We study the reinforcement learning problem of complex action control in the Multi-player
Online Battle Arena (MOBA) 1v1 games. This problem involves far more complicated state and …

MOBA games, eg, Honor of Kings, League of Legends, and Dota 2, pose grand challenges
to AI systems such as multi-agent, enormous state-action space, complex action control, etc. …

We present JueWu-SL, the first supervised-learning-based artificial intelligence (AI)
program that achieves human-level performance in playing multiplayer online battle arena (MOBA) …

Recently, many researchers have made successful progress in building the AI systems for
MOBA-game-playing with deep reinforcement learning, such as on Dota 2 and Honor of Kings…

Text categorization, or text classification, is one of key tasks for representing the semantic
information of documents. Multi-label text categorization is finer-grained approach to text …

We find that, simply via a sampling-and-voting method, the performance of large language
models (LLMs) scales with the number of agents instantiated. Also, this method, termed as …

Reinforcement learning competitions advance the field by providing appropriate scope and
support to develop solutions toward a specific problem. To promote the development of more …

Transformer has been considered the dominating neural architecture in NLP and CV, mostly
under supervised settings. Recently, a similar surge of using Transformers has appeared in …

Consider a question and its answers in Stack Overflow as a knowledge unit. Knowledge
units often contain semantically relevant knowledge, and thus linkable for different purposes, …

The goal of program synthesis, or code generation, is to generate executable code based
on given descriptions. Recently, there has been an increasing number of studies employing …