most citedPaper2Agent: Reimagining Research Papers As Interactive and Reliable AI Agents

3 citations · 7 across the 5 of their papers we have counts for

collaborators

9 papers

cs.AI2026

What LLMs Think When You Don't Tell Them What to Think About?

Yongchan Kwon, James Zou

Characterizing the behavior of large language models (LLMs) across diverse settings is critical for reliable monitoring and AI safety. However, most existing analyses rely on topic…

q-bio.OT2025

A Roadmap for Predictive Human Immunology

Aly A. Khan, Jason Perera, James Zou +13

For over a century, immunology has masterfully discovered and dissected the components of our immune system, yet its collective behavior remains fundamentally unpredictable. In thi…

cs.AI20253 cited

Paper2Agent: Reimagining Research Papers As Interactive and Reliable AI Agents

Jiacheng Miao, Joe R. Davis, Yaohui Zhang +2

We introduce Paper2Agent, an automated framework that converts research papers into AI agents. Paper2Agent transforms research output from passive artifacts into active systems tha…

cs.AI2025

Inefficiencies of Meta Agents for Agent Design

Batu El, Mert Yuksekgonul, James Zou

Recent works began to automate the design of agentic systems using meta-agents that propose and iteratively refine new agent architectures. In this paper, we examine three key chal…

cs.AI20251 cited

Moloch's Bargain: Emergent Misalignment When LLMs Compete for Audiences

Batu El, James Zou

Large language models (LLMs) are increasingly shaping how information is created and disseminated, from companies using them to craft persuasive advertisements, to election campaig…

cs.CV2025

4KAgent: Agentic Any Image to 4K Super-Resolution

Yushen Zuo, Qi Zheng, Mingyang Wu +10

We present 4KAgent, a unified agentic super-resolution generalist system designed to universally upscale any image to 4K resolution (and even higher, if applied iteratively). Our s…