Xinran Zhao

PhD Candidate · Carnegie Mellon University

I am a fourth-year PhD candidate at CMU LTI, advised by Sherry Wu. My PhD is supported by the Amazon AI PhD Fellowship.

At Google DeepMind (2024, 2026), I worked as a student researcher on LLM planning, long-horizon code generation, and continual learning with Azade Nova and Hanie Sedghi. At Ai2 (2025), I worked on deep research agents with Varsha, Aakanksha, Joseph, Jay, and Jena.

I received my MSCS from Stanford, where I worked with Christopher Manning, and my bachelor's degree from HKUST. At HKUST and during my exchange at Cornell, I was fortunate to work with Yangqiu Song, Dit-Yan Yeung, and Claire Cardie.

I always feel lucky to meet great mentors along my journey, including but not limited to, Shikhar Murty, Hongming Zhang, and Esin Durmus.

I am on the 2026–27 industry job market, with a flexible graduation date!

Research

I am interested in meaningful research on natural language processing (NLP) and language model agents. My goal is to build efficient, effective, and faithful systems that work with people on complex real-world tasks. Recently, I focus on information seeking and planning in long-horizon scenarios, organized around three questions:

Information Seeking & Delivery

How can agents proactively help humans seek information, learn, and stay educated amid massive artificial artifacts?

Escalation (proactive delivery, in submission) · DR Tulu (ICML'26) · Intent-aware QA (ICLR'26) · Revela (ICLR'26) · Mixture of Retrievers (EMNLP'25) · PIR (COLM'24) · Dense X (EMNLP'24) · MixGR (EMNLP'24) · Thrust (when to retrieve, NeurIPS'23)

Reasoning, Planning, Forecasting & Coding Agents

How can agents learn, maintain memory, and evolve over complex long-horizon tasks?

3D Code Editing (In submission) · Tea Leaves (In submission) · ReSHAPE (BiAlign@NeurIPS'26) · Harness Adaptation (In submission) · Pivot-ICL (In submission) · Ramon Llull (LM4Sci@COLM'25) · cAST (EMNLP'25) · Action Sequence Similarity (ICLR'25)

Persuasion & Human–AI Alignment

How can models stay aligned with human motives, goals, and intents under high automation, including through multi-turn behaviors and how multimodal inputs shape model representations?

Real-Time Debate (In submission) · Strategic Debate (ICLR'26) · SPHERE (ACL'25) · FaR (confidence calibration, ACL'24) · Argument Persuasion (ACL'21) · Probing Toxic Content (ACL'21)

Selected Honors and Awards

Best Paper Award, FrontierIR Workshop at AAAI 2026 (Revela)
Amazon AI PhD Fellowship, 2025 (two years of full tuition and stipend; $150,000 in AWS credits)
Google RSGCP Award on LLM Planning ($30,000), 2024
Google RS Conference Travel Scholarship ($3,000), 2024
HKUST Academic Achievement Medal (Top 1%), 2021

Selected Research

All research →

Selected publications and ongoing work. * Equal contribution.

1. Improving Attributed Long-form Question Answering with Intent Awareness

Xinran Zhao, Aakanksha Naik, Jay DeYoung, Joseph Chee Chang, Jena D. Hwang, Tongshuang Wu, and Varsha Kishore

ICLR'26

2. Strategic Planning and Rationalizing on Trees Make LLMs Better Debaters

Danqing Wang*, Zhuorui Ye*, Xinran Zhao*, Fei Fang, and Lei Li

ICLR'26

3. 3DCodeEdit: Benchmarking Instruction-Guided 3D Program Editing

Binjie Wang*, Xinran Zhao*, Shoubin Yu, Xiang Li, Silong Yong, Chenyang Yang, Tianyu Chen, Ruofei Du, He He, Chen Zhao, and Tongshuang Wu

In submission

4. Reading the Tea Leaves, Again: Can Large Language Models Predict Language Model Training Runs?

Xinran Zhao, Xiang Li, Tong Chen, Jinchuan Tian, Zichun Yu, and Tongshuang Wu

In submission

5. Knowing When to Stop: The Evidence–Action Gap in Coding Agents

Tianyu Chen*, Xinran Zhao*, Vijay Viswanathan, Shoubin Yu, Mingyuan Zhou, and Tongshuang Wu

In submission

6. Better Harnesses, Smaller Models: Building 90% Cheaper Agents via Automated Harness Adaptation

Chenyang Yang, Xinran Zhao, Tongshuang Wu, and Christian Kästner

In submission

7. The Ramon Llull's Thinking Machine for Automated Ideation

Xinran Zhao, Boyuan Zheng, Chenglei Si, Haofei Yu, Ken Liu, Runlong Zhou, Ruochen Li, Tong Chen, Xiang Li, Yiming Zhang, and Tongshuang Wu

