11 citations · 11 across the 5 of their papers we have counts for
5 papers
CompEvo: Competition-Induced Evolution for Multi-Agent in News-Driven Time Series Forecasting
Yuxuan Zhang, Yangyang Feng, Yong Guan +6
News-driven time series forecasting uses evolving textual events together with historical observations to predict future values, supporting applications such as market risk monitor…
Two-way Evidence self-Alignment based Dual-Gated Reasoning Enhancement
Kexin Zhang, Junlan Chen, Daifeng Li +4
Large language models (LLMs) encounter difficulties in knowledge-intensive multi-step reasoning (KIMSR) tasks. One challenge is how to effectively extract and represent rationale e…
Can Competition Enhance the Proficiency of Agents Powered by Large Language Models in the Realm of News-driven Time Series Forecasting?
Yuxuan Zhang, Yangyang Feng, Daifeng Li +3
Multi-agents-based news-driven time series forecasting is considered as a potential paradigm shift in the era of large language models (LLMs). The challenge of this task lies in me…
Structuring Scientific Innovation: A Framework for Modeling and Discovering Impactful Knowledge Combinations
Junlan Chen, Kexin Zhang, Daifeng Li +3
The emergence of large language models offers new possibilities for structured exploration of scientific knowledge. Rather than viewing scientific discovery as isolated ideas or co…
Media Bias Detector: Designing and Implementing a Tool for Real-Time Selection and Framing Bias Analysis in News Coverage
Jenny S Wang, Samar Haider, Amir Tohidi +5
Mainstream media, through their decisions on what to cover and how to frame the stories they cover, can mislead readers without using outright falsehoods. Therefore, it is crucial…