyuan Deng, Jie Gao, Jalaj Upadhyay et al.
Towards Unbiased Calibration using Meta-Regularization
Jacek Golebiowski, Cheng Wang
Iterative Substructure Extraction for Molecular Relational Learning with Interactive Graph Information Bottleneck
Shuai Zhang, Junfeng Fang, Xuqiang Li et al.
Demystifying the Token Dynamics of Deep Selective State Space Models
Thieu Vo, Duy-Tung Pham, Xin Tong et al.
GPromptShield: Elevating Resilience in Graph Prompt Tuning Against Adversarial Attacks
Shuhan Song, Ping Li, Ming Dun et al.
Gaussian Splatting Lucas-Kanade
Liuyue Xie, Joel Julin, Koichiro Niinuma et al.
PolyhedronNet: Representation Learning for Polyhedra with Surface-attributed Graph
Dazhou Yu, Genpei Zhang, Liang Zhao
Learning Successor Features with Distributed Hebbian Temporal Memory
Evgenii Dzhivelikian, Petr Kuderov, Aleksandr Panov
Capability Localization: Capabilities Can be Localized rather than Individual Knowledge
Xiusheng Huang, Jiaxiang Liu, Yequan Wang et al.
Stochastic variance-reduced Gaussian variational inference on the Bures-Wasserstein manifold
Hoang Phuc Hau Luu, Hanlin Yu, Bernardo Williams et al.
EDiT: A Local-SGD-Based Efficient Distributed Training Method for Large Language Models
Jialiang Cheng, Ning Gao, Yun Yue et al.
GETS: Ensemble Temperature Scaling for Calibration in Graph Neural Networks
Dingyi Zhuang, Chonghe Jiang, Yunhan Zheng et al.
Scale-Free Graph-Language Models
Jianglin Lu, Yixuan Liu, Yitian Zhang et al.
On Rollouts in Model-Based Reinforcement Learning
Bernd Frauenknecht, Devdutt Subhasish, Friedrich Solowjow et al.
Towards Learning High-Precision Least Squares Algorithms with Sequence Models
Jerry Liu, Jessica Grogan, Owen Dugan et al.
Scalable Decentralized Learning with Teleportation
Yuki Takezawa, Sebastian Stich
Real-time design of architectural structures with differentiable mechanics and neural networks
Rafael Pastrana, Eder Medina, Isabel M. de Oliveira et al.
NRGBoost: Energy-Based Generative Boosted Trees
João Bravo
GraphBridge: Towards Arbitrary Transfer Learning in GNNs
Li Ju, Xingyi Yang, Qi Li et al.
PFGuard: A Generative Framework with Privacy and Fairness Safeguards
Soyeon Kim, Yuji Roh, Geon Heo et al.
SGD with memory: fundamental properties and stochastic acceleration
Dmitry Yarotsky, Maksim Velikanov
Risk-Sensitive Variational Actor-Critic: A Model-Based Approach
Alonso Granados, Mohammadreza Ebrahimi, Jason Pacheco
Performance Gaps in Multi-view Clustering under the Nested Matrix-Tensor Model
Hugo Lebeau, Mohamed El Amine Seddik, José Henrique Goulart
Efficient and Trustworthy Causal Discovery with Latent Variables and Complex Relations
Xiuchuan Li, Tongliang Liu
Compositional Conservatism: A Transductive Approach in Offline Reinforcement Learning
Yeda Song, Dongwook Lee, Gunhee Kim
Ito Diffusion Approximation of Universal Ito Chains for Sampling, Optimization and Boosting
Aleksei Ustimenko, Aleksandr Beznosikov
Can Generative AI Solve Your In-Context Learning Problem? A Martingale Perspective
Andrew Jesson, Nicolas Beltran-Velez, David Blei
MuseGNN: Forming Scalable, Convergent GNN Layers that Minimize a Sampling-Based Energy
Haitian Jiang, Renjie Liu, Zengfeng Huang et al.
Data Distillation for extrapolative protein design through exact preference optimization
Mostafa Karimi, Sharmi Banerjee, Tommi Jaakkola et al.
Causal Identification for Complex Functional Longitudinal Studies
Andrew Ying
P2Seg: Pointly-supervised Segmentation via Mutual Distillation
Zipeng Wang, Xuehui Yu, Xumeng Han et al.
Robust Model Based Reinforcement Learning Using $\mathcal{L}_1$ Adaptive Control
Minjun Sung, Sambhu Harimanas Karumanchi, Aditya Gahlawat et al.
