2 citations · 2 across the 12 of their papers we have counts for
12 papers
From Economic Agents to Agentic Economies: A Systems Blueprint for Economic World Models
Jiale Han, Xiang Li, Jing Qian +7
Economic World Models (EWMs) are generative economic models that simulate how economies evolve from within by modeling heterogeneous agents, their beliefs and actions, and the mark…
Agent-UCT: Upper Confidence Bounds Applied to Trees for Cost-Aware Agentic Workflow Optimization
Yang Li, Hai Liu, Dian Shao +9
Workflow search pays for complete quality observations, whose execution cost changes as reusable prefixes accumulate. AgentUCT uses an economic model of the remaining evaluation co…
StateFuse: Deterministic Conflict-Preserving Memory for Multi-Agent Systems
Sergey Volkov, Yang Li, Ye Luo
Agent systems accumulate conflicting observations across branches, retries, and replicas, yet many practical memory layers still collapse disagreement behind overwrite rules that a…
Uncertainty-Adjusted Sorting for Asset Pricing with Machine Learning
Yan Liu, Ye Luo, Zigan Wang +1
Machine learning is central to empirical asset pricing, but portfolio construction still relies on point predictions and largely ignores asset-specific estimation uncertainty. We p…
AgentGit: A Version Control Framework for Reliable and Scalable LLM-Powered Multi-Agent Systems
Yang Li, Siqi Ping, Xiyu Chen +4
With the rapid progress of large language models (LLMs), LLM-powered multi-agent systems (MAS) are drawing increasing interest across academia and industry. However, many current M…
Hierarchical AI Multi-Agent Fundamental Investing: Evidence from China's A-Share Market
Chujun He, Zhonghao Huang, Xiangguo Li +5
We present a multi-agent, AI-driven framework for fundamental investing that integrates macro indicators, industry-level and firm-specific information to construct optimized equity…
Meta-Policy Reflexion: Reusable Reflective Memory and Rule Admissibility for Resource-Efficient LLM Agent
Chunlong Wu, Ye Luo, Zhibo Qu +1
Large language model (LLM) agents achieve impressive single-task performance but commonly exhibit repeated failures, inefficient exploration, and limited cross-task adaptability. E…
Can AI Master Econometrics? Evidence from Econometrics AI Agent on Expert-Level Tasks
Qiang Chen, Tianyang Han, Jin Li +5
Can AI effectively perform complex econometric analysis traditionally requiring human expertise? This paper evaluates AI agents' capability to master econometrics, focusing on empi…
OpenAI-o1 AB Testing: Does the o1 model really do good reasoning in math problem solving?
Leo Li, Ye Luo, Tingyou Pan
The Orion-1 model by OpenAI is claimed to have more robust logical reasoning capabilities than previous large language models. However, some suggest the excellence might be partial…
Seesaw Experimentation: A/B Tests with Spillovers
Jin Li, Ye Luo, Xiaowei Zhang
This paper examines how spillover effects in A/B testing can impede organizational progress and develops strategies for mitigating these challenges. We identify a phenomenon termed…
Attribution and Persuasion: The Paradox of Interpretable AI
Hanzhe Li, Jin Li, Ye Luo +1
This paper studies AI persuasion by distinguishing between two reasons for disagreement: attention differences, where the AI detects features the decision-maker missed, and compreh…
Dynamic Selection in Algorithmic Decision-making
Jin Li, Ye Luo, Xiaowei Zhang
This paper identifies and addresses dynamic selection problems in online learning algorithms with endogenous data. In a contextual multi-armed bandit model, a novel bias (self-fulf…