Most Cited ICLR "heuristic search algorithms" Papers
6,124 papers found • Page 10 of 31
Conference
Mix-CPT: A Domain Adaptation Framework via Decoupling Knowledge Learning and Format Alignment
Jinhao Jiang, Junyi Li, Xin Zhao et al.
On the Transfer of Object-Centric Representation Learning
Aniket Rajiv Didolkar, Andrii Zadaianchuk, Anirudh Goyal et al.
CausalRivers - Scaling up benchmarking of causal discovery for real-world time-series
Gideon Stein, Maha Shadaydeh, Jan Blunk et al.
PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation
Pablo Lemos, Sammy Sharief, Nikolay Malkin et al.
Mitigating Parameter Interference in Model Merging via Sharpness-Aware Fine-Tuning
Yeoreum Lee, Jinwook Jung, Sungyong Baik
Unified Convergence Analysis for Score-Based Diffusion Models with Deterministic Samplers
RUNJIA LI, Qiwei Di, Quanquan Gu
Understanding Fairness Surrogate Functions in Algorithmic Fairness
Yong Liu, (Andrew) Zhanke Zhou, Zhicong Li et al.
The Expressive Leaky Memory Neuron: an Efficient and Expressive Phenomenological Neuron Model Can Solve Long-Horizon Tasks.
Aaron Spieler, Nasim Rahaman, Georg Martius et al.
Attributing Culture-Conditioned Generations to Pretraining Corpora
Huihan Li, Arnav Goel, Keyu He et al.
Equivariant Symmetry Breaking Sets
YuQing Xie, Tess Smidt
Distributed Speculative Inference (DSI): Speculation Parallelism for Provably Faster Lossless Language Model Inference
Nadav Timor, Jonathan Mamou, Daniel Korat et al.
Generating Freeform Endoskeletal Robots
Muhan Li, Lingji Kong, Sam Kriegman
Actions Speak Louder Than Words: Rate-Reward Trade-off in Markov Decision Processes
Haotian Wu, Gongpu Chen, Deniz Gunduz
S4M: S4 for multivariate time series forecasting with Missing values
Jing Peng, Meiqi Yang, Qiong Zhang et al.
LIFe-GoM: Generalizable Human Rendering with Learned Iterative Feedback Over Multi-Resolution Gaussians-on-Mesh
Jing Wen, Alex Schwing, Shenlong Wang
PADRe: A Unifying Polynomial Attention Drop-in Replacement for Efficient Vision Transformer
Pierre-David Letourneau, Manish Singh, Hsin-Pai Cheng et al.
Video In-context Learning: Autoregressive Transformers are Zero-Shot Video Imitators
Wentao Zhang, Junliang Guo, Tianyu He et al.
HMoRA: Making LLMs More Effective with Hierarchical Mixture of LoRA Experts
Mengqi Liao, Wei Chen, Junfeng Shen et al.
Multi-Modal and Multi-Attribute Generation of Single Cells with CFGen
Alessandro Palma, Till Richter, Hanyi Zhang et al.
Learning from negative feedback, or positive feedback or both
Abbas Abdolmaleki, Bilal Piot, Bobak Shahriari et al.
Have the VLMs Lost Confidence? A Study of Sycophancy in VLMs
Shuo Li, Tao Ji, Xiaoran Fan et al.
VEDIT: Latent Prediction Architecture For Procedural Video Representation Learning
Han Lin, Tushar Nagarajan, Nicolas Ballas et al.
BRAID: Input-driven Nonlinear Dynamical Modeling of Neural-Behavioral Data
Parsa Vahidi, Omid G. Sani, Maryam Shanechi
Identifying Policy Gradient Subspaces
Jan Schneider, Pierre Schumacher, Simon Guist et al.
Transformers Learn Low Sensitivity Functions: Investigations and Implications
Bhavya Vasudeva, Deqing Fu, Tianyi Zhou et al.
Learning Fine-Grained Representations through Textual Token Disentanglement in Composed Video Retrieval
Yue Wu, Zhaobo Qi, Yiling Wu et al.
Distilling Reinforcement Learning Algorithms for In-Context Model-Based Planning
Jaehyeon Son, Soochan Lee, Gunhee Kim
Two-timescale Extragradient for Finding Local Minimax Points
Jiseok Chae, Kyuwon Kim, Donghwan Kim
ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design
Keir Adams, Kento Abeywardane, Jenna Fromer et al.