Reinforcement Learning for Control of Non-Markovian Cellular Population Dynamics
Josiah Kratz, Jacob Adamczyk
Linear Mode Connectivity in Differentiable Tree Ensembles
Ryuichi Kanoh, Mahito Sugiyama
Generalizing Weisfeiler-Lehman Kernels to Subgraphs
Dongkwan Kim, Alice Oh
Aux-NAS: Exploiting Auxiliary Labels with Negligibly Extra Inference Cost
Yuan Gao, WEIZHONG ZHANG, Wenhan Luo et al.
SWEb: A Large Web Dataset for the Scandinavian Languages
Tobias Norlund, Tim Isbister, Amaru Cuba Gyllensten et al.
Inverse decision-making using neural amortized Bayesian actors
Dominik Straub, Tobias Fabian Niehues, Jan Peters et al.
Generating Less Certain Adversarial Examples Improves Robust Generalization
Minxing Zhang, Michael Backes, Xiao Zhang
SFESS: Score Function Estimators for $k$-Subset Sampling
Klas Wijk, Ricardo Vinuesa, Hossein Azizpour
Scale-Aware Contrastive Reverse Distillation for Unsupervised Medical Anomaly Detection
Chunlei Li, Yilei Shi, Jingliang Hu et al.
Optimizing 4D Gaussians for Dynamic Scene Video from Single Landscape Images
In-Hwan Jin, Haesoo Choo, Seong-Hun Jeong et al.
A Causal Lens for Learning Long-term Fair Policies
Jacob Lear, Lu Zhang
NfgTransformer: Equivariant Representation Learning for Normal-form Games
SIQI LIU, Luke Marris, Georgios Piliouras et al.
Near-optimal Active Regression of Single-Index Models
Yi Li, Wai Ming Tai
R2Det: Exploring Relaxed Rotation Equivariance in 2D Object Detection
Zhiqiang Wu, Yingjie Liu, Hanlin Dong et al.
Attention-based Iterative Decomposition for Tensor Product Representation
Taewon Park, inchul choi, Minho Lee
LocoVR: Multiuser Indoor Locomotion Dataset in Virtual Reality
Kojiro Takeyama, Yimeng Liu, Misha Sra
Bayesian Bi-clustering of Neural Spiking Activity with Latent Structures
Ganchao Wei
LiFT: Learning to Fine-Tune via Bayesian Parameter Efficient Meta Fine-Tuning
Minyoung Kim, Timothy Hospedales
URLOST: Unsupervised Representation Learning without Stationarity or Topology
Zeyu Yun, Juexiao Zhang, Yann LeCun et al.
3DIS: Depth-Driven Decoupled Image Synthesis for Universal Multi-Instance Generation
Dewei Zhou, Ji Xie, Zongxin Yang et al.
CLDyB: Towards Dynamic Benchmarking for Continual Learning with Pre-trained Models
Shengzhuang Chen, Yikai Liao, Xiaoxiao Sun et al.
Can We Ignore Labels in Out of Distribution Detection?
Hong Yang, Qi Yu, Travis Desell
Schur's Positive-Definite Network: Deep Learning in the SPD cone with structure
Can Pouliquen, Mathurin Massias, Titouan Vayer
Risk-Sensitive Diffusion: Robustly Optimizing Diffusion Models with Noisy Samples
Yangming Li, Max Ruiz Luyten, Mihaela van der Schaar
Strength Estimation and Human-Like Strength Adjustment in Games
Chun Jung Chen, Chung-Chin Shih, Ti-Rong Wu
Object-Centric Pretraining via Target Encoder Bootstrapping
Nikola Đukić, Tim Lebailly, Tinne Tuytelaars
PT-T2I/V: An Efficient Proxy-Tokenized Diffusion Transformer for Text-to-Image/Video-Task
Jing Wang, Ao Ma, Jiasong Feng et al.
Generative Adversarial Ranking Nets
Yinghua Yao, Yuangang Pan, Jing Li et al.
When GNNs meet symmetry in ILPs: an orbit-based feature augmentation approach
Qian Chen, Lei Li, Qian Li et al.
Towards Scalable Topological Regularizers
Wong Hiu-Tung, Darrick Lee, Hong Yan
Systems with Switching Causal Relations: A Meta-Causal Perspective
Moritz Willig, Tim Tobiasch, Florian Busch et al.
Amortized Network Intervention to Steer the Excitatory Point Processes
Zitao Song, Wendi Ren, Shuang Li
Optimal Learning of Kernel Logistic Regression for Complex Classification Scenarios
Hongwei Wen, Annika Betken, Hanyuan Hang
Zero-cost Proxy for Adversarial Robustness Evaluation
Yuqi Feng, Yuwei Ou, Jiahao Fan et al.
