1 citations · 1 across the 9 of their papers we have counts for
10 papers
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…
State-Robust Nash Predictions In Population Games
Rui Sun, Junfei Guo
This paper introduces state-robust equilibrium (SRE), a local validity test for Nash predictions in finite-strategy population games when the payoff-relevant aggregate state may be…
AdaTIR: Adaptive Tool-Integrated Reasoning via Difficulty-Aware Policy Optimization
Zhaiyu Fang, Ruipeng Sun
Tool-Integrated Reasoning (TIR) has significantly enhanced the capabilities of Large Language Models (LLMs), yet current agents tend to exhibit cognitive offloading, redundantly in…
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…
ContestTrade: A Multi-Agent Trading System Based on Internal Contest Mechanism
Li Zhao, Rui Sun, Zuoyou Jiang +5
In financial trading, large language model (LLM)-based agents demonstrate significant potential, but their decisions can be sensitive to noisy and non-stationary market information…
FinResearchBench: A Logic Tree based Agent-as-a-Judge Evaluation Framework for Financial Research Agents
Rui Sun, Zuo Bai, Wentao Zhang +4
Recently, AI agents are rapidly evolving in intelligence and widely used in professional research applications, such as STEM, software development, and finance. Among these AI agen…