collaborators

5 papers

cs.CL2026

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging

Jie Cao, Zhenxuan Fan, Zhuonan Wang +8

Large language models (LLMs) achieve remarkable performance on diverse downstream and domain-specific tasks via parameter-efficient fine-tuning (PEFT). However, existing PEFT metho…

cs.CL2026

IPS: In-Prompt Process Supervision for Short Video Content Moderation

Mingchao Liu, Yu Sun, Ruixiao Sun +5

Multimodal large language models (MLLMs) are effective at capturing the semantics of short video content; however, they often fail to attend to the policy-specific details required…

cs.AI2026

GAM: Hierarchical Graph-based Agentic Memory for LLM Agents

Zhaofen Wu, Hanrong Zhang, Fulin Lin +9

To sustain coherent long-term interactions, Large Language Model (LLM) agents must navigate the tension between acquiring new information and retaining prior knowledge. Current uni…

cs.CV2026

When Rules Fall Short: Agent-Driven Discovery of Emerging Content Issues in Short Video Platforms

Chenghui Yu, Hongwei Wang, Junwen Chen +5

Trends on short-video platforms evolve at a rapid pace, with new content issues emerging every day that fall outside the coverage of existing annotation policies. However, traditio…

cs.CV2025

Reasoning-Enhanced Domain-Adaptive Pretraining of Multimodal Large Language Models for Short Video Content Governance

Zixuan Wang, Yu Sun, Hongwei Wang +6

Short video platforms are evolving rapidly, making the identification of inappropriate content increasingly critical. Existing approaches typically train separate and small classif…