Papers
How Many Experts Are Enough? Towards Optimal Semantic Specialization for Mixture-of-Experts
Sumin Park, Noseong Park
ProLoG: Hybrid Prompt and LoRA Based Adaptation of Vision-Language Models for OOD Generalization
Jungwuk Park, Dong-Jun Han, Jaekyun Moon
Fair Model-based Clustering
Jinwon Park, Kunwoong Kim, Jihu Lee et al.
Transferable Model-agnostic Vision-Language Model Adaptation for Efficient Weak-to-Strong Generalization
Jihwan Park, Taehoon Song, Sanghyeok Lee et al.
MoCHA: Advanced Vision-Language Reasoning with MoE Connector and Hierarchical Group Attention
Yuqi Pang, Bowen Yang, Yun Cao et al.
Decoupling Shared and Personalized Knowledge: A Dual-Branch Federated Learning Framework for Multi-Domain with Non-IID Data
Yiran Pang, Zhen Ni, Xiangnan Zhong
Forest vs Tree: The (N, K) Trade-off in Reproducible ML Evaluation
Deepak Pandita, Flip Korn, Chris Welty et al.
Dynamic Sparsity: Challenging Common Sparsity Assumptions for Learning World Models in Robotic Reinforcement Learning Benchmarks
Muthukumar Pandaram, Jakob Hollenstein, David Drexel et al.
On the Misalignment Between Data Learnability and Forgettability in Machine Unlearning
Zijie Pan, Zuobin Ying, Yajie Wang et al.
Prototype Entropy Alignment: Reinforcing Structured Uncertainty in LLM Reasoning
Zhengyuan Pan, Yanhao Chen, Zhongquan Jian et al.
Re-architecting Personalized Federated Learning for Demanding Edge Environments
Quyang Pan, Sheng Sun, Tingting Wi et al.
Correcting False Alarms from Unseen: Adapting Graph Anomaly Detectors at Test Time
Junjun Pan, Yixin Liu, Chuan Zhou et al.
OPTION: An Online Pricing Strategy for Asynchronous Federated Learning Against Free-Riding Attacks
Bangqi Pan, Jianfeng Lu, Shuqin Cao et al.
Policy Newton Methods for Distortion Riskmetrics
Soumen Pachal, Mizhaan Prajit Maniyar, Prashanth L. A.
Learn from Global Correlations: Enhancing Evolutionary Algorithm via Spectral GNN
Kaichen Ouyang, Zong Ke, Shengwei Fu et al.
DisCo DETR: Distance-aware Multi-view Contrastive Learning for DETR Pre-training
Chao Ouyang, Yuyang Bai, Jun Zhang et al.
ParaDySe: A Parallel Strategy Switching Framework for Dynamic Sequences in Transformer-based Large Language Models
Zhixin Ou, Peng Liang, Linbo Qiao et al.
The Strong Lottery Ticket Hypothesis for Multi-Head Attention Mechanisms
Hikari Otsuka, Daiki Chijiwa, Yasuyuki Okoshi et al.
Large Language Models Meet Extreme Multi-label Classification: Scaling and Multi-modal Framework
Diego Ortego, Marlon Rodríguez, Mario Almagro et al.
Computing Probabilistic Explanations for ML Models: Fixed-Parameter Algorithms
Sebastian Ordyniak, Mateusz Rychlicki, Stefan Szeider
Do It for HER: First-Order Temporal Logic Reward Specification in Reinforcement Learning
Pierriccardo Olivieri, Fausto Lasca, Alessandro Gianola et al.
Task Prototype-Based Knowledge Retrieval for Multi-Task Learning from Partially Annotated Data
Youngmin Oh, Hyung-Il Kim, Jung Uk Kim
FlowPath: Learning Data-Driven Manifolds with Invertible Flows for Robust Irregularly-sampled Time Series Classification
YongKyung Oh, Dong-Young Lim, Sungil Kim
Object-Centric World Models for Causality-Aware Reinforcement Learning
Yosuke Nishimoto, Takashi Matsubara
Mitigating Endogenous Confirmation Bias in Noisy Label Learning for Vision-Language Models
Feiyang Ning, Xinyang Chen