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Found 4 papers, 0 papers with code
Instruction Diversity Drives Generalization To Unseen Tasks
We investigate the trade-off between the number of instructions the model is trained on and the number of training samples provided for each instruction and observe that the diversity of the instruction set determines generalization.
Transformer-Based Models Are Not Yet Perfect At Learning to Emulate Structural Recursion
The framework includes a representation that captures the general \textit{syntax} of structural recursion, coupled with two different frameworks for understanding their \textit{semantics} -- one that is more natural from a programming languages perspective and one that helps bridge that perspective with a mechanistic understanding of the underlying transformer architecture.
PACE-LM: Prompting and Augmentation for Calibrated Confidence Estimation with GPT-4 in Cloud Incident Root Cause Analysis
Major cloud providers have employed advanced AI-based solutions like large language models to aid humans in identifying the root causes of cloud incidents.
Optimization of Multi-Factor Model in Quantitative Trading Based On Reinforcement Learning
Quantitative trading strategies play an important role in stock trading, and reinforcement learning (RL) has been increasingly applied to trading activities in recent years.
