activity
20242026
collaborators

6 papers

math.NA2026

Predictive Moving Sample Method for Physics-Informed Neural Solvers of Time-Dependent PDEs

Beining Xu, Bocheng Zhang, Haijun Yu +2

Time-dependent partial differential equations (PDEs) often develop sharp fronts, localized peaks, and other moving structures that occupy only a small portion of the space--time do…

cs.CL2026

Auditing Stealth Sycophancy in Mental-Health Dialogue: Structured Clinical-State Diagnostics and Clean Matched Benchmarks

Tianze Han, Beining Xu, Hanbo Zhang +1

Mental-health dialogue models are increasingly evaluated by AI-based evaluators, yet these evaluators often treat surface empathy, supportiveness, or fluency as evidence of safety.…

math.NA2026

Moving sample method for solving time-dependent partial differential equations

Beining Xu, Haijun Yu, Jiayu Zhai +2

Solving time-dependent partial differential equations (PDEs) that exhibit sharp gradients or local singularities is computationally demanding, as traditional physics-informed neura…

cs.CL2025

TECP: Token-Entropy Conformal Prediction for LLMs

Beining Xu, Yongming Lu

Uncertainty quantification (UQ) for open-ended language generation remains a critical yet underexplored challenge, especially under black-box constraints where internal model signa…

cs.CL2025

Understanding the Effects of RLHF on the Quality and Detectability of LLM-Generated Texts

Beining Xu, Arkaitz Zubiaga

Large Language Models (LLMs) have demonstrated exceptional performance on a range of downstream NLP tasks by generating text that closely resembles human writing. However, the ease…

cs.AI2024

Adaptable and Precise: Enterprise-Scenario LLM Function-Calling Capability Training Pipeline

Guancheng Zeng, Wentao Ding, Beining Xu +8

Enterprises possess a vast array of API assets scattered across various functions, forming the backbone of existing business processes. By leveraging these APIs as functional tools…