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20232026
most citedLightweight and Accurate Multi-View Stereo with Confidence-Aware Diffusion Model

11 citations · 28 across the 29 of their papers we have counts for

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9 papers · 1 filter

cs.LG2026

PromptDyG: Test-Time Prompt Adaptation on Dynamic Graphs

Guoguo Ai, Chaoxi Niu, Hui Yan +3

Activities in numerous evolving systems can be represented as dynamic graphs in snapshot form at different time intervals, i.e., discrete-time dynamic graphs (DTDGs). Existing meth…

cs.LG2025

Distributional Multi-objective Black-box Optimization for Diffusion-model Inference-time Multi-Target Generation

Kim Yong Tan, Yueming Lyu, Ivor Tsang +1

Diffusion models have been successful in learning complex data distributions. This capability has driven their application to high-dimensional multi-objective black-box optimizatio…

cs.LG2025

EvoSpeak: Large Language Models for Interpretable Genetic Programming-Evolved Heuristics

Meng Xu, Jiao Liu, Yew Soon Ong

Genetic programming (GP) has demonstrated strong effectiveness in evolving tree-structured heuristics for complex optimization problems. Yet, in dynamic and large-scale scenarios,…

cs.LG2025

SiamNAS: Siamese Surrogate Model for Dominance Relation Prediction in Multi-objective Neural Architecture Search

Yuyang Zhou, Ferrante Neri, Yew-Soon Ong +1

Modern neural architecture search (NAS) is inherently multi-objective, balancing trade-offs such as accuracy, parameter count, and computational cost. This complexity makes NAS com…

cs.LG2025

MermaidFlow: Redefining Agentic Workflow Generation via Safety-Constrained Evolutionary Programming

Chengqi Zheng, Jianda Chen, Yueming Lyu +5

Despite the promise of autonomous agentic reasoning, existing workflow generation methods frequently produce fragile, unexecutable plans due to unconstrained LLM-driven constructio…

cs.LG2025

Fast Direct: Query-Efficient Online Black-box Guidance for Diffusion-model Target Generation

Kim Yong Tan, Yueming Lyu, Ivor Tsang +1

Guided diffusion-model generation is a promising direction for customizing the generation process of a pre-trained diffusion model to address specific downstream tasks. Existing gu…