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Found 6 papers, 4 papers with code
ECCO: Can We Improve Model-Generated Code Efficiency Without Sacrificing Functional Correctness?
Although large language models (LLMs) have been largely successful in generating functionally correct programs, conditioning models to produce efficient solutions while ensuring correctness remains a challenge.
Pre-Calc: Learning to Use the Calculator Improves Numeracy in Language Models
Quantitative and numerical comprehension in language is an important task in many fields like education and finance, but still remains a challenging task for language models.
XLDA: Linear Discriminant Analysis for Scaling Continual Learning to Extreme Classification at the Edge
Streaming Linear Discriminant Analysis (LDA) while proven in Class-incremental Learning deployments at the edge with limited classes (upto 1000), has not been proven for deployment in extreme classification scenarios.
Predictive Maneuver Planning with Deep Reinforcement Learning (PMP-DRL) for comfortable and safe autonomous driving
Our proposed approach combines a predictive model and an RL agent to plan for comfortable and safe maneuvers.
C3PO: A Lightweight Copying Mechanism for Translating Pseudocode to Code
In the Copy Phase, a binary classifier is employed to determine and mask the pseudocode tokens that can be directly copied into the code.
A Comparative Study of Algorithms for Intelligent Traffic Signal Control
In this paper, methods have been explored to effectively optimise traffic signal control to minimise waiting times and queue lengths, thereby increasing traffic flow.
