MLab
ACMLab is Stanford's premier machine learning club. Its goal is to teach anyone with basic CS experience machine learning. After an intensive ramp-up workshop in the fall, members work on publishing papers at top ML conferences and workshops. We have published 6 workshop papers so far at top conferences and workshops such as ACL and ICLR. Alumni have gone on to Google AI, Stanford ML Group, Stanford NLP Group, and VMWare.
Board
Alden Eberts
2027
Co-Director
Christopher Sun
2027
Co-Director
Winter 2025 SemEval
We submitted to Tasks 2, 3, 8, and 11 of the Workshop on Semantic Evaluation.
Recent Projects
Fall 2024 Onboarding Project
This year 30 teams with 94 participants participated in the Fall Onboarding Project, developing custom models for the task of bird classification.
SemEVAL
We submitted to the Workshop on Semantic Evaluation's Task 1 (lexical complexity modelling) and Task 8 (automatically extracting measurements from scientific text). Our teams performed competitively on both tasks, including second place in one of the Task 8 subcategories. Our task description papers appeared at SemEval at ACL 2021.
Google BIG-Bench
Members proposed 4 tasks to be used in Google's BIG-Bench challenge. The purpose of this challenge was to create a collaborative benchmark for enourmous language models like GPT-3. MLab submitted tasks about temporal sequences, logic puzzles, sarcasm, and IPA translation.