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Found 8 papers, 2 papers with code
Textbooks Are All You Need
Despite this small scale, phi-1 attains pass@1 accuracy 50. 6% on HumanEval and 55. 5% on MBPP.
Overcoming the Convex Barrier for Simplex Inputs
Recent progress in neural network verification has challenged the notion of a convex barrier, that is, an inherent weakness in the convex relaxation of the output of a neural network.
Scaling the Convex Barrier with Sparse Dual Algorithms
Tight and efficient neural network bounding is crucial to the scaling of neural network verification systems.
AutoSimulate: (Quickly) Learning Synthetic Data Generation
Simulation is increasingly being used for generating large labelled datasets in many machine learning problems.
STEER: Simple Temporal Regularization For Neural ODEs
Training Neural Ordinary Differential Equations (ODEs) is often computationally expensive.
Alpha MAML: Adaptive Model-Agnostic Meta-Learning
Model-agnostic meta-learning (MAML) is a meta-learning technique to train a model on a multitude of learning tasks in a way that primes the model for few-shot learning of new tasks.
Meta Learning Deep Visual Words for Fast Video Object Segmentation
We address this problem by considering the task of video object segmentation.
Incremental Tube Construction for Human Action Detection
In this work, we introduce a real-time and online joint-labelling and association algorithm for action detection that can incrementally construct space-time action tubes on the most challenging action videos in which different action categories occur concurrently.
