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Found 6 papers, 0 papers with code
Large Language Models as Financial Data Annotators: A Study on Effectiveness and Efficiency
Collecting labeled datasets in finance is challenging due to scarcity of domain experts and higher cost of employing them.
Identifying Multiple Personalities in Large Language Models with External Evaluation
In this paper, we investigate LLM personalities using an alternate personality measurement method, which we refer to as the external evaluation method, where instead of prompting LLMs with multiple-choice questions in the Likert scale, we evaluate LLMs' personalities by analyzing their responses toward open-ended situational questions using an external machine learning model.
DocLLM: A layout-aware generative language model for multimodal document understanding
Enterprise documents such as forms, invoices, receipts, reports, contracts, and other similar records, often carry rich semantics at the intersection of textual and spatial modalities.
REFinD: Relation Extraction Financial Dataset
A number of datasets for Relation Extraction (RE) have been created to aide downstream tasks such as information retrieval, semantic search, question answering and textual entailment.
InProC: Industry and Product/Service Code Classification
However, unavailability of labeled datasets as well as the need for high precision results within the financial domain makes this a challenging problem.
Parameterized Explanations for Investor / Company Matching
We compare the performance of our system with human generated recommendations and demonstrate the ability of our algorithm to perform extremely well on this task.
