collaborators

7 papers

physics.flu-dyn2026

AI CFD Scientist: Toward Open-Ended Computational Fluid Dynamics Discovery with Physics-Aware AI Agents

Nithin Somasekharan, Rabi Pathak, Manushri Dhanakoti +4

Recent LLM-based agents have closed substantial portions of the scientific discovery loop in software-only machine-learning research, in chemistry, and in biology. Extending the sa…

cs.IR2026

FollowTable: A Benchmark for Instruction-Following Table Retrieval

Rihui Jin, Yuchen Lu, Ting Zhang +7

Table Retrieval (TR) has traditionally been formulated as an ad-hoc retrieval problem, where relevance is primarily determined by topical semantic similarity. With the growing adop…

cs.AI2026

VisioMath: Benchmarking Figure-based Mathematical Reasoning in LMMs

Can Li, Ying Liu, Ting Zhang +2

Large Multimodal Models have achieved remarkable progress in integrating vision and language, enabling strong performance across perception, reasoning, and domain-specific tasks. H…

cs.AI2026

Foam-Agent: A Large Language Model-Based Multi-Agent Framework for Automating Computational Fluid Dynamics Workflows

Ling Yue, Nithin Somasekharan, Tingwen Zhang +4

Computational fluid dynamics (CFD) has been the main workhorse of computational physics, yet its steep learning curve and fragmented, multi-stage workflow create significant barrie…

cs.AI2025

Foam-Agent 2.0: An End-to-End Composable Multi-Agent Framework for Automating CFD Simulation in OpenFOAM

Ling Yue, Nithin Somasekharan, Tingwen Zhang +2

Computational Fluid Dynamics (CFD) is an essential simulation tool in engineering, yet its steep learning curve and complex manual setup create significant barriers. To address the…

cs.CL2025

Discerning minds or generic tutors? Evaluating instructional guidance capabilities in Socratic LLMs

Ying Liu, Can Li, Ting Zhang +4

The conversational capabilities of large language models hold significant promise for enabling scalable and interactive tutoring. While prior research has primarily examined their…