VONet: Unsupervised Video Object Learning With Parallel U-Net Attention and Object-wise Sequential VAE
Haonan Yu, Wei Xu
A representation-learning game for classes of prediction tasks
Neria Uzan, Nir Weinberger
Residual Kernel Policy Network: Enhancing Stability and Robustness in RKHS-Based Reinforcement Learning
Yixian Zhang, Huaze Tang, Huijing Lin et al.
Efficient Off-Policy Learning for High-Dimensional Action Spaces
Fabian Otto, Philipp Becker, Vien A Ngo 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.
Semantix: An Energy-guided Sampler for Semantic Style Transfer
Huiang He, Minghui HU, Chuanxia Zheng et al.
Doubly robust identification of treatment effects from multiple environments
Piersilvio De Bartolomeis, Julia Kostin, Javier Abad et al.
RESfM: Robust Deep Equivariant Structure from Motion
Fadi Khatib, Yoni Kasten, Dror Moran et al.
Learning Robust Representations with Long-Term Information for Generalization in Visual Reinforcement Learning
Rui Yang, Jie Wang, Qijie Peng et al.
Improved Diffusion-based Generative Model with Better Adversarial Robustness
Zekun Wang, Mingyang Yi, Shuchen Xue et al.
Regret Bounds for Episodic Risk-Sensitive Linear Quadratic Regulator
Wenhao Xu, Xuefeng Gao, Xuedong He
Improving Graph Neural Networks by Learning Continuous Edge Directions
Seong Ho Pahng, Sahand Hormoz
Separation Power of Equivariant Neural Networks
Marco Pacini, Xiaowen Dong, Bruno Lepri et al.
Last Iterate Convergence of Incremental Methods as a Model of Forgetting
Xufeng Cai, Jelena Diakonikolas
Strong Preferences Affect the Robustness of Preference Models and Value Alignment
Ziwei Xu, Mohan Kankanhalli
Balanced Ranking with Relative Centrality: A multi-core periphery perspective
Chandra Sekhar Mukherjee, Jiapeng Zhang
Clique Number Estimation via Differentiable Functions of Adjacency Matrix Permutations
Indradyumna Roy, Eeshaan Jain, Soumen Chakrabarti et al.
Adaptive Rank Allocation: Speeding Up Modern Transformers with RaNA Adapters
Roberto Garcia, Jerry Liu, Daniel Sorvisto et al.
MCNC: Manifold-Constrained Reparameterization for Neural Compression
Chayne Thrash, Reed Andreas, Ali Abbasi et al.
Associative memory and dead neurons
Vladimir Fanaskov, Ivan Oseledets
Locally Connected Echo State Networks for Time Series Forecasting
Filip Matzner, František Mráz
Generalization and Distributed Learning of GFlowNets
Tiago Silva, Amauri Souza, Omar Rivasplata et al.
High-Dynamic Radar Sequence Prediction for Weather Nowcasting Using Spatiotemporal Coherent Gaussian Representation
Ziye Wang, Yiran Qin, Lin Zeng et al.
Feedback Schrödinger Bridge Matching
Panagiotis Theodoropoulos, Nikolaos Komianos, Vincent Pacelli et al.
Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift
Zhen Zhang, Xin Liu, Shaoli Wang et al.
HADAMRNN: BINARY AND SPARSE TERNARY ORTHOGONAL RNNS
Armand Foucault, Francois Malgouyres, Franck Mamalet
Efficient Policy Evaluation with Safety Constraint for Reinforcement Learning
Claire Chen, Shuze Liu, Shangtong Zhang
Decoupled Subgraph Federated Learning
Javad Aliakbari, Johan Östman, Alexandre Graell i Amat
Rethinking Self-Distillation: Label Averaging and Enhanced Soft Label Refinement with Partial Labels
Hyeonsu Jeong, Hye Won Chung
Learning a Fast Mixing Exogenous Block MDP using a Single Trajectory
Alexander Levine, Peter Stone, Amy Zhang
Fitting Networks with a Cancellation Trick
Jiashun Jin, Jingming Wang
Utilitarian Algorithm Configuration for Infinite Parameter Spaces
Devon Graham, Kevin Leyton-Brown
A Large-scale Dataset and Benchmark for Commuting Origin-Destination Flow Generation
Can Rong, Jingtao Ding, Yan Liu et al.
Debiasing Federated Learning with Correlated Client Participation
Zhenyu Sun, Ziyang Zhang, Zheng Xu et al.
Do Contemporary Causal Inference Models Capture Real-World Heterogeneity? Findings from a Large-Scale Benchmark
Haining Yu, Yizhou Sun
Entropy-based Activation Function Optimization: A Method on Searching Better Activation Functions
Haoyuan Sun, Zihao Wu, Bo Xia et al.
