6 papers
Trade in Minutes! Rationality-Driven Agentic System for Quantitative Financial Trading
Zifan Song, Kaitao Song, Guosheng Hu +5
Recent advancements in large language models (LLMs) and agentic systems have shown exceptional decision-making capabilities, revealing significant potential for autonomic finance.…
Enhancing User Engagement in Socially-Driven Dialogue through Interactive LLM Alignments
Jiashuo Wang, Kaitao Song, Chunpu Xu +5
Enhancing user engagement through interactions plays an essential role in socially-driven dialogues. While prior works have optimized models to reason over relevant knowledge or pl…
Chain-of-Model Learning for Language Model
Kaitao Song, Xiaohua Wang, Xu Tan +14
In this paper, we propose a novel learning paradigm, termed Chain-of-Model (CoM), which incorporates the causal relationship into the hidden states of each layer as a chain style,…
EvoAgent: Towards Automatic Multi-Agent Generation via Evolutionary Algorithms
Siyu Yuan, Kaitao Song, Jiangjie Chen +3
The rise of powerful large language models (LLMs) has spurred a new trend in building LLM-based autonomous agents for solving complex tasks, especially multi-agent systems. Despite…
TaskBench: Benchmarking Large Language Models for Task Automation
Yongliang Shen, Kaitao Song, Xu Tan +6
In recent years, the remarkable progress of large language models (LLMs) has sparked interest in task automation, which involves decomposing complex tasks described by user instruc…
Can Graph Learning Improve Planning in LLM-based Agents?
Xixi Wu, Yifei Shen, Caihua Shan +8
Task planning in language agents is emerging as an important research topic alongside the development of large language models (LLMs). It aims to break down complex user requests i…