Most Cited ICLR "continuous variable inference" Papers
6,124 papers found • Page 18 of 31
Conference
BTR: Binary Token Representations for Efficient Retrieval Augmented Language Models
Qingqing Cao, Sewon Min, Yizhong Wang et al.
Understanding and Mitigating Bottlenecks of State Space Models through the Lens of Recency and Over-smoothing
Peihao Wang, Ruisi Cai, Yuehao Wang et al.
Dense Video Object Captioning from Disjoint Supervision
Xingyi Zhou, Anurag Arnab, Chen Sun et al.
Adversarial Attacks on Fairness of Graph Neural Networks
Binchi Zhang, Yushun Dong, Chen Chen et al.
Last-Iterate Convergence Properties of Regret-Matching Algorithms in Games
Yang Cai, Gabriele Farina, Julien Grand-Clément et al.
Expressivity of Neural Networks with Random Weights and Learned Biases
Ezekiel Williams, Alexandre Payeur, Avery Ryoo et al.
Efficient Active Imitation Learning with Random Network Distillation
Emilien Biré, Anthony Kobanda, Ludovic Denoyer et al.
Attributing Culture-Conditioned Generations to Pretraining Corpora
Huihan Li, Arnav Goel, Keyu He et al.
Causal Representation Learning from Multimodal Biomedical Observations
Yuewen Sun, Lingjing Kong, Guangyi Chen et al.
PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation
Pablo Lemos, Sammy Sharief, Nikolay Malkin et al.
lpNTK: Better Generalisation with Less Data via Sample Interaction During Learning
Shangmin Guo, YI REN, Stefano Albrecht et al.
Triples as the Key: Structuring Makes Decomposition and Verification Easier in LLM-based TableQA
Zhen Yang, Ziwei Du, Minghan Zhang et al.
Prediction without Preclusion: Recourse Verification with Reachable Sets
Avni Kothari, Bogdan Kulynych, Tsui-Wei Weng et al.
Explaining Modern Gated-Linear RNNs via a Unified Implicit Attention Formulation
Itamar Zimerman, ameen ali ali, Lior Wolf
Stochastic Semi-Gradient Descent for Learning Mean Field Games with Population-Aware Function Approximation
Chenyu Zhang, Xu Chen, Xuan Di
DGQ: Distribution-Aware Group Quantization for Text-to-Image Diffusion Models
Hyogon Ryu, NaHyeon Park, Hyunjung Shim
CAX: Cellular Automata Accelerated in JAX
Maxence Faldor, Antoine Cully
FairSeg: A Large-Scale Medical Image Segmentation Dataset for Fairness Learning Using Segment Anything Model with Fair Error-Bound Scaling
Yu Tian, Min Shi, Yan Luo et al.
Routing Experts: Learning to Route Dynamic Experts in Existing Multi-modal Large Language Models
Qiong Wu, Zhaoxi Ke, Yiyi Zhou et al.
Fair Classifiers that Abstain without Harm
Tongxin Yin, Jean-Francois Ton, Ruocheng Guo et al.
Improving Complex Reasoning with Dynamic Prompt Corruption: A Soft Prompt Optimization Approach
Sinan Fan, Liang Xie, Chen Shen et al.
Generating Freeform Endoskeletal Robots
Muhan Li, Lingji Kong, Sam Kriegman
FreqPrior: Improving Video Diffusion Models with Frequency Filtering Gaussian Noise
Yunlong Yuan, Yuanfan Guo, Chunwei Wang et al.
CausalRivers - Scaling up benchmarking of causal discovery for real-world time-series
Gideon Stein, Maha Shadaydeh, Jan Blunk et al.
Entropy-MCMC: Sampling from Flat Basins with Ease
Bolian Li, Ruqi Zhang
Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Models
Marien Renaud, Jiaming Liu, Valentin De Bortoli et al.
TVNet: A Novel Time Series Analysis Method Based on Dynamic Convolution and 3D-Variation
Chenghan Li, Mingchen LI, Ruisheng Diao
Efficiently Computing Similarities to Private Datasets
Arturs Backurs, Zinan Lin, Sepideh Mahabadi et al.
Exact Computation of Any-Order Shapley Interactions for Graph Neural Networks
Maximilian Muschalik, Fabian Fumagalli, Paolo Frazzetto et al.
