2 citations · 4 across the 11 of their papers we have counts for
5 papers · 1 filter
Towards Effective Model Editing for LLM Personalization
Baixiang Huang, Limeng Cui, Jiapeng Liu +7
Personalization is becoming indispensable for LLMs to align with individual user preferences and needs. Yet current approaches are often computationally expensive, data-intensive,…
Fine-grained text-driven dual-human motion generation via dynamic hierarchical interaction
Mu Li, Yin Wang, Zhiying Leng +3
Human interaction is inherently dynamic and hierarchical, where the dynamic refers to the motion changes with distance, and the hierarchy is from individual to inter-individual and…
ChemActor: Enhancing Automated Extraction of Chemical Synthesis Actions with LLM-Generated Data
Yu Zhang, Ruijie Yu, Jidong Tian +5
With the increasing interest in robotic synthesis in the context of organic chemistry, the automated extraction of chemical procedures from literature is critical. However, this ta…
AgentA/B: Automated and Scalable Web A/BTesting with Interactive LLM Agents
Yuxuan Lu, Ting-Yao Hsu, Hansu Gu +9
A/B testing experiment is a widely adopted method for evaluating UI/UX design decisions in modern web applications. Yet, traditional A/B testing remains constrained by its dependen…
Fg-T2M++: LLMs-Augmented Fine-Grained Text Driven Human Motion Generation
Yin Wang, Mu Li, Jiapeng Liu +4
We address the challenging problem of fine-grained text-driven human motion generation. Existing works generate imprecise motions that fail to accurately capture relationships spec…