From the 1 of 8 linked papers with an AI index.
8 papers
MUGEN: A Unified Framework for Efficient Motion Understanding and Generation
Zhankai Ye, Yukai Jin, Bingyang Wei +5
The paper introduces MUGEN, a unified framework that uses a single adaptive-length autoencoder to compress human motion into continuous latent slots, enabling efficient text-to-mot…
HCAG: Hierarchical Abstraction and Retrieval-Augmented Generation on Theoretical Repositories with LLMs
Yusen Wu, Xiaotie Deng
Existing Retrieval-Augmented Generation (RAG) methods for code struggle to capture the high-level architectural patterns and cross-file dependencies inherent in complex, theory-dri…
MALLES: A Multi-agent LLMs-based Economic Sandbox with Consumer Preference Alignment
Yusen Wu, Yiran Liu, Xiaotie Deng
In the real economy, modern decision-making is fundamentally challenged by high-dimensional, multimodal environments, which are further complicated by agent heterogeneity and combi…
DeepRule: An Integrated Framework for Automated Business Rule Generation via Deep Predictive Modeling and Hybrid Search Optimization
Yusen Wu, Xiaotie Deng
This paper proposes DeepRule, an integrated framework for automated business rule generation in retail assortment and pricing optimization. Addressing the systematic misalignment b…
Hummer: Towards Limited Competitive Preference Dataset
Li Jiang, Yusen Wu, Junwu Xiong +6
Preference datasets are essential for incorporating human preferences into pre-trained language models, playing a key role in the success of Reinforcement Learning from Human Feedb…
Game Theory Meets Large Language Models: A Systematic Survey with Taxonomy and New Frontiers
Haoran Sun, Yusen Wu, Peng Wang +4
Game theory is a foundational framework for analyzing strategic interactions, and its intersection with large language models (LLMs) is a rapidly growing field. However, existing s…