SMITE: Segment Me In TimE
Amirhossein Alimohammadi, Sauradip Nag, Saeid Asgari et al.
Dual-Encoders for Extreme Multi-label Classification
Nilesh Gupta, Fnu Devvrit, Ankit Singh Rawat et al.
Mask in the Mirror: Implicit Sparsification
Tom Jacobs, Rebekka Burkholz
MindSimulator: Exploring Brain Concept Localization via Synthetic fMRI
Qi Zhang, Qi Zhang, Zixuan Gong et al.
Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control
Songyuan Zhang, Oswin So, Mitchell Black et al.
LASeR: Towards Diversified and Generalizable Robot Design with Large Language Models
JUNRU SONG, Yang Yang, Huan Xiao et al.
IMDPrompter: Adapting SAM to Image Manipulation Detection by Cross-View Automated Prompt Learning
Quan Zhang, Yuxin Qi, Xi Tang et al.
SMT: Fine-Tuning Large Language Models with Sparse Matrices
Haoze He, Juncheng Li, Xuan Jiang et al.
UNR-Explainer: Counterfactual Explanations for Unsupervised Node Representation Learning Models
Hyunju Kang, Geonhee Han, Hogun Park
Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models
Jun Zhang, Jue Wang, Huan Li et al.
Actions Speak Louder Than Words: Rate-Reward Trade-off in Markov Decision Processes
Haotian Wu, Gongpu Chen, Deniz Gunduz
A Recipe for Improved Certifiable Robustness
Kai Hu, Klas Leino, Zifan Wang et al.
Independent-Set Design of Experiments for Estimating Treatment and Spillover Effects under Network Interference
Chencheng Cai, Xu Zhang, Edoardo Airoldi
Skill or Luck? Return Decomposition via Advantage Functions
Hsiao-Ru Pan, Bernhard Schoelkopf
Empowering LLM Agents with Zero-Shot Optimal Decision-Making through Q-learning
Jiajun Chai, Sicheng Li, Yuqian Fu et al.
CAMBranch: Contrastive Learning with Augmented MILPs for Branching
Jiacheng Lin, Meng XU, Zhihua Xiong et al.
Language Agents Meet Causality -- Bridging LLMs and Causal World Models
John Gkountouras, Matthias Lindemann, Phillip Lippe et al.
ACES: Automatic Cohort Extraction System for Event-Stream Datasets
Justin Xu, Jack Gallifant, ALISTAIR JOHNSON et al.
Robustness Auditing for Linear Regression: To Singularity and Beyond
Ittai Rubinstein, Samuel Hopkins
Reasoning Elicitation in Language Models via Counterfactual Feedback
Alihan Hüyük, Xinnuo Xu, Jacqueline Maasch et al.
RecDreamer: Consistent Text-to-3D Generation via Uniform Score Distillation
Chenxi Zheng, Yihong Lin, Bangzhen Liu et al.
Confidence-aware Reward Optimization for Fine-tuning Text-to-Image Models
Kyuyoung Kim, Jongheon Jeong, Minyong An et al.
Better autoregressive regression with LLMs via regression-aware fine-tuning
Michal Lukasik, Zhao Meng, Harikrishna Narasimhan et al.
Contextual Self-paced Learning for Weakly Supervised Spatio-Temporal Video Grounding
Akash Kumar, Zsolt Kira, Yogesh S Rawat
Does Safety Training of LLMs Generalize to Semantically Related Natural Prompts?
Sravanti Addepalli, Yerram Varun, Arun Suggala et al.
PADRe: A Unifying Polynomial Attention Drop-in Replacement for Efficient Vision Transformer
Pierre-David Letourneau, Manish Singh, Hsin-Pai Cheng et al.
Two-timescale Extragradient for Finding Local Minimax Points
Jiseok Chae, Kyuwon Kim, Donghwan Kim
PostCast: Generalizable Postprocessing for Precipitation Nowcasting via Unsupervised Blurriness Modeling
Junchao Gong, Siwei Tu, Weidong Yang et al.
TaskGalaxy: Scaling Multi-modal Instruction Fine-tuning with Tens of Thousands Vision Task Types
Jiankang Chen, Tianke Zhang, Changyi Liu et al.
