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WenLi Du

6 accepted papers

2026

From Text to Simulation: A Multi-Agent LLM Workflow for Automated Chemical Process Design

AAAI 2026technical

Process simulation is a critical cornerstone of chemical engineering design. Current automated chemical design methodologies focus mainly on various representations of process flow diagrams. However, transforming these diagrams into executable simulation flowsheets remains a time-consuming and labor

Cited by 0SourcePDFScholar
2025

Neural Architecture Search Driven by Locally Guided Diffusion for Personalized Federated Learning

ICCV 2025poster

Neural Architecture Search (NAS) has gained significant attention in personalized federated learning (PFL) due to its ability to automatically design tailored models for individual clients. While most existing NAS approaches for PFL perform architecture search on the server side, client-side NAS--wh…

Cited by 0SourcePDFScholar
2025

Noise-Resistant Video Anomaly Detection via RGB Error-Guided Multiscale Predictive Coding and Dynamic Memory

CVPR 2025poster

Due to the interference of background noise, existing video anomaly detection methods are prone to detect some normal events in complex scenes as anomalies. Meanwhile, we note that the diversity of normal patterns has not been adequately considered, i.e., the normal events that are worthy of referen…

Cited by 0SourcePDFScholar
2024

ZSEE: A Dataset based on Zeolite Synthesis Event Extraction for Automated Synthesis Platform

NAACL 2024findings

Automated synthesis of zeolite, one of the most important catalysts in chemical industries, holds great significance for attaining economic and environmental benefits. Structural synthesis data extracted through NLP technologies from zeolite experimental procedures can significantly expedite automat…

2023

EMT-NAS:Transferring Architectural Knowledge Between Tasks From Different Datasets

CVPR 2023poster

The success of multi-task learning (MTL) can largely be attributed to the shared representation of related tasks, allowing the models to better generalise. In deep learning, this is usually achieved by sharing a common neural network architecture and jointly training the weights. However, the joint…