# Lab Tools & Systems ## ResearchAtlas — graph-based literature discovery A system that helps researchers map a field rather than just rank hits. Instead of returning a ranked list like a standard search engine, ResearchAtlas is **coverage-oriented**: it builds a graph over the literature so a user can see the structure of a research area, discover related work, and navigate connections between papers and ideas. It reflects the lab's broader thesis that **graph structure is a first-class signal** for understanding and retrieval. Link: https://www.researchatlas.dpdns.org/ ## LLMCostCut — cutting LLM API cost by up to 10× A method/toolkit that reduces the number of expensive large-LLM API calls **by up to 10×** through **selective invocation** (only calling the large model when it is actually needed) combined with **online distillation** (learning from the large model's outputs so a cheaper model can handle more cases over time). This is the research basis for the **cost-aware model routing** used inside this very assistant: cheap questions are answered by a small/fast model and only substantive research questions escalate to a stronger model. Link: https://github.com/zhaoliangvaio/llmcostcut ## How this assistant embodies the lab's research This lab assistant is itself a small demonstration of several of the lab's lines of work: - **Retrieval-augmented generation (RAG)** over the lab's publications — see *GRAG* and *Spatial-RAG*. - **Citation-/graph-aware retrieval**: after vector search, results are expanded one hop along a paper graph (shared authors and topics), echoing *GRAG* and *CG-RAG*. - **Trustworthy generation**: answers are grounded in retrieved sources with inline citations, and the assistant declines to answer when the corpus does not support a claim — reflecting the lab's emphasis on robustness and uncertainty. - **Cost-aware routing**: a direct nod to *LLMCostCut*. ## Note on "Causal Dynamics Lab" / Cielara Separately, Dr. Zhao is involved as a research scientist with the **Causal Dynamics Lab**, an AI lab whose product **Cielara** builds a "production world model" to simulate code changes against live environments before deployment. This is an industry effort distinct from his Emory academic group; for academic research, advising, and publications, refer to the Emory lab.