1 citations · 1 across the 19 of their papers we have counts for
19 papers
CNeo-Bench: Diagnosing Large Language Models on Chinese Neologisms
Kaiyan Zhao, Zhongtao Miao, Zheyong Xie +2
Chinese neologisms exploit diverse and unique linguistic mechanisms, such as phonetic substitution (e.g., 886 for ``bye-bye'') and visual character decomposition that are rare in o…
MedUAG: Unified Understanding and Generation for Medical Multimodal Models
Zijie Meng, Yuncheng Zhang, Hualiang Wang +8
Recent Multimodal Large Language Models (MLLMs) are rapidly evolving into unified understanding and generation (UAG) frameworks. However, extending these unified paradigms to the m…
DentAgent: Evidence-Centric Multi-Agent Coordination for Multimodal Dental Reasoning
Zijie Meng, Xiwei Dai, Yixuan Tang +6
Oral diseases affect billions of people worldwide, underscoring a pressing need for accurate and reliable dental assessment that integrates heterogeneous evidence from domain knowl…
GCAgent: Enhancing Group Chat Communication through Dialogue Agents System
Zijie Meng, Zheyong Xie, Zheyu Ye +5
As a key form in online social platforms, group chat is a popular space for interest exchange or problem-solving, but its effectiveness is often hindered by inactivity and manageme…
Vision-DeepResearch Benchmark: Rethinking Visual and Textual Search for Multimodal Large Language Models
Yu Zeng, Wenxuan Huang, Zhen Fang +14
Multimodal Large Language Models (MLLMs) have advanced VQA and now support Vision-DeepResearch systems that use search engines for complex visual-textual fact-finding. However, eva…
QP-OneModel: A Unified Generative LLM for Multi-Task Query Understanding in Xiaohongshu Search
Jianzhao Huang, Xiaorui Huang, Fei Zhao +9
Query Processing (QP) bridges user intent and content supply in large-scale Social Network Service (SNS) search engines. Traditional QP systems rely on pipelines of isolated discri…
Balancing Understanding and Generation in Discrete Diffusion Models
Yue Liu, Yuzhong Zhao, Zheyong Xie +5
In discrete generative modeling, two dominant paradigms demonstrate divergent capabilities: Masked Diffusion Language Models (MDLM) excel at semantic understanding and zero-shot ge…
Decouple Searching from Training: Scaling Data Mixing via Model Merging for Large Language Model Pre-training
Shengrui Li, Fei Zhao, Kaiyan Zhao +6
Determining an effective data mixture is a key factor in Large Language Model (LLM) pre-training, where models must balance general competence with proficiency on hard tasks such a…
EComStage: Stage-wise and Orientation-specific Benchmarking for Large Language Models in E-commerce
Kaiyan Zhao, Zijie Meng, Zheyong Xie +4
Large Language Model (LLM)-based agents are increasingly deployed in e-commerce applications to assist customer services in tasks such as product inquiries, recommendations, and or…
Benchmarking Machine Translation on Chinese Social Media Texts
Kaiyan Zhao, Zheyong Xie, Zhongtao Miao +3
The prevalence of rapidly evolving slang, neologisms, and highly stylized expressions in informal user-generated text, particularly on Chinese social media, poses significant chall…
Robust Tool Use via Fission-GRPO: Learning to Recover from Execution Errors
Zhiwei Zhang, Fei Zhao, Rui Wang +6
Large language models (LLMs) can call tools effectively, yet they remain brittle in multi-turn execution: after a tool-call error, smaller models often fall into repetitive invalid…
Optimizing Generative Ranking Relevance via Reinforcement Learning in Xiaohongshu Search
Ziyang Zeng, Heming Jing, Jindong Chen +11
Ranking relevance is a fundamental task in search engines, aiming to identify the items most relevant to a given user query. Traditional relevance models typically produce scalar s…
Interleaving Reasoning for Better Text-to-Image Generation
Wenxuan Huang, Shuang Chen, Zheyong Xie +15
Unified multimodal understanding and generation models recently have achieve significant improvement in image generation capability, yet a large gap remains in instruction followin…
AgentGroupChat-V2: Divide-and-Conquer Is What LLM-Based Multi-Agent System Need
Zhouhong Gu, Xiaoxuan Zhu, Yin Cai +12
Large language model based multi-agent systems have demonstrated significant potential in social simulation and complex task resolution domains. However, current frameworks face cr…
MT: Scaling MLLM-based Text Image Machine Translation via Multi-Task Reinforcement Learning
Zhaopeng Feng, Yupu Liang, Shaosheng Cao +7
Text Image Machine Translation (TIMT)-the task of translating textual content embedded in images-is critical for applications in accessibility, cross-lingual information access, an…
PaRT: Enhancing Proactive Social Chatbots with Personalized Real-Time Retrieval
Zihan Niu, Zheyong Xie, Shaosheng Cao +9
Social chatbots have become essential intelligent companions in daily scenarios ranging from emotional support to personal interaction. However, conventional chatbots with passive…
MT-R1-Zero: Advancing LLM-based Machine Translation via R1-Zero-like Reinforcement Learning
Zhaopeng Feng, Shaosheng Cao, Jiahan Ren +7
Large-scale reinforcement learning (RL) methods have proven highly effective in enhancing the reasoning abilities of large language models (LLMs), particularly for tasks with verif…
Qilin: A Multimodal Information Retrieval Dataset with APP-level User Sessions
Jia Chen, Qian Dong, Haitao Li +9
User-generated content (UGC) communities, especially those featuring multimodal content, improve user experiences by integrating visual and textual information into results (or ite…
ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval
Suyuan Huang, Chao Zhang, Yuanyuan Wu +12
Dense retrieval in most industries employs dual-tower architectures to retrieve query-relevant documents. Due to online deployment requirements, existing real-world dense retrieval…