Federated Class-Incremental Learning: A Hybrid Approach Using Latent Exemplars and Data-Free Techniques to Address Local and Global Forgetting
Milad Khademi Nori, IL-MIN KIM, Guanghui Wang
Towards hyperparameter-free optimization with differential privacy
Ruixuan Liu, Zhiqi Bu
PALMBENCH: A COMPREHENSIVE BENCHMARK OF COMPRESSED LARGE LANGUAGE MODELS ON MOBILE PLATFORMS
Yilong Li, Jingyu Liu, Hao Zhang et al.
Boosting the visual interpretability of CLIP via adversarial fine-tuning
Shizhan Gong, Haoyu LEI, Qi Dou et al.
CLIPDrag: Combining Text-based and Drag-based Instructions for Image Editing
Ziqi Jiang, Zhen Wang, Long Chen
Rethinking Fair Representation Learning for Performance-Sensitive Tasks
Charles Jones, Fabio De Sousa Ribeiro, Mélanie Roschewitz et al.
Context-aware Dynamic Pruning for Speech Foundation Models
Masao Someki, Yifan Peng, Siddhant Arora et al.
Multi-Perspective Data Augmentation for Few-shot Object Detection
Anh-Khoa Nguyen Vu, Quoc Truong Truong, Vinh-Tiep Nguyen et al.
Most discriminative stimuli for functional cell type clustering
Max F. Burg, Thomas Zenkel, Michaela Vystrčilová et al.
ActionReasoningBench: Reasoning about Actions with and without Ramification Constraints
Divij Handa, Pavel Dolin, Shrinidhi Kumbhar et al.
HyperDAS: Towards Automating Mechanistic Interpretability with Hypernetworks
Jiuding Sun, Jing Huang, Sidharth Baskaran et al.
Generalization Bounds and Model Complexity for Kolmogorov–Arnold Networks
Xianyang Zhang, Huijuan Zhou
Conformalized Interactive Imitation Learning: Handling Expert Shift and Intermittent Feedback
Michelle Zhao, Henny Admoni, Reid Simmons et al.
Active Task Disambiguation with LLMs
Katarzyna Kobalczyk, Nicolás Astorga, Tennison Liu et al.
Physics-Informed Deep Inverse Operator Networks for Solving PDE Inverse Problems
Sung Woong Cho, Hwijae Son
Offline RL with Observation Histories: Analyzing and Improving Sample Complexity
Joey Hong, Anca Dragan, Sergey Levine
Accelerating 3D Molecule Generation via Jointly Geometric Optimal Transport
Haokai Hong, Wanyu LIN, KC Tan
Pursuing Feature Separation based on Neural Collapse for Out-of-Distribution Detection
Yingwen Wu, Ruiji Yu, Xinwen Cheng et al.
Diff-Prompt: Diffusion-driven Prompt Generator with Mask Supervision
Weicai Yan, Wang Lin, Zirun Guo et al.
Learning Fine-Grained Representations through Textual Token Disentanglement in Composed Video Retrieval
Yue Wu, Zhaobo Qi, Yiling Wu et al.
ConMix: Contrastive Mixup at Representation Level for Long-tailed Deep Clustering
Zhixin Li, Yuheng Jia
Preserving Deep Representations in One-Shot Pruning: A Hessian-Free Second-Order Optimization Framework
Ryan Lucas, Rahul Mazumder
Learning Hierarchical Polynomials with Three-Layer Neural Networks
Zihao Wang, Eshaan Nichani, Jason Lee
Earlier Tokens Contribute More: Learning Direct Preference Optimization From Temporal Decay Perspective
Ruichen Shao, Bei Li, Gangao Liu et al.
DAMO: Decoding by Accumulating Activations Momentum for Mitigating Hallucinations in Vision-Language Models
Kaishen Wang, Hengrui Gu, Meijun Gao et al.
Towards Eliminating Hard Label Constraints in Gradient Inversion Attacks
Yanbo Wang, Jian Liang, Ran He
Poison-splat: Computation Cost Attack on 3D Gaussian Splatting
Jiahao Lu, Yifan Zhang, Qiuhong Shen et al.
