Tootfinder

LLM-as-a-Supervisor: Mistaken Therapeutic Behaviors Trigger Targeted Supervisory Feedback
Chen Xu, Zhenyu Lv, Tian Lan, Xianyang Wang, Luyao Ji, Leyang Cui, Minqiang Yang, Jian Shen, Qunxi Dong, Xiuling Liu, Juan Wang, Bin Hu
https://arxiv.org/abs/2508.09042

LLM-as-a-Supervisor: Mistaken Therapeutic Behaviors Trigger Targeted Supervisory Feedback
Although large language models (LLMs) hold significant promise in psychotherapy, their direct application in patient-facing scenarios raises ethical and safety concerns. Therefore, this work shifts towards developing an LLM as a supervisor to train real therapists. In addition to the privacy of clinical therapist training data, a fundamental contradiction complicates the training of therapeutic behaviors: clear feedback standards are necessary to ensure a controlled training system, yet there i…

Greetings, earthlings!

Robotic Calibration Based on Haptic Feedback Improves Sim-to-Real Transfer
Juraj Gavura, Michal Vavrecka, Igor Farkas, Connor Gade
https://arxiv.org/abs/2507.08572

Robotic Calibration Based on Haptic Feedback Improves Sim-to-Real Transfer
When inverse kinematics (IK) is adopted to control robotic arms in manipulation tasks, there is often a discrepancy between the end effector (EE) position of the robot model in the simulator and the physical EE in reality. In most robotic scenarios with sim-to-real transfer, we have information about joint positions in both simulation and reality, but the EE position is only available in simulation. We developed a novel method to overcome this difficulty based on haptic feedback calibration, us…

Leveraging Large Language Models for Classifying App Users' Feedback
Yasaman Abedini, Abbas Heydarnoori
https://arxiv.org/abs/2507.08250 https://

Leveraging Large Language Models for Classifying App Users' Feedback
In recent years, significant research has been conducted into classifying application (app) user feedback, primarily relying on supervised machine learning algorithms. However, fine-tuning more generalizable classifiers based on existing labeled datasets remains an important challenge, as creating large and accurately labeled datasets often requires considerable time and resources. In this paper, we evaluate the capabilities of four advanced LLMs, including GPT-3.5-Turbo, GPT-4, Flan-T5, and Ll…

Rifling/sorting through old books & computer materials stored at my parents place. Hope you enjoy seeing these as much as I did flipping through them.
#GenX #IBMPC #Vintage

Met LOL een culturele thema tocht: IJsselbiënnale #regel17

Aus einer kleinen Ausstellung über historische Momente des chinesischen Fernsehens im CCTV Tower. #Beijing