We Hit 99.1% on the LOCOMO Benchmark. Here's How.

1. 1Review existing model assumptions
2. 2Identify potential bottlenecks in model design
3. 3Remove or challenge assumptions to improve performance
4. 4Test and evaluate the updated model on the LOCOMO benchmark
5. 5Analyze results to determine the impact of assumption removal on model accuracy

ML engineers and researchers can benefit from this approach to improve model performance and identify potential bottlenecks in their designs

💡 Challenging assumptions in model design can lead to significant improvements in model performance

💡 Remove assumptions, not complexity, to achieve high accuracy on the LOCOMO benchmark