Gen-Z: Generative Zero-Shot Text Classification with Contextualized Label Descriptions
Sachin Kumar, Chan Young Park, Yulia Tsvetkov
$t^3$-Variational Autoencoder: Learning Heavy-tailed Data with Student's t and Power Divergence
Juno Kim, Jaehyuk Kwon, Mincheol Cho et al.
ELFS: Label-Free Coreset Selection with Proxy Training Dynamics
Haizhong Zheng, Elisa Tsai, Yifu Lu et al.
S4M: S4 for multivariate time series forecasting with Missing values
Jing Peng, Meiqi Yang, Qiong Zhang et al.
On the Modeling Capabilities of Large Language Models for Sequential Decision Making
Martin Klissarov, R Devon Hjelm, Alexander Toshev et al.
Learning Semantic Proxies from Visual Prompts for Parameter-Efficient Fine-Tuning in Deep Metric Learning
Li Ren, Chen Chen, Liqiang Wang et al.
AtomSurf: Surface Representation for Learning on Protein Structures
Vincent Mallet, Yangyang Miao, Souhaib Attaiki et al.
PIG: Physics-Informed Gaussians as Adaptive Parametric Mesh Representations
Namgyu Kang, Jaemin Oh, Youngjoon Hong et al.
Don't flatten, tokenize! Unlocking the key to SoftMoE's efficacy in deep RL
Ghada Sokar, Johan S Obando Ceron, Aaron Courville et al.
Second Order Bounds for Contextual Bandits with Function Approximation
Aldo Pacchiano
Refining CLIP's Spatial Awareness: A Visual-Centric Perspective
Congpei Qiu, Yanhao Wu, Wei Ke et al.
BitStack: Any-Size Compression of Large Language Models in Variable Memory Environments
Xinghao Wang, Pengyu Wang, Bo Wang et al.
Diffeomorphic Mesh Deformation via Efficient Optimal Transport for Cortical Surface Reconstruction
Thanh-Tung Le, Khai Nguyen, shanlin sun et al.
Bidirectional Decoding: Improving Action Chunking via Guided Test-Time Sampling
Yuejiang Liu, Jubayer Hamid, Annie Xie et al.
VEDIT: Latent Prediction Architecture For Procedural Video Representation Learning
Han Lin, Tushar Nagarajan, Nicolas Ballas et al.
InstaSHAP: Interpretable Additive Models Explain Shapley Values Instantly
James Enouen, Yan Liu
Expand and Compress: Exploring Tuning Principles for Continual Spatio-Temporal Graph Forecasting
Wei Chen, Yuxuan Liang
Mini-batch Coresets for Memory-efficient Language Model Training on Data Mixtures
Dang Nguyen, Wenhan Yang, Rathul Anand et al.
CO-MOT: Boosting End-to-end Transformer-based Multi-Object Tracking via Coopetition Label Assignment and Shadow Sets
feng yan, Weixin Luo, Yujie Zhong et al.
Faithful and Efficient Explanations for Neural Networks via Neural Tangent Kernel Surrogate Models
Andrew Engel, Zhichao Wang, Natalie Frank et al.
Counterfactual Density Estimation using Kernel Stein Discrepancies
Diego Martinez-Taboada, Edward Kennedy
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.
On the Transfer of Object-Centric Representation Learning
Aniket Rajiv Didolkar, Andrii Zadaianchuk, Anirudh Goyal et al.
Mix-CPT: A Domain Adaptation Framework via Decoupling Knowledge Learning and Format Alignment
Jinhao Jiang, Junyi Li, Xin Zhao et al.
On the Completeness of Invariant Geometric Deep Learning Models
Zian Li, Xiyuan Wang, Shijia Kang et al.
ESE: Espresso Sentence Embeddings
Xianming Li, Zongxi Li, Jing Li et al.
InsertNeRF: Instilling Generalizability into NeRF with HyperNet Modules
Yanqi Bao, Tianyu Ding, Jing Huo et al.
Dynamical Diffusion: Learning Temporal Dynamics with Diffusion Models
Xingzhuo Guo, Yu Zhang, Baixu Chen et al.
Controllable Satellite-to-Street-View Synthesis with Precise Pose Alignment and Zero-Shot Environmental Control
Xianghui Ze, Zhenbo Song, Qiwei Wang et al.
Immunogenicity Prediction with Dual Attention Enables Vaccine Target Selection
Song Li, Yang Tan, Song Ke et al.
