Crew Ai Note
Published:
The Summary of Crewai course: Multi AI Agent Systems with crewAI
Posts by Collection
notes
Machine Learning I Note
Published:
The Summary of MSADS Machine Learning I
LLM 核心原理深度解析 Permalink
Published:
从基础到前沿的系统化大模型原理解析 — 六章覆盖 Transformer / 预训练 / 人类对齐 / MoE / RoPE / 推理优化。
AI 大模型应用开发工程师 — 面试 500+ 题题库 Permalink
Published:
六大模块、522 道精选题，覆盖从基础原理到工程部署的完整知识体系。
LLM 大规模训练与部署 Permalink
Published:
分布式训练并行策略 + 推理服务化 + 量化压缩 + 生产部署 — 一份覆盖从单机多卡到千卡集群、从理论推导到工程指标的系统笔记。
portfolio
HikerScrolls — Beautiful Travel Journals from Obsidian
An Obsidian plugin that turns your trip notes into stunning, shareable travel journals with GPX route maps, AI-generated pen sketches, and scrollytelling layouts.
publications
Analyst Reports and Stock Performance: Evidence from the Chinese Market
Published in Asia-Pacific Financial Markets, 2025
Used a fine-tuned BERT sentiment classifier on Chinese sell-side analyst reports to test whether textual tone predicts cross-sectional returns in the A-share market. Accepted at Asia-Pacific Financial Markets.
Recommended citation: Liu, R., Liang, J., Chen, H., & Hu, Y. (2025). "Analyst Reports and Stock Performance: Evidence from the Chinese Market." Asia-Pacific Financial Markets.
Download Paper
Faster Adaptive Optimization via Expected Gradient Outer Product Reparameterization
Published in SIAM Journal on Mathematics of Data Science (under review), 2025
Tightens Adagrad/Adam convergence bounds by a factor of 1/d via EGOP-based reparameterization, and proposes Auxiliary-Variable and Reduced EGOP algorithms that bypass the storage/compute bottleneck of full-matrix preconditioning. Submitted to SIMODS.
Recommended citation: DePavia, A., Cruzado, J., Liang, J., Charisopoulos, V., & Willett, R. (2025). "Faster Adaptive Optimization via Expected Gradient Outer Product Reparameterization." Submitted to SIAM Journal on Mathematics of Data Science (SIMODS).
Download Paper
Validating Two Pathological Foundation Models for Breast Biomarker Detection
Published in In preparation, 2025
First study transferring Direct Preference Optimization (DPO) from LLM alignment to computational pathology. A label-free preference-pair pipeline (UMAP + DBSCAN on TITAN embeddings) plus LoRA-DPO fine-tuning lifts PR-status AUROC from 79.75% to 81.92% and Cohen’s κ from 45.40% to 54.43%. In preparation.
Recommended citation: Atiya, S., Liang, J., et al. (2025). "Validating Two Pathological Foundation Models for Breast Biomarker Detection." In preparation.
talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown file that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.