6 papers
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…
Trade-R1: Bridging Verifiable Rewards to Stochastic Environments via Process-Level Reasoning Verification
Rui Sun, Yifan Sun, Sheng Xu +5
Reinforcement Learning (RL) has enabled Large Language Models (LLMs) to achieve remarkable reasoning in domains like mathematics and coding, where verifiable rewards provide clear…
Alpha-R1: Alpha Screening with LLM Reasoning via Reinforcement Learning
Zuoyou Jiang, Li Zhao, Rui Sun +6
Signal decay and regime shifts pose recurring challenges for data-driven investment strategies in non-stationary markets, where conventional time-series and machine learning approa…