17 citations · 22 across the 32 of their papers we have counts for
7 papers · 1 filter
Can Agentic Trading Systems Pay for Their Own Intelligence?
Qiqi Duan, Changlun Li, Chen Wang +10
Large language model (LLM) agents are increasingly used in trading systems, where model reasoning, tool use, and continual decisions incur costs that are expected to produce tradin…
Monte Carlo Tree Search for Table-to-Multimodal Report Generation
Teng Lin, Zhiyang Zhang, Yuyu Luo +1
Automatically generating professional multimodal reports comprising both textual analysis and visual charts from structured tabular data is a critical challenge in data intelligenc…
DataSpace: Benchmarking Data Agents for Verifiable Analytics over Heterogeneous Workspaces
Boyan Li, Zhuowen Liang, Yupeng Xie +11
Data agents enable natural-language analytics over organizational workspaces, where relevant evidence may be scattered across databases, structured files, long documents, and multi…
EVOQUANT: Self-Evolving Verifier-Guided Strategy Optimization for Robust Quantitative Trading
Jie Mao, Changlun Li, Xiang Li +6
Quantitative strategy optimization remains largely manual, requiring domain experts to identify weak signals, tune risk-control rules, and repeatedly validate iterative revisions.…
CSTrader: A Testbed for Language-Grounded Trading in a Community-Driven Virtual Asset Market
Yao Shi, Kingfung Luo, Nan Tang +1
Niche asset markets, such as Counter-Strike 2 (CS2) weapon skins, are small, volatile, and heavily driven by community discussions and platform rules. These properties make them ha…
DocSage: An Information Structuring Agent for Multi-Doc Multi-Entity Question Answering
Teng Lin, Yizhang Zhu, Zhengxuan Zhang +2
Multi-document Multi-entity Question Answering inherently demands models to track implicit logic between multiple entities across scattered documents. However, existing Large Langu…
Concise Reasoning, Big Gains: Pruning Long Reasoning Trace with Difficulty-Aware Prompting
Yifan Wu, Jingze Shi, Bingheng Wu +4
Existing chain-of-thought (CoT) distillation methods can effectively transfer reasoning abilities to base models but suffer from two major limitations: excessive verbosity of reaso…