// CMU CS · MULTI-AGENT LLM SYSTEMS · AI SAFETY

Jerick Shi

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Portrait of Jerick Shi
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01 about

Hi, I'm Jerick.

I'm a recent graduate of Carnegie Mellon University's MSCS program (2026), where my research focused on Multi-Agent LLM Systems and AI Safety.

My master's thesis examined deceptive behaviors in multi-agent LLM systems, co-advised by Vincent Conitzer (CMU) and Zhijing Jin (University of Toronto). I also work remotely as an external collaborator for the Jinesis Lab.

During my undergrad at CMU, I completed majors in both Computer Science and Mathematics with a minor in Computational Finance, graduating with University and College Honors.

STATUS_LOG

→ Presenting When Agents Lie (Best Paper Award) at the ICML NExT-Game workshop in Seoul on July 11, 2026.

→ Joining The Voleon Group as a Software Engineer in July 2026.

→ Open to summer lecturer positions in CS, ML, AI, or quantitative finance.

→ Passionate about teaching: TA for 7 different CMU courses, from differential equations to graduate AI. See my teaching philosophy.

→ Off-hours: tricking, breakdancing, freediving, photography, and K-Pop dance — proof on the hobbies page.

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years at CMU
02 mission log

Recent transmissions

2026.07

Best Paper Award. "When Agents Lie: Premeditation, Persistence, and Exploitation in Repeated Games" accepted to the ICML New Frontiers in Game-Theoretic Learning (NExT-Game) workshop — and won the Best Paper Award. Presenting in Seoul on July 11. Read the paper.

2026.07

Paper accepted. "What Game-Theoretic Benchmarks Miss: Strategic Silence in Multi-Agent LLMs" accepted to the ICML Workshop on Failure Modes of Agentic AI. Read the paper.

2026.04.20

Thesis defended. Successfully defended my master's thesis, "The Structure of Deception: How LLM Agents Lie, Break Promises, and Exploit Trust in Multi-Agent Settings." Watch the defense presentation.

2026.03.01

Paper accepted. "Cheap Talk, Empty Promise: Frontier LLMs easily break public promises for self-interest" accepted to the ICLR AI for Mechanism Design and Strategic Decision Making workshop.

2026.03.01

Paper accepted. "Behavioral and Strategic Deception in Large Language Models: A Taxonomy and Benchmark Analysis" accepted to the ICLR Agents in the Wild: Safety, Security, and Beyond workshop.

2025.12.06

Paper accepted. "Market-Dependent Communication in Multi-Agent Alpha Generation" accepted to the NeurIPS GenAI in Finance workshop.

03 research

Deception, communication & trust between AI agents

How do LLM agents behave when they can communicate, commit, and privately deviate? My work builds taxonomies, benchmarks, and empirical evaluations of deceptive behavior in multi-agent systems.

★ BEST PAPER ICML '26 WS

When Agents Lie

Premeditation, persistence, and exploitation: how LLM agents deceive in repeated games. Best Paper at the NExT-Game workshop.

ICLR '26 WS

Cheap Talk, Empty Promise

Frontier LLMs break public commitments in ~57% of scenarios — often without recognizing they're doing it.

ICLR '26 WS

From Hallucination to Scheming

A unified taxonomy of LLM deception, applied to 35 benchmarks to expose systematic coverage gaps.

04 writing

Latest from the blog

2026.07.21 · new

Poster Hall Finds: 11 Papers That Stopped Me at ICML 2026

Notes from wandering the ICML 2026 poster halls in Seoul: readable papers on LLM agents, education, and finance, plus why each one caught my attention.

2025.09.28 · featured

Rethinking Education: My Vision for an AI-Enhanced Classroom

Imagining a future classroom where AI tools enhance learning through collaborative homework, conversational exams, and authentic project-based assessment.

2025.09.08

How I Actually Learn Complex Research Papers with AI

A practical walkthrough of using AI to understand dense academic papers, from adversarial training to developing genuine mathematical intuition.

05 side quest

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