8 papers
A foundation model of numerical intelligence with cross-disciplinary generalization
Chenghan Wu, Zongmin Yu, Liu Yang
Intelligence is commonly understood as the ability to acquire and apply knowledge, adapt to unfamiliar situations and solve new problems. Large language models exhibit this capacit…
LemonHarness Technical Report
Kailong Ren, Fubo Sun, Jiachen Liu +18
As large language model (LLM) agents are applied to longer tasks, they increasingly modify workspace state across multiple rounds of iteration. However, agents typically observe on…
Agentic Symbolic Search: Characterizing PDEs Beyond Hand-crafted Expressions, Meshes, and Neural Networks
Zongmin Yu, Liu Yang
Mathematicians understand a PDE solution through mathematical structures rather than tables of computed values. Historically, this has been the product of mathematical analysis, ca…
Escher-Loop: Mutual Evolution by Closed-Loop Self-Referential Optimization
Ziyang Liu, Xinyan Guo, Xuchen Wei +2
While recent autonomous agents demonstrate impressive capabilities, they predominantly rely on manually scripted workflows and handcrafted heuristics, inherently limiting their pot…
ClawMark: A Living-World Benchmark for Multi-Turn, Multi-Day, Multimodal Coworker Agents
Fanqing Meng, Lingxiao Du, Zijian Wu +46
Language-model agents are increasingly used as persistent coworkers that assist users across multiple working days. During such workflows, the surrounding environment may change in…
Evolving Ensemble of Agents
Zongmin Yu, Liu Yang
We introduce the Evolving Ensemble of Agents (EvE), a decentralized framework that organizes existing, highly capable coding agents into a live, co-evolving system for algorithmic…
PDE Generalization of In-Context Operator Networks: A Study on 1D Scalar Nonlinear Conservation Laws
Liu Yang, Stanley J. Osher
Can we build a single large model for a wide range of PDE-related scientific learning tasks? Can this model generalize to new PDEs, even of new forms, without any fine-tuning? In-c…
Fine-Tune Language Models as Multi-Modal Differential Equation Solvers
Liu Yang, Siting Liu, Stanley J. Osher
In the growing domain of scientific machine learning, in-context operator learning has shown notable potential in building foundation models, as in this framework the model is trai…