PostEdit: Posterior Sampling for Efficient Zero-Shot Image Editing
Feng Tian, Yixuan Li, Yichao Yan et al.
Dense Video Object Captioning from Disjoint Supervision
Xingyi Zhou, Anurag Arnab, Chen Sun et al.
Distributional Associations vs In-Context Reasoning: A Study of Feed-forward and Attention Layers
Lei Chen, Joan Bruna, Alberto Bietti
AnoLLM: Large Language Models for Tabular Anomaly Detection
Che-Ping Tsai, Ganyu Teng, Phillip Wallis et al.
SMT: Fine-Tuning Large Language Models with Sparse Matrices
Haoze He, Juncheng Li, Xuan Jiang et al.
CONTRA: Conformal Prediction Region via Normalizing Flow Transformation
Zhenhan FANG, Aixin Tan, Jian Huang
Efficient Active Imitation Learning with Random Network Distillation
Emilien Biré, Anthony Kobanda, Ludovic Denoyer et al.
ESE: Espresso Sentence Embeddings
Xianming Li, Zongxi Li, Jing Li et al.
Step-by-Step Reasoning for Math Problems via Twisted Sequential Monte Carlo
Shengyu Feng, Xiang Kong, shuang ma et al.
Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations
Richard Bergna, Sergio Calvo Ordoñez, Felix Opolka et al.
IPDreamer: Appearance-Controllable 3D Object Generation with Complex Image Prompts
Bohan Zeng, Shanglin Li, Yutang Feng et al.
Distance-Based Tree-Sliced Wasserstein Distance
Viet-Hoang Tran, Minh-Khoi Nguyen-Nhat, Trang Pham et al.
The Wasserstein Believer: Learning Belief Updates for Partially Observable Environments through Reliable Latent Space Models
Raphael Avalos, Florent Delgrange, Ann Nowe et al.
PIG: Physics-Informed Gaussians as Adaptive Parametric Mesh Representations
Namgyu Kang, Jaemin Oh, Youngjoon Hong et al.
Causally Aligned Curriculum Learning
Mingxuan Li, Junzhe Zhang, Elias Bareinboim
Understanding and Mitigating Bottlenecks of State Space Models through the Lens of Recency and Over-smoothing
Peihao Wang, Ruisi Cai, Yuehao Wang et al.
Improving Language Model Distillation through Hidden State Matching
Sayantan Dasgupta, Trevor Cohn
Triples as the Key: Structuring Makes Decomposition and Verification Easier in LLM-based TableQA
Zhen Yang, Ziwei Du, Minghan Zhang et al.
Pursuing Feature Separation based on Neural Collapse for Out-of-Distribution Detection
Yingwen Wu, Ruiji Yu, Xinwen Cheng et al.
Directional Gradient Projection for Robust Fine-Tuning of Foundation Models
Chengyue Huang, Junjiao Tian, Brisa Maneechotesuwan et al.
DrS: Learning Reusable Dense Rewards for Multi-Stage Tasks
Tongzhou Mu, Minghua Liu, Hao Su
Decision Tree Induction Through LLMs via Semantically-Aware Evolution
Tennison Liu, Nicolas Huynh, Mihaela van der Schaar
Valid Conformal Prediction for Dynamic GNNs
Ed Davis, Ian Gallagher, Daniel Lawson et al.
DAMO: Decoding by Accumulating Activations Momentum for Mitigating Hallucinations in Vision-Language Models
Kaishen Wang, Hengrui Gu, Meijun Gao et al.
Stochastic Semi-Gradient Descent for Learning Mean Field Games with Population-Aware Function Approximation
Chenyu Zhang, Xu Chen, Xuan Di
Boosting the visual interpretability of CLIP via adversarial fine-tuning
Shizhan Gong, Haoyu LEI, Qi Dou et al.
Implicit Neural Surface Deformation with Explicit Velocity Fields
Lu Sang, Zehranaz Canfes, Dongliang Cao et al.
