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Found 3 papers, 1 papers with code
A Survey on Large Language Model Hallucination via a Creativity Perspective
Hallucinations in large language models (LLMs) are always seen as limitations.
Unveiling the Potential of Sentiment: Can Large Language Models Predict Chinese Stock Price Movements?
The rapid advancement of Large Language Models (LLMs) has spurred discussions about their potential to enhance quantitative trading strategies.
GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection
With a long history of traditional Graph Anomaly Detection (GAD) algorithms and recently popular Graph Neural Networks (GNNs), it is still not clear (1) how they perform under a standard comprehensive setting, (2) whether GNNs can outperform traditional algorithms such as tree ensembles, and (3) how about their efficiency on large-scale graphs.
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