LM4Sci@COLM'25

8. MoR: Better Handling Diverse Queries with a Mixture of Sparse, Dense, and Human Retrievers

Jushaan Singh Kalra*, Xinran Zhao*, To Eun Kim, Fengyu Cai, Fernando Diaz, and Tongshuang Wu

EMNLP'25 [Code]

9. cAST: Enhancing Code Retrieval-Augmented Generation with Structural Chunking via Abstract Syntax Tree

Yilin Zhang, Xinran Zhao, Zora Zhiruo Wang, Chenyang Yang, Jiayi Wei, and Tongshuang Wu

EMNLP'25 [Code]

10. Improving Large Language Model Planning with Action Sequence Similarity

Xinran Zhao, Hanie Sedghi, Bernd Bohnet, Dale Schuurmans, and Azade Nova

ICLR'25

11. Beyond Relevance: Evaluate and Improve Retrievers on Perspective Awareness

Xinran Zhao, Tong Chen, Sihao Chen, Hongming Zhang, and Tongshuang Wu

COLM'24

12. Fact-and-Reflection (FaR) Improves Confidence Calibration of Large Language Models

Xinran Zhao, Hongming Zhang, Xiaoman Pan, Wenlin Yao, Dong Yu, Tongshuang Wu, and Jianshu Chen

ACL'24

13. Thrust: Adaptively Propels Large Language Models with External Knowledge

Xinran Zhao, Hongming Zhang, Xiaoman Pan, Wenlin Yao, Dong Yu, and Jianshu Chen

NeurIPS'23

Large-scale Collaborations

DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research

Rulin Shao, Akari Asai, Shannon Zejiang Shen, Hamish Ivison, Varsha Kishore, Jingming Zhuo, Xinran Zhao, Molly Park, Samuel G. Finlayson, David Sontag, Tyler Murray, Sewon Min, Pradeep Dasigi, Luca Soldaini, Faeze Brahman, Wen-tau Yih, Tongshuang Wu, Luke Zettlemoyer, Yoon Kim, Hannaneh Hajishirzi, and Pang Wei Koh

ICML'26 · Spotlight

OpenReview

Efficient Test-Time Adaptation through Human-AI Interaction

Zora Zhiruo Wang, Apurva Gandhi, Rulin Shao, Aspen Chen, Jonas Mueller, Zhiqi Liang, Jett Chen, Michael Ryan, Qianou Ma, Luxi He, Zhoujun Cheng, Andre He, Seungone Kim, Jiayi Geng, Mingqian Zheng, Weiwei Sun, Zheyuan Zhang, Xinran Zhao, Yike Wang, Abe Hou, Liwei Jiang, Pang Wei Koh, Diyi Yang, Graham Neubig, and Daniel Fried

TTCL@NeurIPS'26

OpenReview

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (BIG-bench)

BIG-bench collaboration (including Xinran Zhao)

TMLR'23

OpenReview

Academic Events

Winter, 2027 General chair, FrontierIR, the Second Workshop on New Frontiers in Information Retrieval at AAAI 2027.
Fall, 2026 Invited panelist, Global Embodied Ecosystem Night at IROS 2026.
Summer, 2026 Invited talk at Google DeepMind: Continual Learning for Coding Agents.
Summer, 2025 Invited talk at UW H2 Group: Improving Large Language Model Planning with Action Sequence Similarity.
Summer, 2024 Invited talk at Samaya AI: Towards Building Retrieval Systems in Complex Realistic Scenarios.
Summer, 2022 Invited talk at the ICML Commonsense Tutorial: On Task Difficulty of Few-shot Learning.
Spring, 2022 Invited talk at NUS, Department of Marketing: NLP as a Tool for Scientific Discovery.

Service

General chair, FrontierIR, the Second Workshop on New Frontiers in Information Retrieval at AAAI 2027.
Area chair for ACL and EMNLP (2024–present), and NAACL (2025–present).
Reviewer for NeurIPS (2024–present), ICLR (2025–present), ICML (2025–present), and COLM (2024–present); previously for ACL, EMNLP, NAACL, EACL, AACL, AAAI, and ECCV.

Miscellaneous

Besides research, I also enjoy:

Bodybuilding: I can deadlift 140 kg and squat 140 kg for sets.
Debate: I was a member of the HKUST Mandarin Debate Team. We won first prize at the Bay Area Debate Championship and placed in the top eight at the sixth and seventh International Mandarin Debate Invitational in Singapore.
Poetry: I write traditional Chinese poetry and have published a few poems in newspapers.
Archery: I was an active member of the HKUST Archery Club.