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Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction

A Circuit Domain Generalization Framework for Efficient Logic Synthesis in Chip Design

A Hierarchical Adaptive Multi-Task Reinforcement Learning Framework for Multiplier Circuit Design

Accelerating PDE Data Generation via Differential Operator Action in Solution Space

Coarse-to-Fine Highlighting: Reducing Knowledge Hallucination in Large Language Models

Reinforcement Learning within Tree Search for Fast Macro Placement

Towards General Algorithm Discovery for Combinatorial Optimization: Learning Symbolic Branching Policy from Bipartite Graph

SAC-KG: Exploiting Large Language Models as Skilled Automatic Constructors for Domain Knowledge Graph

Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling (Spotlight)

Rethinking Branching on Exact Combinatorial OPtimization Solver: The First Deep Symbolic Discovery Framework