activity
20242026
most citedSRLAgent: Enhancing Self-Regulated Learning Skills through Gamification and LLM Assistance

2 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2026

MicroVerse: An Instrument for Measuring Self-Authored Identity Drift in Long-Horizon Multi-Agent Language-Model Simulations

Sky Ng, Brihi Joshi, Ishan Gupta +47

Long-horizon, multi-agent language model (LM) simulations are widely proposed for studying social behavior, yet instruments to measure whether persona-conditioned agents maintain i…

math.NA2026

Optimizing Irreversible Perturbations of the Unadjusted Langevin Algorithm

Qianyu Julie Zhu, Youssef Marzouk, Konstantinos Spiliopoulos +1

Irreversible perturbations accelerate the convergence of Langevin dynamics, breaking detailed balance while preserving the invariant measure. The design of optimal irreversible per…

cs.LG2026

Online Reasoning Calibration: Test-Time Training Enables Generalizable Conformal LLM Reasoning

Cai Zhou, Zekai Wang, Menghua Wu +6

While test-time scaling has enabled large language models to solve highly difficult tasks, state-of-the-art results come at exorbitant compute costs. These inefficiencies can be at…

cs.LG2026

Conformal Prediction for Generative Models via Adaptive Cluster-Based Density Estimation

Qidong Yang, Qianyu Julie Zhu, Jonathan Giezendanner +3

Conditional generative models map input variables to complex, high-dimensional distributions, enabling realistic sample generation in a diverse set of domains. A critical challenge…

cs.HC2025★ 2 cited

SRLAgent: Enhancing Self-Regulated Learning Skills through Gamification and LLM Assistance

Wentao Ge, Yuqing Sun, Ziyan Wang +5

Self-regulated learning (SRL) is crucial for college students navigating increased academic demands and independence. Insufficient SRL skills can lead to disorganized study habits,…

stat.ML2024

On the design of scalable, high-precision spherical-radial Fourier features

Ayoub Belhadji, Qianyu Julie Zhu, Youssef Marzouk

Approximation using Fourier features is a popular technique for scaling kernel methods to large-scale problems, with myriad applications in machine learning and statistics. This me…