UNR-Explainer: Counterfactual Explanations for Unsupervised Node Representation Learning Models
Hyunju Kang, Geonhee Han, Hogun Park
DGQ: Distribution-Aware Group Quantization for Text-to-Image Diffusion Models
Hyogon Ryu, NaHyeon Park, Hyunjung Shim
Robustness Auditing for Linear Regression: To Singularity and Beyond
Ittai Rubinstein, Samuel Hopkins
Circuit Transformer: A Transformer That Preserves Logical Equivalence
Xihan Li, Xing Li, Lei Chen et al.
Implicit Neural Representations and the Algebra of Complex Wavelets
T Mitchell Roddenberry, Vishwanath Saragadam, Maarten V de Hoop et al.
Injecting Universal Jailbreak Backdoors into LLMs in Minutes
Zhuowei Chen, qiannan zhang, Shichao Pei
Empowering LLM Agents with Zero-Shot Optimal Decision-Making through Q-learning
Jiajun Chai, Sicheng Li, Yuqian Fu et al.
Accelerated Convergence of Stochastic Heavy Ball Method under Anisotropic Gradient Noise
Rui Pan, Yuxing Liu, Xiaoyu Wang et al.
Multi-Perspective Data Augmentation for Few-shot Object Detection
Anh-Khoa Nguyen Vu, Quoc Truong Truong, Vinh-Tiep Nguyen et al.
HQGS: High-Quality Novel View Synthesis with Gaussian Splatting in Degraded Scenes
Xin Lin, Shi Luo, Xiaojun Shan et al.
Customizable Combination of Parameter-Efficient Modules for Multi-Task Learning
Haowen Wang, Tao Sun, Congyun Jin et al.
What Has Been Overlooked in Contrastive Source-Free Domain Adaptation: Leveraging Source-Informed Latent Augmentation within Neighborhood Context
JING WANG, Wonho Bae, Jiahong Chen et al.
Robust Training of Federated Models with Extremely Label Deficiency
Yonggang Zhang, Zhiqin Yang, Xinmei Tian et al.
In-context Time Series Predictor
Jiecheng Lu, Yan Sun, Shihao Yang
ActionReasoningBench: Reasoning about Actions with and without Ramification Constraints
Divij Handa, Pavel Dolin, Shrinidhi Kumbhar et al.
DebGCD: Debiased Learning with Distribution Guidance for Generalized Category Discovery
Yuanpei Liu, Kai Han
PostCast: Generalizable Postprocessing for Precipitation Nowcasting via Unsupervised Blurriness Modeling
Junchao Gong, Siwei Tu, Weidong Yang et al.
Glauber Generative Model: Discrete Diffusion Models via Binary Classification
Harshit Varma, Dheeraj Nagaraj, Karthikeyan Shanmugam
Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models
Jun Zhang, Jue Wang, Huan Li et al.
Neuron-based Multifractal Analysis of Neuron Interaction Dynamics in Large Models
Xiongye Xiao, Heng Ping, Chenyu Zhou et al.
CLIPDrag: Combining Text-based and Drag-based Instructions for Image Editing
Ziqi Jiang, Zhen Wang, Long Chen
Not All LLM-Generated Data Are Equal: Rethinking Data Weighting in Text Classification
Hsun-Yu Kuo, Yin-Hsiang Liao, Yu-Chieh Chao et al.
HiBug2: Efficient and Interpretable Error Slice Discovery for Comprehensive Model Debugging
Muxi Chen, Chenchen Zhao, Qiang Xu
Distributionally Robust Optimization with Bias and Variance Reduction
Ronak Mehta, Vincent Roulet, Krishna Pillutla et al.
Tight Clusters Make Specialized Experts
Stefan Nielsen, Rachel Teo, Laziz Abdullaev et al.
Integrative Decoding: Improving Factuality via Implicit Self-consistency
Yi Cheng, Xiao Liang, Yeyun Gong et al.
VAE-Var: Variational Autoencoder-Enhanced Variational Methods for Data Assimilation in Meteorology
Yi Xiao, Qilong Jia, Kun Chen et al.
Cached Multi-Lora Composition for Multi-Concept Image Generation
Xiandong Zou, Mingzhu Shen, Christos-Savvas Bouganis et al.
Stealthy Shield Defense: A Conditional Mutual Information-Based Approach against Black-Box Model Inversion Attacks
Tianqu Zhuang, Hongyao Yu, Yixiang Qiu et al.
