Mohammad Taufeeque
Member of Technical Staff
Mohammad Taufeeque is a research engineer at FAR.AI. Taufeeque has a bachelor’s degree in Computer Science & Engineering from IIT Bombay, India. He has previously interned at Microsoft Research, working on adapting deployed neural text classifiers to out-of-distribution data.
NEWs & publications
Pacing Outside the Box: RNNs Learn to Plan in Sokoban
July 24, 2024
pacing-outside-the-box-rnns-learn-to-plan-in-sokoban
Planning behavior in a recurrent neural network that plays Sokoban
planning-behavior-in-a-recurrent-neural-network-that-plays-sokoban
We Found Exploits in GPT-4’s Fine-tuning & Assistants APIs
December 21, 2023
we-found-exploits-in-gpt-4s-fine-tuning-assistants-apis
Exploiting Novel GPT-4 APIs
exploiting-novel-gpt-4-apis
Codebook Features: Sparse and Discrete Interpretability for Neural Networks
October 19, 2023
codebook-features-sparse-and-discrete-interpretability-for-neural-networks
Codebook Features: Sparse and Discrete Interpretability for Neural Networks
codebook-features-sparse-and-discrete-interpretability-for-neural-networks
Planning behavior in a recurrent neural network that plays Sokoban
July 22, 2024
planning-behavior-in-a-recurrent-neural-network-that-plays-sokoban
Pacing Outside the Box: RNNs Learn to Plan in Sokoban
pacing-outside-the-box-rnns-learn-to-plan-in-sokoban
Exploiting Novel GPT-4 APIs
December 21, 2023
exploiting-novel-gpt-4-apis
We Found Exploits in GPT-4’s Fine-tuning & Assistants APIs
we-found-exploits-in-gpt-4s-fine-tuning-assistants-apis
Codebook Features: Sparse and Discrete Interpretability for Neural Networks
October 27, 2023
codebook-features-sparse-and-discrete-interpretability-for-neural-networks
Codebook Features: Sparse and Discrete Interpretability for Neural Networks
codebook-features-sparse-and-discrete-interpretability-for-neural-networks
imitation: Clean Imitation Learning Implementations
September 22, 2022
imitation-clean-imitation-learning-implementations
