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Found 7 papers, 0 papers with code
Prompting in the Dark: Assessing Human Performance in Prompt Engineering for Data Labeling When Gold Labels Are Absent
Millions of users prompt large language models (LLMs) for various tasks, but how good are people at prompt engineering?
What Color Scheme is More Effective in Assisting Readers to Locate Information in a Color-Coded Article?
The rise of Large Language Models (LLMs) has streamlined document coding, enabling simple automatic text labeling with various schemes.
Convolutional Bayesian Filtering
In this paper, we find that by adding an additional event that stipulates an inequality condition, we can transform the conditional probability into a special integration that is analogous to convolution.
If in a Crowdsourced Data Annotation Pipeline, a GPT-4
Recent studies indicated GPT-4 outperforms online crowd workers in data labeling accuracy, notably workers from Amazon Mechanical Turk (MTurk).
Adversarial Batch Inverse Reinforcement Learning: Learn to Reward from Imperfect Demonstration for Interactive Recommendation
In this research, we focus on the problem of learning to reward (LTR), which is fundamental to reinforcement learning.
Classifying Crime Types using Judgment Documents from Social Media
Experiments show that the proposed method achieves state-of-the-art results on the present dataset.
Lumos in the Night Sky: AI-enabled Visual Tool for Exploring Night-Time Light Patterns
We introduce NightPulse, an interactive tool for Night-time light (NTL) data visualization and analytics, which enables researchers and stakeholders to explore and analyze NTL data with a user-friendly platform.
