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Found 5 papers, 0 papers with code
Starting from “Zero”: An Incremental Zero-shot Learning Approach for Assessing Peer Feedback Comments
However, all these powerful algorithms have the same Achilles’ heel: the reliance on sufficient historical data.
ECC Analyzer: Extract Trading Signal from Earnings Conference Calls using Large Language Model for Stock Performance Prediction
In the realm of financial analytics, leveraging unstructured data, such as earnings conference calls (ECCs), to forecast stock performance is a critical challenge that has attracted both academics and investors.
RiskLabs: Predicting Financial Risk Using Large Language Model Based on Multi-Sources Data
Through comparative experiments, we demonstrate how different data sources contribute to financial risk assessment and discuss the critical role of LLMs in this context.
Can Large Language Models Detect Misinformation in Scientific News Reporting?
The central research question of this paper is whether it is possible to use large language models (LLMs) to detect misinformation in scientific reporting.
Causal-TGAN: Causally-Aware Synthetic Tabular Data Generative Adversarial Network
The flexibility of this architecture is its capability to support different types of expert knowledge (e. g., complete or partial) about the causal nature of the underlying phenomenon.