Graph Generation with $K^2$-trees
Yunhui Jang, Dongwoo Kim, Sungsoo Ahn
Graph Neural Networks Gone Hogwild
Olga Solodova, Nick Richardson, Deniz Oktay et al.
Local Loss Optimization in the Infinite Width: Stable Parameterization of Predictive Coding Networks and Target Propagation
Satoki Ishikawa, Rio Yokota, Ryo Karakida
THE ROBUSTNESS OF DIFFERENTIABLE CAUSAL DISCOVERY IN MISSPECIFIED SCENARIOS
Huiyang Yi, Yanyan He, Duxin Chen et al.
Efficient Exploration and Discriminative World Model Learning with an Object-Centric Abstraction
Anthony GX-Chen, Kenneth Marino, Rob Fergus
SleepSMC: Ubiquitous Sleep Staging via Supervised Multimodal Coordination
Shuo Ma, Yingwei Zhang, Yiqiang Chen et al.
Incremental Causal Effect for Time to Treatment Initialization
Andrew Ying, Zhichen Zhao, Ronghui Xu
MamBEV: Enabling State Space Models to Learn Birds-Eye-View Representations
Hongyu Ke, Jack Morris, Kentaro Oguchi et al.
Unlearning-based Neural Interpretations
Ching Lam Choi, Alexandre Duplessis, Serge Belongie
New Algorithms for the Learning-Augmented k-means Problem
Junyu Huang, Qilong Feng, Ziyun Huang et al.
DyCAST: Learning Dynamic Causal Structure from Time Series
Yue Cheng, Bochen Lyu, Weiwei Xing et al.
Unsupervised Disentanglement of Content and Style via Variance-Invariance Constraints
Yuxuan Wu, Ziyu Wang, Bhiksha Raj et al.
A Robust Method to Discover Causal or Anticausal Relation
Yu Yao, Yang Zhou, Bo Han et al.
TDDBench: A Benchmark for Training data detection
Zhihao Zhu, Yi Yang, Defu Lian
RAPPER: Reinforced Rationale-Prompted Paradigm for Natural Language Explanation in Visual Question Answering
Kai-Po Chang, Chi-Pin Huang, Wei-Yuan Cheng et al.
Learning the Optimal Stopping for Early Classification within Finite Horizons via Sequential Probability Ratio Test
Akinori F. Ebihara, Taiki Miyagawa, Kazuyuki Sakurai et al.
Radar: Fast Long-Context Decoding for Any Transformer
Yongchang Hao, Mengyao Zhai, Hossein Hajimirsadeghi et al.
Boosting Perturbed Gradient Ascent for Last-Iterate Convergence in Games
Kenshi Abe, Mitsuki Sakamoto, Kaito Ariu et al.
Accelerated training through iterative gradient propagation along the residual path
Erwan Fagnou, Paul Caillon, Blaise Delattre et al.
Learning Neural Networks with Distribution Shift: Efficiently Certifiable Guarantees
Gautam Chandrasekaran, Adam Klivans, Lin Lin Lee et al.
Neural networks on Symmetric Spaces of Noncompact Type
Xuan Son Nguyen, Yang, Aymeric Histace
Complementary Label Learning with Positive Label Guessing and Negative Label Enhancement
Yuhang Li, Zhuying Li, Yuheng Jia
Fast and Accurate Blind Flexible Docking
Zizhuo Zhang, Lijun Wu, Kaiyuan Gao et al.
Causal Effect Estimation with Mixed Latent Confounders and Post-treatment Variables
Yaochen Zhu, Jing Ma, Liang Wu et al.
Dynamic Assortment Selection and Pricing with Censored Preference Feedback
Jung-hun Kim, Min-hwan Oh
Conservative Contextual Bandits: Beyond Linear Representations
Rohan Deb, Mohammad Ghavamzadeh, Arindam Banerjee
Towards Empowerment Gain through Causal Structure Learning in Model-Based Reinforcement Learning
Hongye Cao, Fan Feng, Meng Fang et al.
TTVD: Towards a Geometric Framework for Test-Time Adaptation Based on Voronoi Diagram
Mingxi Lei, Chunwei Ma, Meng Ding et al.
Discrete Latent Plans via Semantic Skill Abstractions
Haobin Jiang, Wang, Zongqing Lu
Learning-Augmented Frequent Directions
Anders Aamand, Justin Chen, Siddharth Gollapudi et al.
LCOT: Linear Circular Optimal Transport
ROCIO DIAZ MARTIN, Ivan Medri, Yikun Bai et al.