Subgraph Federated Learning for Local Generalization
Sungwon Kim, Yoonho Lee, Yunhak Oh et al.
Distilling Reinforcement Learning Algorithms for In-Context Model-Based Planning
Jaehyeon Son, Soochan Lee, Gunhee Kim
PWM: Policy Learning with Multi-Task World Models
Ignat Georgiev, Varun Giridhar, Nick Hansen et al.
BRAID: Input-driven Nonlinear Dynamical Modeling of Neural-Behavioral Data
Parsa Vahidi, Omid G. Sani, Maryam Shanechi
CREIMBO: Cross-Regional Ensemble Interactions in Multi-view Brain Observations
Noga Mudrik, Ryan Ly, Oliver Ruebel et al.
Let Your Features Tell The Differences: Understanding Graph Convolution By Feature Splitting
Yilun Zheng, Xiang Li, Sitao Luan et al.
Understanding Fairness Surrogate Functions in Algorithmic Fairness
Yong Liu, (Andrew) Zhanke Zhou, Zhicong Li et al.
Enhancing Language Model Agents using Diversity of Thoughts
Vijay Chandra Lingam, Behrooz Tehrani, sujay sanghavi et al.
BinaryDM: Accurate Weight Binarization for Efficient Diffusion Models
Xingyu Zheng, Xianglong Liu, Haotong Qin et al.
Effective and Efficient Time-Varying Counterfactual Prediction with State-Space Models
Haotian Wang, Haoxuan Li, Hao Zou et al.
Identifying Policy Gradient Subspaces
Jan Schneider, Pierre Schumacher, Simon Guist et al.
Re-evaluating Open-ended Evaluation of Large Language Models
Si-Qi Liu, Ian Gemp, Luke Marris et al.
DoF: A Diffusion Factorization Framework for Offline Multi-Agent Reinforcement Learning
Chao Li, Ziwei Deng, Chenxing Lin et al.
UniCoTT: A Unified Framework for Structural Chain-of-Thought Distillation
Xianwei Zhuang, Zhihong Zhu, Zhichang Wang et al.
Towards Understanding the Robustness of Diffusion-Based Purification: A Stochastic Perspective
Yiming Liu, Kezhao Liu, Yao Xiao et al.
HQGS: High-Quality Novel View Synthesis with Gaussian Splatting in Degraded Scenes
Xin Lin, Shi Luo, Xiaojun Shan et al.
Graph Neural Ricci Flow: Evolving Feature from a Curvature Perspective
Jialong Chen, Bowen Deng, Zhen WANG et al.
Feature Responsiveness Scores: Model-Agnostic Explanations for Recourse
Seung Hyun Cheon, Anneke Wernerfelt, Sorelle Friedler et al.
Breaking Class Barriers: Efficient Dataset Distillation via Inter-Class Feature Compensator
xin zhang, Jiawei Du, Ping Liu et al.
Long-Term Typhoon Trajectory Prediction: A Physics-Conditioned Approach Without Reanalysis Data
Young-Jae Park, Minseok Seo, Doyi Kim et al.
Semantic Flow: Learning Semantic Fields of Dynamic Scenes from Monocular Videos
Fengrui Tian, Yueqi Duan, Angtian Wang et al.
Distributed Speculative Inference (DSI): Speculation Parallelism for Provably Faster Lossless Language Model Inference
Nadav Timor, Jonathan Mamou, Daniel Korat et al.
Video In-context Learning: Autoregressive Transformers are Zero-Shot Video Imitators
Wentao Zhang, Junliang Guo, Tianyu He et al.
Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling
Hyungi Lee, Giung Nam, Edwin Fong et al.
FreSh: Frequency Shifting for Accelerated Neural Representation Learning
Adam Kania, Marko Mihajlovic, Sergey Prokudin et al.
UniDetox: Universal Detoxification of Large Language Models via Dataset Distillation
Huimin LU, Masaru Isonuma, Junichiro Mori et al.
VertiBench: Advancing Feature Distribution Diversity in Vertical Federated Learning Benchmarks
Zhaomin Wu, Junyi Hou, Bingsheng He
Universal generalization guarantees for Wasserstein distributionally robust models
Tam Le, Jerome Malick
GPS: A Probabilistic Distributional Similarity with Gumbel Priors for Set-to-Set Matching
Ziming Zhang, Fangzhou Lin, Haotian Liu et al.