Gradient descent with generalized Newton’s method
Zhiqi Bu, Shiyun Xu
OSDA Agent: Leveraging Large Language Models for De Novo Design of Organic Structure Directing Agents
Zhaolin Hu, Yixiao Zhou, Zhongan Wang et al.
Dynamic Sparse Training versus Dense Training: The Unexpected Winner in Image Corruption Robustness
Boqian Wu, Qiao Xiao, Shunxin Wang et al.
Linear combinations of latents in generative models: subspaces and beyond
Erik Bodin, Alexandru Stere, Dragos Margineantu et al.
Decoupling Angles and Strength in Low-rank Adaptation
Massimo Bini, Leander Girrbach, Zeynep Akata
On the Identification of Temporal Causal Representation with Instantaneous Dependence
Zijian Li, Yifan Shen, Kaitao Zheng et al.
DRL: Decomposed Representation Learning for Tabular Anomaly Detection
Hangting Ye, He Zhao, Wei Fan et al.
Beyond Content Relevance: Evaluating Instruction Following in Retrieval Models
Jianqun Zhou, Yuanlei Zheng, Wei Chen et al.
Multiview Equivariance Improves 3D Correspondence Understanding with Minimal Feature Finetuning
Yang You, Yixin Li, Congyue Deng et al.
BadRobot: Jailbreaking Embodied LLM Agents in the Physical World
Hangtao Zhang, Chenyu Zhu, Xianlong Wang et al.
Maximizing the Potential of Synthetic Data: Insights from Random Matrix Theory
Aymane El Firdoussi, Mohamed El Amine Seddik, Soufiane Hayou et al.
Circuit Representation Learning with Masked Gate Modeling and Verilog-AIG Alignment
Haoyuan Wu, Haisheng Zheng, Yuan Pu et al.
Mini-batch Coresets for Memory-efficient Language Model Training on Data Mixtures
Dang Nguyen, Wenhan Yang, Rathul Anand et al.
Tuning-Free Bilevel Optimization: New Algorithms and Convergence Analysis
Yifan Yang, Hao Ban, Minhui Huang et al.
Federated Residual Low-Rank Adaption of Large Language Models
Yunlu Yan, Chun-Mei Feng, Wangmeng Zuo et al.
Refining CLIP's Spatial Awareness: A Visual-Centric Perspective
Congpei Qiu, Yanhao Wu, Wei Ke et al.
Swiss Army Knife: Synergizing Biases in Knowledge from Vision Foundation Models for Multi-Task Learning
Yuxiang Lu, Shengcao Cao, Yu-Xiong Wang
Stiefel Flow Matching for Moment-Constrained Structure Elucidation
Austin H Cheng, Alston Lo, Kin Long Kelvin Lee et al.
Towards Understanding the Robustness of Diffusion-Based Purification: A Stochastic Perspective
Yiming Liu, Kezhao Liu, Yao Xiao et al.
Probabilistic Learning to Defer: Handling Missing Expert Annotations and Controlling Workload Distribution
Cuong Nguyen, Thanh-Toan Do, Gustavo Carneiro
Unveiling the Magic of Code Reasoning through Hypothesis Decomposition and Amendment
Yuze Zhao, Tianyun Ji, Wenjun Feng et al.
Analyzing and Improving Optimal-Transport-based Adversarial Networks
Jaemoo Choi, Jaewoong Choi, Myungjoo Kang
Bayesian Experimental Design Via Contrastive Diffusions
Jacopo Iollo, Christophe Heinkelé, Pierre Alliez et al.
Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better
Enshu Liu, Junyi Zhu, Zinan Lin et al.
Unsupervised Model Tree Heritage Recovery
Eliahu Horwitz, Asaf Shul, Yedid Hoshen
CAMEx: Curvature-aware Merging of Experts
Dung Viet Nguyen, Minh Nguyen, Luc Nguyen et al.
Growth Inhibitors for Suppressing Inappropriate Image Concepts in Diffusion Models
Die Chen, Zhiwen Li, Mingyuan Fan et al.
Learning-Augmented Search Data Structures
Chunkai Fu, Brandon G. Nguyen, Jung Seo et al.
