6 papers
LiveSearch: Questions as Executable Verifier Code for a Live Benchmark of Professional-Source Financial Search Agents
Sinuo Wang, Wentao Zhao, Jiacheng Lu +6
In finance, the answer that matters is usually the current one: prices, rates, and disclosures hold only as of a given day, so retrieving up-to-date facts is a core capability of a…
From Search to Research: Exploring Search Scaling in Autonomous Quantitative Factor Mining
Kangcheng Deng, Hui Cai, Jiacheng Lu +6
Inference scaling has been shown to improve large language model (LLM) performance, and this principle naturally extends to autonomous LLM agents through increased search budgets,…
CalibratedRubric: Task-Adaptive Rubric Banks for Open-Ended LLM Evaluation
Mengting Chen, Yanshu Sun, Wanting Liang +5
Reliable evaluation of open-ended LLM outputs requires fine-grained rubrics, yet expert curation is costly and difficult to scale. Existing automated pipelines rely on strict judge…
One Analyst Is Not Ground Truth: Grading Agent-Built Financial Models Against Observed Professional Practice
Jiacheng Lu, Sinuo Wang, Yiming Li +15
Language model agents can now construct complete financial models, but it remains unclear whether they have learned the financial judgment that gives those models meaning. Existing…
FinResearchBench II: A Deep Research Benchmark with Consensus-Derived Gold Rubrics for Distinguishing Financial Report Quality
Beidi Luan, Rui Sun, Sinuo Wang +5
Deep research agents are increasingly used to produce long-form financial reports, yet large-scale evaluation remains bottlenecked by the need for human experts to define and execu…
From Knowing to Doing: A Memory-Controlled Benchmark for LLM Trading Agents on Stock Markets
Taojie Zhu, Wentao Zhao, Rui Sun +7
Evaluating whether large language model (LLM) agents can profit in capital markets is increasingly framed as end-to-end trading: place an agent in a historical market, let it trade…