Search Results for author:
Found 5 papers, 1 papers with code
Evaluating LLMs' Mathematical Reasoning in Financial Document Question Answering
Large Language Models (LLMs), excel in natural language understanding, but their capability for complex mathematical reasoning with an amalgamation of structured tables and unstructured text is uncertain.
NICE: To Optimize In-Context Examples or Not?
Recent work shows that in-context learning and optimization of in-context examples (ICE) can significantly improve the accuracy of large language models (LLMs) on a wide range of tasks, leading to an apparent consensus that ICE optimization is crucial for better performance.
Towards Zero-Shot and Few-Shot Table Question Answering using GPT-3
We present very early results on using GPT-3 to perform question answering on tabular data.
The information content of brain states is explained by structural constraints on state energetics
These activity patterns define global brain states and contain information in accordance with their expected probability of occurrence.
Structural underpinnings of control in multiplex networks
For this purpose, we calculate the exact expression of optimal control energy in terms of layer spectra and the relative alignment between the eigenmodes of the input layer and the deeper target layer.
