6 papers
From Distributions to Stochastic Processes: Neural Approximation of Measure-Valued Maps
Yichen Wang, Ziyi Wang, Wenlian Lu +5
Learning mappings between probability distributions arises naturally when inputs and outputs are represented by populations of samples rather than individual observations. We devel…
Freeze, Then Select: Structured Field Adapters and Stability-Validated Weak Selection for PDE Discovery from Sparse Observations
Juncheng Zhong, Chenghuang Shen, Jianfeng Liu +5
PDE discovery from sparse observations requires reconstructing a continuous field and selecting the correct differential terms. Our analysis of optimization paths in coupled neural…
AutoVSR: Automatic Visual-to-Symbolic Reasoning for Symbolic Expression Generation from Circuit Schematic
Zhe Xiao, Longfei Li, Xu He +3
Symbolic expressions can effectively characterize and predict circuit behavior, but deriving them directly from circuit schematics is challenging. This process requires accurate vi…
CirrusBench: Evaluating LLM-based Agents Beyond Correctness in Real-World Cloud Service Environments
Yi Yu, Guangquan Hu, Chenghuang Shen +15
The increasing agentic capabilities of Large Language Models (LLMs) have enabled their deployment in real-world applications, such as cloud services, where customer-assistant inter…
Adapting Technical-Service LLM Agents with Latent Logic Augmentation, Robust Noise Reduction, and Hybrid Reward Modeling
Junzhuo Ma, Chenghuang Shen, Yi Yu +15
Technical-service LLM agents are entering production workflows, where value depends on whether engineers adopt generated replies. Service tickets hide decision logic, contain noisy…
Concise and Organized Perception Facilitates Reasoning in Large Language Models
Junjie Liu, Shaotian Yan, Chen Shen +4
Exploiting large language models (LLMs) to tackle reasoning has garnered growing attention. It still remains highly challenging to achieve satisfactory results in complex logical p…