activity
20242026
most citedTree-based Ensemble Learning for Out-of-distribution Detection

1 citations · 1 across the 7 of their papers we have counts for

collaborators

10 papers

cs.AI2026

ShopSimulator: Evaluating and Exploring RL-Driven LLM Agent for Shopping Assistants

Pei Wang, Yanan Wu, Xiaoshuai Song +13

Large language model (LLM)-based agents are increasingly deployed in e-commerce shopping. To perform thorough, user-tailored product searches, agents should interpret personal pref…

cs.AI2026

GDEPO: Group Dual-dynamic and Equal-right Advantage Policy Optimization with Enhanced Training Data Utilization for Sample-Constrained Reinforcement Learning

Zhengqing Yan, Xinyang Liu, Yi Zhang +7

Automated Theorem Proving (ATP) represents a fundamental challenge in Artificial Intelligence (AI), requiring the construction of machine-verifiable proofs in formal languages such…

stat.ME2025

MMDCP: A Distribution-free Approach to Outlier Detection and Classification with Coverage Guarantees and SCW-FDR Control

Youwu Lin, Xiaoyu Qian, Jinru Wu +2

We propose the Modified Mahalanobis Distance Conformal Prediction (MMDCP), a unified framework for multi-class classification and outlier detection under label shift, where the tra…

cs.CV2025

HQ-OV3D: A High Box Quality Open-World 3D Detection Framework based on Diffision Model

Qi Liu, Yabei Li, Hongsong Wang +1

Traditional closed-set 3D detection frameworks fail to meet the demands of open-world applications like autonomous driving. Existing open-vocabulary 3D detection methods typically…

cs.CL2025

Exploring Stability-Plasticity Trade-offs for Continual Named Entity Recognition

Duzhen Zhang, Chenxing Li, Jiahua Dong +2

Continual Named Entity Recognition (CNER) is an evolving field that focuses on sequentially updating an existing model to incorporate new entity types. Previous CNER methods primar…

cs.CV2025

Show and Polish: Reference-Guided Identity Preservation in Face Video Restoration

Wenkang Han, Wang Lin, Yiyun Zhou +4

Face Video Restoration (FVR) aims to recover high-quality face videos from degraded versions. Traditional methods struggle to preserve fine-grained, identity-specific features when…