activity
20162026
most citedMemory-Guided Multi-View Multi-Domain Fake News Detection

139 citations · 262 across the 50 of their papers we have counts for

collaborators

52 papers

cs.RO2026

NaviScale: Generating Large-Scale Semantic Map Datasets for Object Navigation

Chuanlin Lan, Yanwei Zheng, Weijian Liu +4

Embodied navigation requires spatial representations that generalize across unseen environments, yet collecting large amounts of annotated data from real 3D environments is difficu…

cs.LG2026

WDL-OPD: Weak-Driven On-Policy Distillation via Mixture-Constrained Co-Training

Zehao Chen, Gongxun Li, Tianxiang Ai +9

On-policy distillation (OPD) aligns a student with a teacher on trajectories sampled from the student itself, reducing the train-test state mismatch of offline distillation. The sa…

cs.CL2026

D2C-Routing: Dimension-to-Composition Evidence Routing for Mixed-Origin AI-Generated Text Detection

Xin Chen, Fuwei Zhang, Yiqi Tong +3

AI-generated text detection is commonly framed as a binary document-level judgment about whether a text is human-written or machine-generated. This framing breaks down for mixed-or…

cs.IR2026

Requirement--Evidence Alignment for Compositional E-Commerce Queries

Weihao Shen, Wei Chen, Fuwei Zhang +6

Compositional e-commerce queries express multiple requirements that must hold jointly, yet existing rerankers collapse these constraints into aggregate relevance and often promote…

cs.IR2026

Unpaired Modality-Agnostic Generative Recommendation

Weihao Shen, Wei Chen, Fuwei Zhang +6

Generative Recommendation (GR) formulates recommendation as autoregressive generation over discrete semantic identifiers (IDs). Although recent multimodal GR methods improve semant…

cs.IR2026

Beyond Matching: Category-Guided Latent Intent Reasoning for Generative Retrieval in E-Commerce

Fuwei Zhang, Xiaoyu Liu, Jiajie Jin +8

Generative retrieval offers a new paradigm for e-commerce search by mapping user queries directly to product Semantic Identifiers (SIDs). However, e-commerce queries are often shor…