Alice Benchmarks: Connecting Real World Re-Identification with the Synthetic
Xiaoxiao Sun, Yue Yao, Shengjin Wang et al.
Entropy-MCMC: Sampling from Flat Basins with Ease
Bolian Li, Ruqi Zhang
Reconciling Spatial and Temporal Abstractions for Goal Representation
Mehdi Zadem, Sergio Mover, Sao Mai Nguyen
GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning
Minghao Xu, Yunteng Geng, Yihang Zhang et al.
Spreading Out-of-Distribution Detection on Graphs
Daeho Um, Jongin Lim, Sunoh Kim et al.
Shedding Light on Time Series Classification using Interpretability Gated Networks
Yunshi Wen, Tengfei Ma, Ronny Luss et al.
Leveraging Submodule Linearity Enhances Task Arithmetic Performance in LLMs
Rui Dai, Sile Hu, Xu Shen et al.
Student-Informed Teacher Training
Nico Messikommer, Jiaxu Xing, Elie Aljalbout et al.
Bridging the Gap between Database Search and \emph{De Novo} Peptide Sequencing with SearchNovo
Jun Xia, Sizhe Liu, Jingbo Zhou et al.
Error Feedback Reloaded: From Quadratic to Arithmetic Mean of Smoothness Constants
Peter Richtarik, Elnur Gasanov, Konstantin Burlachenko
FedTMOS: Efficient One-Shot Federated Learning with Tsetlin Machine
Shannon How, Jagmohan Chauhan, Geoff Merrett et al.
Breaking Neural Network Scaling Laws with Modularity
Akhilan Boopathy, Sunshine Jiang, William Yue et al.
Error Norm Truncation: Robust Training in the Presence of Data Noise for Text Generation Models
Tianjian Li, Haoran Xu, Philipp Koehn et al.
EditRoom: LLM-parameterized Graph Diffusion for Composable 3D Room Layout Editing
Kaizhi Zheng, Xiaotong Chen, Xuehai He et al.
Gaussian-Det: Learning Closed-Surface Gaussians for 3D Object Detection
Hongru Yan, Yu Zheng, Yueqi Duan
Koopman-based generalization bound: New aspect for full-rank weights
Yuka Hashimoto, Sho Sonoda, Isao Ishikawa et al.
From Graphs to Hypergraphs: Hypergraph Projection and its Reconstruction
Yanbang Wang, Jon Kleinberg
Enhancing Cognition and Explainability of Multimodal Foundation Models with Self-Synthesized Data
Yucheng Shi, Quanzheng Li, Jin Sun et al.
Let Me Grok for You: Accelerating Grokking via Embedding Transfer from a Weaker Model
Zhiwei Xu, Zhiyu Ni, Yixin Wang et al.
Active Task Disambiguation with LLMs
Katarzyna Kobalczyk, Nicolás Astorga, Tennison Liu et al.
Accessing Vision Foundation Models via ImageNet-1K
Yitian Zhang, Xu Ma, Yue Bai et al.
Neural Eulerian Scene Flow Fields
Kyle Vedder, Neehar Peri, Ishan Khatri et al.
BrainOOD: Out-of-distribution Generalizable Brain Network Analysis
Jiaxing Xu, Yongqiang Chen, Xia Dong et al.
LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation
Mufei Li, Viraj Shitole, Eli Chien et al.
BrainACTIV: Identifying visuo-semantic properties driving cortical selectivity using diffusion-based image manipulation
Diego García Cerdas, Christina Sartzetaki, Magnus Petersen et al.
Dynamical Diffusion: Learning Temporal Dynamics with Diffusion Models
Xingzhuo Guo, Yu Zhang, Baixu Chen et al.
Feature Responsiveness Scores: Model-Agnostic Explanations for Recourse
Seung Hyun Cheon, Anneke Wernerfelt, Sorelle Friedler et al.
The Curse of Diversity in Ensemble-Based Exploration
Zhixuan Lin, Pierluca D'Oro, Evgenii Nikishin et al.
ELICIT: LLM Augmentation Via External In-context Capability
Futing Wang, Jianhao (Elliott) Yan, Yue Zhang et al.
Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching
Arnav Kumar Jain, Harley Wiltzer, Jesse Farebrother et al.
