Most Cited 2025 "rank loss optimization" Papers
21,856 papers found • Page 110 of 110
Conference
Domain-Adapted Diffusion Model for PROTAC Linker Design Through the Lens of Density Ratio in Chemical Space
Zixing Song, Ziqiao Meng, Jose Miguel Hernandez-Lobato
Three-Dimensional Trajectory Prediction with 3DMoTraj Dataset
Hao Zhou, Xu Yang, Mingyu Fan et al.
Continuously Updating Digital Twins using Large Language Models
Harry Amad, Nicolás Astorga, Mihaela van der Schaar
Do Not Mimic My Voice : Speaker Identity Unlearning for Zero-Shot Text-to-Speech
Taesoo Kim, Jinju Kim, Dongchan Kim et al.
Aggregation of Dependent Expert Distributions in Multimodal Variational Autoencoders
Rogelio A. Mancisidor, Robert Jenssen, Shujian Yu et al.
Distillation of Discrete Diffusion through Dimensional Correlations
Satoshi Hayakawa, Yuhta Takida, Masaaki Imaizumi et al.
SecEmb: Sparsity-Aware Secure Federated Learning of On-Device Recommender System with Large Embedding
Peihua Mai, Youlong Ding, Ziyan Lyu et al.
ML$^2$-GCL: Manifold Learning Inspired Lightweight Graph Contrastive Learning
Jianqing Liang, Zhiqiang Li, Xinkai Wei et al.
Multi-agent Architecture Search via Agentic Supernet
Guibin Zhang, Luyang Niu, Junfeng Fang et al.
Radio: Rate–Distortion Optimization for Large Language Model Compression
Sean I. Young
An Analysis of Quantile Temporal-Difference Learning
Mark Rowland, Remi Munos, Mohammad Gheshlaghi Azar et al.
Explicit Preference Optimization: No Need for an Implicit Reward Model
Xiangkun Hu, Lemin Kong, Tong He et al.
Annealing Flow Generative Models Towards Sampling High-Dimensional and Multi-Modal Distributions
Dongze Wu, Yao Xie
RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers
Xuwei Xu, Yang Li, Yudong Chen et al.
Extracting Rare Dependence Patterns via Adaptive Sample Reweighting
Yiqing Li, Yewei Xia, Xiaofei Wang et al.
Bipartite Ranking From Multiple Labels: On Loss Versus Label Aggregation
Michal Lukasik, Lin Chen, Harikrishna Narasimhan et al.
ELoRA: Low-Rank Adaptation for Equivariant GNNs
Chen Wang, Siyu Hu, Guangming Tan et al.
PTTA: Purifying Malicious Samples for Test-Time Model Adaptation
Jing Ma, Hanlin Li, Xiang Xiang
CFPT: Empowering Time Series Forecasting through Cross-Frequency Interaction and Periodic-Aware Timestamp Modeling
Feifei Kou, Jiahao Wang, Lei Shi et al.
Redundancy Undermines the Trustworthiness of Self-Interpretable GNNs
Wenxin Tai, Ting Zhong, Goce Trajcevski et al.
Modular Duality in Deep Learning
Jeremy Bernstein, Laker Newhouse
Gap-Dependent Bounds for Federated $Q$-Learning
Haochen Zhang, Zhong Zheng, Lingzhou Xue
Slimming the Fat-Tail: Morphing-Flow for Adaptive Time Series Modeling
Tianyu Liu, kai sun, Fuchun Sun et al.
Enhancing Ligand Validity and Affinity in Structure-Based Drug Design with Multi-Reward Optimization
Seungbeom Lee, Munsun Jo, Jungseul Ok et al.
GS-Bias: Global-Spatial Bias Learner for Single-Image Test-Time Adaptation of Vision-Language Models
Zhaohong Huang, Yuxin Zhang, JingJing Xie et al.
BECAME: Bayesian Continual Learning with Adaptive Model Merging
Mei Li, Yuxiang Lu, Qinyan Dai et al.
Pre-Training Graph Contrastive Masked Autoencoders are Strong Distillers for EEG
Xinxu Wei, kanhao zhao, Yong Jiao et al.
