Habby is a simple and distraction-free Bullet Journal and Habit Tracking app designed to help users capture their day with meaningful sentences and track daily habits.
Habby is a beautifully designed app that combines the simplicity of a Bullet Journal with the functionality of a Habit Tracker. Users can capture their day with a single meaningful sentence, track daily habits with flexible measurement options, and set monthly goals with progress tracking. The app is available on both iOS and Android platforms, making it accessible for a wide range of users.
Proactive mental care for high performance staff, driven by the October Insights platform.
DeepSeek-R1 is a reasoning model trained via large-scale reinforcement learning (RL) without the need for supervised fine-tuning (SFT). It demonstrates remarkable performance in reasoning tasks, including self-verification and reflection. The model addresses challenges such as endless repetition and poor readability, and achieves performance comparable to OpenAI-o1 across math, code, and reasoning tasks.
This project implements the conversion algorithm from the ToMi dataset to the T4D (Thinking is for Doing) dataset, as introduced in the paper https://arxiv.org/abs/2310.03051. It filters examples with Theory of Mind (ToM) questions and adapts the algorithm to account for second-order false beliefs.