Longtian Bao

Ph.D. Student in Computer Science at the University of Chicago

I am a Ph.D. student in Computer Science at the University of Chicago and a member of the Chicago Human+AI (CHAI) Lab. My work bridges Natural Language Processing and Machine Learning, with a focus on reinforcement fine-tuning and self-evolving curricula for LLM reasoning, long-context understanding, information retrieval, and efficient state-space models like Mamba-2.

Previously, I completed my M.S. in Computer Science and B.S. in Computer Engineering at UC San Diego, where I was a researcher at the Laboratory for Emerging Intelligence advised by Prof. Leon Bergen and Prof. Ramamohan Paturi. I have experience building full-stack educational platforms and autonomous robotic systems.

Longtian Bao

Selected Publications

* denotes equal contribution

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics
Longtian Bao*, Jianyou Wang*, Yang Zhang*, Youze Zheng*, Ramamohan Paturi
arXiv preprint, 2026
Multi-Agent LLM Serving Is a Full-Stack Problem: A Small Step Towards Algorithm–System Co-Design
Zhongkai Yu, Jinya Jiang, Longtian Bao, Junxia Cui, Jingyi Zhang, Zhengan Cheng, Zaifeng Pan, Jingbo Shang, Yufei Ding
Under review, 2026
DeepImagine: Learning Biomedical Reasoning via Successive Counterfactual Imagining
Youze Zheng*, Jianyou Wang*, Yuhan Chen, Matthew Feng, Longtian Bao, Hanyuan Zhang, Maxim Khan, Aditya K. Sehgal, Christopher D. Rosin, Umber Dube, Ramamohan Paturi
arXiv preprint, 2026
CT Open: An Open-Access, Uncontaminated, Live Platform for the Open Challenge of Clinical Trial Outcome Prediction
Jianyou Wang*, Youze Zheng*, Longtian Bao, Hanyuan Zhang, Qirui Zheng, Yuhan Chen, Yang Zhang, Matthew Feng, Maxim Khan, Aditya K. Sehgal, Christopher D. Rosin, Ramamohan Paturi, Umber Dube, Leon Bergen
arXiv preprint, 2026
Single-Pass Document Scanning for Question Answering
Weili Cao*, Jianyou Wang*, Youze Zheng*, Longtian Bao*, Qirui Zheng, Taylor Berg-Kirkpatrick, Ramamohan Paturi, Leon Bergen
Conference on Language Modeling (COLM), 2025 Oral Spotlight, Top 2%
Measuring Risk of Bias in Biomedical Reports: The RoBBR Benchmark
Jianyou Wang*, Weili Cao*, Longtian Bao, Youze Zheng, Gil Pasternak, Kaicheng Wang, Xiaoyue Wang, Ramamohan Paturi, Leon Bergen
Empirical Methods in Natural Language Processing (EMNLP), 2025

Research Funding

ACCESS Discover Compute Allocation
Principal Investigator · Longtian Bao
August 4, 2026 – August 3, 2027 · Project CIS261451

Self-Evolving Curricula for Reinforcement Fine-Tuning of Language Models on Competition Mathematics. Received in-kind computing support through the NSF-supported ACCESS program, with 750,000 ACCESS credits initially available.

Experience

Ph.D. Student
Department of Computer Science, University of Chicago
Reinforcement fine-tuning for LLM reasoning; multi-agent LLM serving
Mar 2026 – Present
  • Designed Question-begets-Question (QbQ), a scalable data-generation procedure in which a teacher model transforms competition-math problems into diverse variants probing the same skills, enabling reinforcement fine-tuning without oracle reasoning traces.
  • Proposed a self-evolving curriculum that re-seeds QbQ each round from problems the current checkpoint can mostly solve, breaking the static-training ceiling and lifting Qwen2.5-Math-7B from 5.6% to 16.5% pass@1 on AIME with no saturation after 20 rounds.
  • Introduced a unified typed-graph representation of multi-agent LLM systems and serving optimizations achieving up to a 5× speedup while using 54–89% fewer tokens on real GPUs, showing that decode dominance makes phase-aware algorithm–system co-design essential.
Research Assistant
Laboratory for Emerging Intelligence, UCSD
Advisors: Prof. Leon Bergen and Prof. Ramamohan Paturi
Apr 2024 – Mar 2026
  • Co-developed CT Open, an open-access, uncontaminated, live platform for the open challenge of clinical trial outcome prediction, enabling rigorous evaluation of LLMs on prospective post-training-cutoff trials.
  • Contributed to DeepImagine, which teaches LLMs biomedical reasoning by training them to infer how observed clinical-trial results change under controlled perturbations, combining supervised fine-tuning on strict counterfactual pairs with RL from verifiable rewards.
  • Re-architected a Mamba-2 State-Space Model with a classification head, creating a subquadratic model that preserves global context for efficient sentence retrieval in documents up to 256k tokens, with a link-based synthetic data pipeline for long-context QA training.
  • Constructed a fine-grained sentence-retrieval benchmark from 41 existing QA datasets via an LLM-assisted annotation-validation pipeline.
  • Developed the RoBBR benchmark for risk-of-bias assessment in biomedical research from expert judgments on 500+ studies, with subtasks that disentangle the retrieval and reasoning abilities of language models.
Instructional Assistant
UC San Diego
2021 – 2024
  • Data Structures (CSE 12): Spring 21, Winter 23, Winter 24
  • Accel. Intro to Programming (CSE 11): Winter 22, Fall 22, Spring 23
  • Computer Organization (CSE 30): Fall 23
  • Software Tools & Techniques Lab (CSE 15L): Spring 21

Projects

UCSD Autograder

2023–2024
Engineered a full-stack educational platform used by over 1,000 students. Developed containerized autograders and real-time ticket queues for office hours.
Full Stack Docker Database

Autonomous AI Racer

Winter 2024
Built a 1/10-scale autonomous vehicle with Jetson Nano, LIDAR, and OAK-D. Trained behavioral cloning models using TensorFlow to navigate racetracks.
Robotics Computer Vision TensorFlow

DaCe Reproducibility

Fall 2022
Evaluated the DaCe high-performance framework on NPBench using AMD hardware. Ported and debugged NumPy benchmarks to analyze performance portability.
HPC Python Benchmarking

Skills

Languages & Core
Python (Advanced) C/C++ Java TypeScript Bash
Machine Learning & AI
PyTorch TensorFlow Transformers Mamba-2 SSMs Long-context QA OpenCV
Systems & DevOps
Docker AWS (EC2/S3) Linux Git PostgreSQL Distributed Training
Tools & Hardware
LLM APIs Weights & Biases NVIDIA Jetson LIDAR React Flask/FastAPI