21 citations · 27 across the 8 of their papers we have counts for
9 papers
TPO: Uncertainty-Guided Exploration Control for Stable Multi-Turn Agentic Reinforcement Learning
Haixin Wang, Hejie Cui, Chenwei Zhang +7
Recent progress in multi-turn reinforcement learning (RL) has significantly improved reasoning LLMs' performances on complex interactive tasks. Despite advances in stabilization te…
SynPlanResearch-R1: Encouraging Tool Exploration for Deep Research with Synthetic Plans
Hansi Zeng, Zoey Li, Yifan Gao +7
Research Agents enable models to gather information from the web using tools to answer user queries, requiring them to dynamically interleave internal reasoning with tool use. Whil…
PersonaAgent: Bridging Memory and Action for Personalized LLM Agents
Weizhi Zhang, Xinyang Zhang, Chenwei Zhang +12
Large Language Model (LLM) empowered agents have recently emerged as advanced paradigms that exhibit impressive capabilities in a wide range of domains and tasks. Despite their pot…
Shopping MMLU: A Massive Multi-Task Online Shopping Benchmark for Large Language Models
Yilun Jin, Zheng Li, Chenwei Zhang +19
Online shopping is a complex multi-task, few-shot learning problem with a wide and evolving range of entities, relations, and tasks. However, existing models and benchmarks are com…
Concept2Box: Joint Geometric Embeddings for Learning Two-View Knowledge Graphs
Zijie Huang, Daheng Wang, Binxuan Huang +8
Knowledge graph embeddings (KGE) have been extensively studied to embed large-scale relational data for many real-world applications. Existing methods have long ignored the fact ma…
PV2TEA: Patching Visual Modality to Textual-Established Information Extraction
Hejie Cui, Rongmei Lin, Nasser Zalmout +4
Information extraction, e.g., attribute value extraction, has been extensively studied and formulated based only on text. However, many attributes can benefit from image-based extr…
Towards Open-World Product Attribute Mining: A Lightly-Supervised Approach
Liyan Xu, Chenwei Zhang, Xian Li +2
We present a new task setting for attribute mining on e-commerce products, serving as a practical solution to extract open-world attributes without extensive human intervention. Ou…
OA-Mine: Open-World Attribute Mining for E-Commerce Products with Weak Supervision
Xinyang Zhang, Chenwei Zhang, Xian Li +4
Automatic extraction of product attributes from their textual descriptions is essential for online shopper experience. One inherent challenge of this task is the emerging nature of…
Minimally-Supervised Structure-Rich Text Categorization via Learning on Text-Rich Networks
Xinyang Zhang, Chenwei Zhang, Luna Xin Dong +2
Text categorization is an essential task in Web content analysis. Considering the ever-evolving Web data and new emerging categories, instead of the laborious supervised setting, i…