MathConstruct: Challenging LLM Reasoning with Constructive Proofs
Mislav Balunovic, Jasper Dekoninck, Nikola Jovanović et al.
Falcon: Fast Visuomotor Policies via Partial Denoising
Haojun Chen, Minghao Liu, Chengdong Ma et al.
Linear Contextual Bandits With Interference
Yang Xu, Wenbin Lu, Rui Song
Commute Graph Neural Networks
Wei Zhuo, Han Yu, Guang Tan et al.
Textural or Textual: How Vision-Language Models Read Text in Images
Hanzhang Wang, Qingyuan Ma
Supervised Contrastive Learning from Weakly-Labeled Audio Segments for Musical Version Matching
Joan Serrà, Recep Oguz Araz, Dmitry Bogdanov et al.
QLASS: Boosting Language Agent Inference via Q-Guided Stepwise Search
Zongyu Lin, Yao Tang, Xingcheng Yao et al.
Understanding the Kronecker Matrix-Vector Complexity of Linear Algebra
Raphael Meyer, William Swartworth, David Woodruff
Offline Model-based Optimization for Real-World Molecular Discovery
Dong-Hee Shin, Young-Han Son, Hyun Jung Lee et al.
On the Statistical Mechanisms of Distributional Compositional Generalization
Jingwen Fu, Nanning Zheng
Multi-Armed Bandits with Interference: Bridging Causal Inference and Adversarial Bandits
Su Jia, Peter Frazier, Nathan Kallus
QMamba: On First Exploration of Vision Mamba for Image Quality Assessment
Fengbin Guan, Xin Li, Zihao Yu et al.
ExpProof : Operationalizing Explanations for Confidential Models with ZKPs
Chhavi Yadav, Evan Laufer, Dan Boneh et al.
FedClean: A General Robust Label Noise Correction for Federated Learning
Xiaoqian Jiang, Jing Zhang
FisherSFT: Data-Efficient Supervised Fine-Tuning of Language Models Using Information Gain
Rohan Deb, Kiran Thekumparampil, Kousha Kalantari et al.
Product of Experts with LLMs: Boosting Performance on ARC Is a Matter of Perspective
Daniel Franzen, Jan Disselhoff, David Hartmann
Testing Conditional Mean Independence Using Generative Neural Networks
Yi Zhang, Linjun Huang, Yun Yang et al.
WeGeFT: Weight‑Generative Fine‑Tuning for Multi‑Faceted Efficient Adaptation of Large Models
Chinmay Savadikar, Xi Song, Tianfu Wu
Towards flexible perception with visual memory
Robert Geirhos, Priyank Jaini, Austin Stone et al.
Streamline Without Sacrifice - Squeeze out Computation Redundancy in LMM
Penghao Wu, Lewei Lu, Ziwei Liu
Sorbet: A Neuromorphic Hardware-Compatible Transformer-Based Spiking Language Model
Kaiwen Tang, Zhanglu Yan, Weng-Fai Wong
To Each Metric Its Decoding: Post-Hoc Optimal Decision Rules of Probabilistic Hierarchical Classifiers
Roman Plaud, Alexandre Perez-Lebel, Matthieu Labeau et al.
Chip Placement with Diffusion Models
Vint Lee, Minh Nguyen, Leena Elzeiny et al.
EVOLvE: Evaluating and Optimizing LLMs For In-Context Exploration
Allen Nie, Yi Su, Bo Chang et al.
Improving Soft Unification with Knowledge Graph Embedding Methods
Xuanming Cui, Chionh Peng, Adriel Kuek et al.
Riemann Tensor Neural Networks: Learning Conservative Systems with Physics-Constrained Networks
Anas Jnini, Lorenzo Breschi, Flavio Vella
The Emperor's New Clothes in Benchmarking? A Rigorous Examination of Mitigation Strategies for LLM Benchmark Data Contamination
Yifan Sun, Han Wang, Dongbai Li et al.
Controlling Large Language Model with Latent Action
Chengxing Jia, Ziniu Li, Pengyuan Wang et al.
Algorithmic Recourse for Long-Term Improvement
Kentaro Kanamori, Ken Kobayashi, Satoshi Hara et al.