Revisiting a Design Choice in Gradient Temporal Difference Learning
Xiaochi Qian, Shangtong Zhang
StochSync: Stochastic Diffusion Synchronization for Image Generation in Arbitrary Spaces
Kyeongmin Yeo, Jaihoon Kim, Minhyuk Sung
Bidirectional Decoding: Improving Action Chunking via Guided Test-Time Sampling
Yuejiang Liu, Jubayer Hamid, Annie Xie et al.
Advantage Alignment Algorithms
Juan Duque, Milad Aghajohari, Timotheus Cooijmans et al.
Intrinsic Dimension Correlation: uncovering nonlinear connections in multimodal representations
Lorenzo Basile, Santiago Acevedo, Luca Bortolussi 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
Investigating the Pre-Training Dynamics of In-Context Learning: Task Recognition vs. Task Learning
Xiaolei Wang, Xinyu Tang, Junyi Li et al.
LoRA-X: Bridging Foundation Models with Training-Free Cross-Model Adaptation
Farzad Farhadzadeh, Debasmit Das, Shubhankar Borse et al.
On the Expressive Power of Sparse Geometric MPNNs
Yonatan Sverdlov, Nadav Dym
TaskGalaxy: Scaling Multi-modal Instruction Fine-tuning with Tens of Thousands Vision Task Types
Jiankang Chen, Tianke Zhang, Changyi Liu et al.
6D Object Pose Tracking in Internet Videos for Robotic Manipulation
Georgy Ponimatkin, Martin Cífka, Tomas Soucek et al.
GNNs Getting ComFy: Community and Feature Similarity Guided Rewiring
Celia Rubio-Madrigal, Adarsh Jamadandi, Rebekka Burkholz
Efficient Source-Free Time-Series Adaptation via Parameter Subspace Disentanglement
Gaurav Patel, Christopher M. Sandino, Behrooz Mahasseni et al.
Precedence-Constrained Winter Value for Effective Graph Data Valuation
Hongliang Chi, Wei Jin, Charu Aggarwal et al.
Divergence-enhanced Knowledge-guided Context Optimization for Visual-Language Prompt Tuning
Yilun Li, Miaomiao Cheng, Xu Han et al.
Multi-View Representation is What You Need for Point-Cloud Pre-Training
Siming Yan, Chen Song, Youkang Kong et al.
UV-Attack: Physical-World Adversarial Attacks on Person Detection via Dynamic-NeRF-based UV Mapping
Yanjie Li, Kaisheng Liang, Bin Xiao
OVTR: End-to-End Open-Vocabulary Multiple Object Tracking with Transformer
Jinyang Li, En Yu, Sijia Chen et al.
How DNNs break the Curse of Dimensionality: Compositionality and Symmetry Learning
Arthur Jacot, Seok Hoan Choi, Yuxiao Wen
Everything is Editable: Extend Knowledge Editing to Unstructured Data in Large Language Models
Jingcheng Deng, Zihao Wei, Liang Pang et al.
RGB-Event ISP: The Dataset and Benchmark
Yunfan LU, Yanlin Qian, Ziyang Rao et al.
MMSearch: Unveiling the Potential of Large Models as Multi-modal Search Engines
Dongzhi Jiang, Renrui Zhang, Ziyu Guo et al.
Bridging Compressed Image Latents and Multimodal Large Language Models
Chia-Hao Kao, Cheng Chien, Yu-Jen Tseng et al.
Time Fairness in Online Knapsack Problems
Adam Lechowicz, Rik Sengupta, Bo Sun et al.
IDInit: A Universal and Stable Initialization Method for Neural Network Training
Yu Pan, Chaozheng Wang, Zekai Wu et al.
Expand and Compress: Exploring Tuning Principles for Continual Spatio-Temporal Graph Forecasting
Wei Chen, Yuxuan Liang
Diffusion Bridge AutoEncoders for Unsupervised Representation Learning
Yeongmin Kim, Kwanghyeon Lee, Minsang Park et al.
PALMBENCH: A COMPREHENSIVE BENCHMARK OF COMPRESSED LARGE LANGUAGE MODELS ON MOBILE PLATFORMS
Yilong Li, Jingyu Liu, Hao Zhang et al.
