activity
20232026
most citedSynthetic Data Generation with Large Language Models for Text Classification: Potential and Limitations

8 citations · 18 across the 13 of their papers we have counts for

collaborators

13 papers

cs.CL2026

Using Grounded Theory for Agent Behavior Analysis at Scale

Zhuoran Lu, Yangyang Yu, Zhuoyan Li +5

Understanding agent behavior requires methods that scale to thousands of trajectories and surface new patterns in long, often unfamiliar tasks where pre-built classifiers fall shor…

cs.HC2026

One AI Signal, Many Human Judgments: A Bayesian Cascade Analysis of AI-based Credibility Indicators in Online Information Spread

Zhuoran Lu, Weilong Wang, Yangyang Yu +4

Social media platforms increasingly use AI-based credibility indicators to help users judge misinformation. Unlike individual human-AI decision-making, these indicators are embedde…

cs.CR2026

Benchmarking Security Risk Detection and Verification in Open Agentic Skill Ecosystems

Ismail Hossain, Sai Puppala, Zhuoran Lu +2

Open agent platforms allow community contributors to publish reusable skills that agents can invoke at runtime. This extensibility also creates a supply-chain risk: malicious contr…

cs.AI2026

How to Interpret Agent Behavior

Jie Gao, Kaiser Sun, Jen-tse Huang +8

Autonomous agents such as Claude Code and Codex now operate for hours or even days. Understanding their runtime behavior has become critical for downstream tasks such as diagnosing…

cs.CE2026

AutoRedTrader: Autonomous Red Teaming of Trading Agents through Synthetic Misinformation Injection

Zhiwei Liu, Yangyang Yu, Yupeng Cao +8

LLM-based financial agents increasingly rely on both numerical market data and textual signals for sequential trading and stock prediction. However, financial misinformation often…

cs.LG2026

Human-LLM Collaborative Feature Engineering for Tabular Data

Zhuoyan Li, Aditya Bansal, Jinzhao Li +8

Large language models (LLMs) are increasingly used to automate feature engineering in tabular learning. Given task-specific information, LLMs can propose diverse feature transforma…

cs.HC2025

WhatELSE: Shaping Narrative Spaces at Configurable Level of Abstraction for AI-bridged Interactive Storytelling

Zhuoran Lu, Qian Zhou, Yi Wang

Generative AI significantly enhances player agency in interactive narratives (IN) by enabling just-in-time content generation that adapts to player actions. While delegating genera…

cs.HC2025★ 2 cited

From Text to Trust: Empowering AI-assisted Decision Making with Adaptive LLM-powered Analysis

Zhuoyan Li, Hangxiao Zhu, Zhuoran Lu +2

AI-assisted decision making becomes increasingly prevalent, yet individuals often fail to utilize AI-based decision aids appropriately especially when the AI explanations are absen…

cs.HC2024★ 1 cited

Corporate Communication Companion (CCC): An LLM-empowered Writing Assistant for Workplace Social Media

Zhuoran Lu, Sheshera Mysore, Tara Safavi +3

Workplace social media platforms enable employees to cultivate their professional image and connect with colleagues in a semi-formal environment. While semi-formal corporate commun…

cs.HC2024★ 2 cited

Does More Advice Help? The Effects of Second Opinions in AI-Assisted Decision Making

Zhuoran Lu, Dakuo Wang, Ming Yin

AI assistance in decision-making has become popular, yet people's inappropriate reliance on AI often leads to unsatisfactory human-AI collaboration performance. In this paper, thro…

cs.HC2024

Decoding AI's Nudge: A Unified Framework to Predict Human Behavior in AI-assisted Decision Making

Zhuoyan Li, Zhuoran Lu, Ming Yin

With the rapid development of AI-based decision aids, different forms of AI assistance have been increasingly integrated into the human decision making processes. To best support h…

cs.CL2023★ 5 cited

Pearl: Personalizing Large Language Model Writing Assistants with Generation-Calibrated Retrievers

Sheshera Mysore, Zhuoran Lu, Mengting Wan +7

Powerful large language models have facilitated the development of writing assistants that promise to significantly improve the quality and efficiency of composition and communicat…

cs.CL2023★ 8 cited

Synthetic Data Generation with Large Language Models for Text Classification: Potential and Limitations

Zhuoyan Li, Hangxiao Zhu, Zhuoran Lu +1

The collection and curation of high-quality training data is crucial for developing text classification models with superior performance, but it is often associated with significan…