activity
20202026
most citedGrounded Curriculum Learning

3 citations · 9 across the 10 of their papers we have counts for

collaborators

11 papers

cs.CV2026

Entropy-Guided k-Guard Sampling for Long-Horizon Autoregressive Video Generation

Yizhao Han, Tianxing Shi, Zhao Wang +6

Autoregressive (AR) architectures have achieved significant successes in LLMs, inspiring explorations for video generation. In LLMs, top-p/top-k sampling strategies work exceptiona…

cs.CY2025

The Essentials of AI for Life and Society: A Full-Scale AI Literacy Course Accessible to All

Zifan Xu, Kristen Procko, Michael Munje +4

In Fall 2023, we introduced a new AI Literacy class called The Essentials of AI for Life and Society (CS 109), a one-credit, seminar course consisting mainly of guest lectures, whi…

cs.LG2025

Provably Minimum-Length Conformal Prediction Sets for Ordinal Classification

Zijian Zhang, Xinyu Chen, Yuanjie Shi +3

Ordinal classification has been widely applied in many high-stakes applications, e.g., medical imaging and diagnosis, where reliable uncertainty quantification (UQ) is essential fo…

cs.RO2025

GACL: Grounded Adaptive Curriculum Learning with Active Task and Performance Monitoring

Linji Wang, Zifan Xu, Peter Stone +1

Curriculum learning has emerged as a promising approach for training complex robotics tasks, yet current applications predominantly rely on manually designed curricula, which deman…

cs.RO20251 cited

Benchmarking Massively Parallelized Multi-Task Reinforcement Learning for Robotics Tasks

Viraj Joshi, Zifan Xu, Bo Liu +2

Multi-task Reinforcement Learning (MTRL) has emerged as a critical training paradigm for applying reinforcement learning (RL) to a set of complex real-world robotic tasks, which de…

cs.AI20251 cited

The Essentials of AI for Life and Society: An AI Literacy Course for the University Community

Joydeep Biswas, Don Fussell, Peter Stone +4

We describe the development of a one-credit course to promote AI literacy at The University of Texas at Austin. In response to a call for the rapid deployment of class to serve a b…