Learning a Neural Solver for Parametric PDEs to Enhance Physics-Informed Methods
Lise Le Boudec, Emmanuel de Bézenac, Louis Serrano et al.
Enabling Realtime Reinforcement Learning at Scale with Staggered Asynchronous Inference
Matt Riemer, Gopeshh Raaj Subbaraj, Glen Berseth et al.
ConMix: Contrastive Mixup at Representation Level for Long-tailed Deep Clustering
Zhixin Li, Yuheng Jia
Out-of-Variable Generalisation for Discriminative Models
Siyuan Guo, Jonas Wildberger, Bernhard Schoelkopf
Concept-ROT: Poisoning Concepts in Large Language Models with Model Editing
Keltin Grimes, Marco Christiani, David Shriver et al.
Optimizing Posterior Samples for Bayesian Optimization via Rootfinding
Taiwo Adebiyi, Bach Do, Ruda Zhang
Gen-Z: Generative Zero-Shot Text Classification with Contextualized Label Descriptions
Sachin Kumar, Chan Young Park, Yulia Tsvetkov
Semantic Flow: Learning Semantic Fields of Dynamic Scenes from Monocular Videos
Fengrui Tian, Yueqi Duan, Angtian Wang et al.
Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control
Songyuan Zhang, Oswin So, Mitchell Black et al.
PlaSma: Procedural Knowledge Models for Language-based Planning and Re-Planning
Faeze Brahman, Chandra Bhagavatula, Valentina Pyatkin et al.
Decoupled Marked Temporal Point Process using Neural Ordinary Differential Equations
Yujee Song, Donghyun LEE, Rui Meng et al.
The Lipschitz-Variance-Margin Tradeoff for Enhanced Randomized Smoothing
Blaise Delattre, Alexandre Araujo, Quentin Barthélemy et al.
Scalable Bayesian Learning with posteriors
Samuel Duffield, Kaelan Donatella, Johnathan Chiu et al.
From Attention to Activation: Unraveling the Enigmas of Large Language Models
Prannay Kaul, Chengcheng Ma, Ismail Elezi et al.
Mask in the Mirror: Implicit Sparsification
Tom Jacobs, Rebekka Burkholz
Long-Term Typhoon Trajectory Prediction: A Physics-Conditioned Approach Without Reanalysis Data
Young-Jae Park, Minseok Seo, Doyi Kim et al.
Expressivity of Neural Networks with Random Weights and Learned Biases
Ezekiel Williams, Alexandre Payeur, Avery Ryoo et al.
State Space Models are Provably Comparable to Transformers in Dynamic Token Selection
Naoki Nishikawa, Taiji Suzuki
Learning to Solve Bilevel Programs with Binary Tender
Bo Zhou, Ruiwei Jiang, Siqian Shen
Stable Hadamard Memory: Revitalizing Memory-Augmented Agents for Reinforcement Learning
Hung Le, Dung Nguyen, Kien Do et al.
IMDPrompter: Adapting SAM to Image Manipulation Detection by Cross-View Automated Prompt Learning
Quan Zhang, Yuxin Qi, Xi Tang et al.
End-to-end Learning of Gaussian Mixture Priors for Diffusion Sampler
Denis Blessing, Xiaogang Jia, Gerhard Neumann
Diff-Prompt: Diffusion-driven Prompt Generator with Mask Supervision
Weicai Yan, Wang Lin, Zirun Guo et al.
Autocorrelation Matters: Understanding the Role of Initialization Schemes for State Space Models
Fusheng Liu, Qianxiao Li
Reinforcement learning with combinatorial actions for coupled restless bandits
Lily Xu, Bryan Wilder, Elias Khalil et al.
Faster Inference of Flow-Based Generative Models via Improved Data-Noise Coupling
Aram Davtyan, Leello Dadi, Volkan Cevher et al.
Bayesian WeakS-to-Strong from Text Classification to Generation
Ziyun Cui, Ziyang Zhang, Guangzhi Sun et al.
Flavors of Margin: Implicit Bias of Steepest Descent in Homogeneous Neural Networks
Nikolaos Tsilivis, Gal Vardi, Julia Kempe
Accelerating 3D Molecule Generation via Jointly Geometric Optimal Transport
Haokai Hong, Wanyu LIN, KC Tan