Attention Network (GA T), a popular GNN architecture in which a node's neighborhood aggregation is weighted by parameterized attention coefficients.

We consider learning a sparse model from linear measurements taken by a network of agents.

Note that these games are two-player games, we select the runner in You-Shall-Not-Pass and kicker in Kick-And-Defend as our target agent. Section 4 mentioned that we download a well-trained policy for each game.

Amidst therecent strides inevaluating LargeLanguage Models forCode (Code LLMs), existing benchmarks havemainly focused onthefunctional correctness of generated code, neglecting the importance of their computational efficiency.

Large language models (LLMs) have shown impressive performance on downstream tasks by in-contextlearning (ICL), which heavily relies on the quality of demonstrations selected from a large set of annotated examples.