Learning Gain Map for Inverse Tone Mapping
yinuo liao, Yuanshen Guan, Ruikang Xu et al.
Generalizability of Neural Networks Minimizing Empirical Risk Based on Expressive Power
Lijia Yu, Yibo Miao, Yifan Zhu et al.
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.
PseDet: Revisiting the Power of Pseudo Label in Incremental Object Detection
Qiuchen Wang, Zehui Chen, Chenhongyi Yang et al.
How Gradient descent balances features: A dynamical analysis for two-layer neural networks
Zhenyu Zhu, Fanghui Liu, Volkan Cevher
DistillHGNN: A Knowledge Distillation Approach for High-Speed Hypergraph Neural Networks
Saman Forouzandeh, Parham Moradi Dowlatabadi, Mahdi Jalili
Adversarial Attacks on Data Attribution
Xinhe Wang, Pingbang Hu, Junwei Deng et al.
PBADet: A One-Stage Anchor-Free Approach for Part-Body Association
Zhongpai Gao, Huayi Zhou, Abhishek Sharma et al.
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.
Gaussian Differentially Private Human Faces Under a Face Radial Curve Representation
Carlos Soto, Matthew Reimherr, Aleksandra Slavkovic et al.
Ranking-aware adapter for text-driven image ordering with CLIP
Wei-Hsiang Yu, Yen-Yu Lin, Ming-Hsuan Yang et al.
TRENDy: Temporal Regression of Effective Nonlinear Dynamics
Matthew Ricci, Guy Pelc, Zoe Piran et al.
UniCon: Unidirectional Information Flow for Effective Control of Large-Scale Diffusion Models
Fanghua Yu, Jinjin Gu, Jinfan Hu et al.
Input Space Mode Connectivity in Deep Neural Networks
Jakub Vrabel, Ori Shem-ur, Yaron Oz et al.
PIED: Physics-Informed Experimental Design for Inverse Problems
Apivich Hemachandra, Gregory Kang Ruey Lau, See-Kiong Ng et al.
Going Beyond Static: Understanding Shifts with Time-Series Attribution
Jiashuo Liu, Nabeel Seedat, Peng Cui et al.
Release the Powers of Prompt Tuning: Cross-Modality Prompt Transfer
Ningyuan Zhang, Jie Lu, Keqiuyin Li et al.
Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making
Aliyah Hsu, Yeshwanth Cherapanamjeri, Briton Park et al.
Satisficing Regret Minimization in Bandits
Qing Feng, Tianyi Ma, Ruihao Zhu
CR2PQ: Continuous Relative Rotary Positional Query for Dense Visual Representation Learning
Shaofeng Zhang, Qiang Zhou, Sitong Wu et al.
GALA: Geometry-Aware Local Adaptive Grids for Detailed 3D Generation
Dingdong Yang, Yizhi Wang, Konrad Schindler et al.
Designing Concise ConvNets with Columnar Stages
Ashish Kumar, Jaesik Park
Learning Structured Representations by Embedding Class Hierarchy with Fast Optimal Transport
Siqi Zeng, Sixian Du, Makoto Yamada et al.
Distribution Backtracking Builds A Faster Convergence Trajectory for Diffusion Distillation
Shengyuan Zhang, Ling Yang, Zejian Li et al.
Benign Overfitting in Out-of-Distribution Generalization of Linear Models
Shange Tang, Jiayun Wu, Jianqing Fan et al.
Any-step Dynamics Model Improves Future Predictions for Online and Offline Reinforcement Learning
Haoxin Lin, Yu-Yan Xu, Yihao Sun et al.
LEAD: Min-Max Optimization from a Physical Perspective
Guillaume Lajoie, Amartya Mitra, Reyhane Askari Hemmat et al.
Neural Causal Graph for Interpretable and Intervenable Classification
Jiawei Wang, Shaofei Lu, Da Cao et al.
DLEFT-MKC: Dynamic Late Fusion Multiple Kernel Clustering with Robust Tensor Learning via Min-Max Optimization
Yi Zhang, Siwei Wang, Jiyuan Liu et al.
Pooling Image Datasets with Multiple Covariate Shift and Imbalance
Sotirios Panagiotis Chytas, Vishnu Lokhande, Vikas Singh
Revisit Micro-batch Clipping: Adaptive Data Pruning via Gradient Manipulation
Lun Wang
EvA: Erasing Spurious Correlations with Activations
Qiyuan He, Kai Xu, Angela Yao
GeoILP: A Synthetic Dataset to Guide Large-Scale Rule Induction
Si Chen, Richong Zhang, Xu Zhang