Implicit Gaussian process representation of vector fields over arbitrary latent manifolds
Robert Peach, Matteo Vinao-Carl, Nir Grossman et al.
Improving Language Model Distillation through Hidden State Matching
Sayantan Dasgupta, Trevor Cohn
Robot Fleet Learning via Policy Merging
Lirui Wang, Kaiqing Zhang, Allan Zhou et al.
StochSync: Stochastic Diffusion Synchronization for Image Generation in Arbitrary Spaces
Kyeongmin Yeo, Jaihoon Kim, Minhyuk Sung
Neuron-based Multifractal Analysis of Neuron Interaction Dynamics in Large Models
Xiongye Xiao, Heng Ping, Chenyu Zhou et al.
Cocoon: Robust Multi-Modal Perception with Uncertainty-Aware Sensor Fusion
Minkyoung Cho, Yulong Cao, Jiachen Sun et al.
Forte : Finding Outliers with Representation Typicality Estimation
Debargha Ganguly, Warren Morningstar, Andrew Yu et al.
Procedural Synthesis of Synthesizable Molecules
Michael Sun, Alston Lo, Minghao Guo et al.
On Disentangled Training for Nonlinear Transform in Learned Image Compression
Han Li, Shaohui Li, Wenrui Dai et al.
Unsupervised Model Tree Heritage Recovery
Eliahu Horwitz, Asaf Shul, Yedid Hoshen
Time-to-Event Pretraining for 3D Medical Imaging
Zepeng Frazier Huo, Jason Fries, Alejandro Lozano et al.
Wicked Oddities: Selectively Poisoning for Effective Clean-Label Backdoor Attacks
Hung Quang Nguyen, Hieu Nguyen, Anh Ta et al.
RGB-Event ISP: The Dataset and Benchmark
Yunfan LU, Yanlin Qian, Ziyang Rao et al.
A Statistical Framework for Ranking LLM-based Chatbots
Siavash Ameli, Siyuan Zhuang, Ion Stoica et al.
Reinforcement learning with combinatorial actions for coupled restless bandits
Lily Xu, Bryan Wilder, Elias Khalil et al.
Diffusion Bridge AutoEncoders for Unsupervised Representation Learning
Yeongmin Kim, Kwanghyeon Lee, Minsang Park et al.
Reconciling Model Multiplicity for Downstream Decision Making
Ally Du, Dung Daniel Ngo, Steven Wu
On Speeding Up Language Model Evaluation
Jin Zhou, Christian Belardi, Ruihan Wu et al.
Divergence-enhanced Knowledge-guided Context Optimization for Visual-Language Prompt Tuning
Yilun Li, Miaomiao Cheng, Xu Han et al.
Adapt-$\infty$: Scalable Continual Multimodal Instruction Tuning via Dynamic Data Selection
Adyasha Maharana, Jaehong Yoon, Tianlong Chen et al.
Decoupling Layout from Glyph in Online Chinese Handwriting Generation
Minsi Ren, Yan-Ming Zhang, yi chen
3D-MolT5: Leveraging Discrete Structural Information for Molecule-Text Modeling
Qizhi Pei, Rui Yan, Kaiyuan Gao et al.
Efficient Source-Free Time-Series Adaptation via Parameter Subspace Disentanglement
Gaurav Patel, Christopher M. Sandino, Behrooz Mahasseni et al.
E(3)-equivariant models cannot learn chirality: Field-based molecular generation
Alexandru Dumitrescu, Dani Korpela, Markus Heinonen et al.
On the Expressive Power of Sparse Geometric MPNNs
Yonatan Sverdlov, Nadav Dym
Tight Time Complexities in Parallel Stochastic Optimization with Arbitrary Computation Dynamics
Alexander Tyurin
Control-oriented Clustering of Visual Latent Representation
Han Qi, Haocheng Yin, Heng Yang
Ensembles of Low-Rank Expert Adapters
Yinghao Li, Vianne Gao, Chao Zhang et al.
SimXRD-4M: Big Simulated X-ray Diffraction Data and Crystal Symmetry Classification Benchmark
Bin Cao, Yang Liu, Zinan Zheng et al.
Bridging Information Asymmetry in Text-video Retrieval: A Data-centric Approach
Zechen Bai, Tianjun Xiao, Tong He et al.
MIND: Math Informed syNthetic Dialogues for Pretraining LLMs
Syeda Nahida Akter, Shrimai Prabhumoye, John Kamalu et al.
Towards Robust Multimodal Open-set Test-time Adaptation via Adaptive Entropy-aware Optimization
Hao Dong, Eleni Chatzi, Olga Fink
Investigating the Pre-Training Dynamics of In-Context Learning: Task Recognition vs. Task Learning
Xiaolei Wang, Xinyu Tang, Junyi Li et al.
How to Probe: Simple Yet Effective Techniques for Improving Post-hoc Explanations
Siddhartha Gairola, Moritz Böhle, Francesco Locatello et al.
Advantage Alignment Algorithms
Juan Duque, Milad Aghajohari, Timotheus Cooijmans et al.
Dynamic Low-Rank Sparse Adaptation for Large Language Models
Weizhong Huang, Yuxin Zhang, Xiawu Zheng et al.
Neural Dueling Bandits: Preference-Based Optimization with Human Feedback
Arun Verma, Zhongxiang Dai, Xiaoqiang Lin et al.
Unleashing the Potential of Vision-Language Pre-Training for 3D Zero-Shot Lesion Segmentation via Mask-Attribute Alignment
Yankai Jiang, Wenhui Lei, Xiaofan Zhang et al.
Stabilized Neural Prediction of Potential Outcomes in Continuous Time
Konstantin Hess, Stefan Feuerriegel
Maximizing the Potential of Synthetic Data: Insights from Random Matrix Theory
Aymane El Firdoussi, Mohamed El Amine Seddik, Soufiane Hayou et al.
Cached Multi-Lora Composition for Multi-Concept Image Generation
Xiandong Zou, Mingzhu Shen, Christos-Savvas Bouganis et al.
Bootstrapped Model Predictive Control
Yuhang Wang, Hanwei Guo, Sizhe Wang et al.
Test-time Adaptation for Regression by Subspace Alignment
Kazuki Adachi, Shin'ya Yamaguchi, Atsutoshi Kumagai et al.
Decoupled Graph Energy-based Model for Node Out-of-Distribution Detection on Heterophilic Graphs
Yuhan Chen, Yihong Luo, Yifan Song et al.
Weakly-Supervised Affordance Grounding Guided by Part-Level Semantic Priors
Peiran Xu, Yadong MU
IGL-Bench: Establishing the Comprehensive Benchmark for Imbalanced Graph Learning
Jiawen Qin, Haonan Yuan, Qingyun Sun et al.
Not-So-Optimal Transport Flows for 3D Point Cloud Generation
Ka-Hei Hui, Chao Liu, xiaohui zeng et al.
Bayesian Experimental Design Via Contrastive Diffusions
Jacopo Iollo, Christophe Heinkelé, Pierre Alliez et al.
Learning a Neural Solver for Parametric PDEs to Enhance Physics-Informed Methods
Lise Le Boudec, Emmanuel de Bézenac, Louis Serrano et al.
Multilevel Generative Samplers for Investigating Critical Phenomena
Ankur Singha, Elia Cellini, Kim A. Nicoli et al.
Probabilistic Learning to Defer: Handling Missing Expert Annotations and Controlling Workload Distribution
Cuong Nguyen, Thanh-Toan Do, Gustavo Carneiro
Linear combinations of latents in generative models: subspaces and beyond
Erik Bodin, Alexandru Stere, Dragos Margineantu et al.
Intrinsic Dimension Correlation: uncovering nonlinear connections in multimodal representations
Lorenzo Basile, Santiago Acevedo, Luca Bortolussi et al.
One Model Transfer to All: On Robust Jailbreak Prompts Generation against LLMs
Linbao Li, Yannan Liu, Daojing He et al.
Optimal Strong Regret and Violation in Constrained MDPs via Policy Optimization
Francesco Emanuele Stradi, Matteo Castiglioni, Alberto Marchesi et al.
Spreading Out-of-Distribution Detection on Graphs
Daeho Um, Jongin Lim, Sunoh Kim et al.