Papers Financial Analysis
“Financial Analysis” 태그가 달린 논문 93편 · 필터 해제
CFBenchmark-MM: Chinese Financial Assistant Benchmark for Multimodal Large Language Model
Multimodal Large Language Models (MLLMs) have rapidly evolved with the growth of Large Language Models (LLMs) and are now applied in various fields. In finance, the integration of diverse modalities such as text, charts,…
Decision MakingFinancial AnalysisLanguage ModelingLanguage Modelling+2EDINET-Bench: Evaluating LLMs on Complex Financial Tasks using Japanese Financial Statements
Financial analysis presents complex challenges that could leverage large language model (LLM) capabilities. However, the scarcity of challenging financial datasets, particularly for Japanese financial data, impedes acade…
Binary ClassificationFinancial AnalysisFraud DetectionLarge Language ModelQuantMCP: Grounding Large Language Models in Verifiable Financial Reality
Large Language Models (LLMs) hold immense promise for revolutionizing financial analysis and decision-making, yet their direct application is often hampered by issues of data hallucination and lack of access to real-time…
Decision MakingFinancial AnalysisHallucinationHow Explanations Leak the Decision Logic: Stealing Graph Neural Networks via Explanation Alignment
Graph Neural Networks (GNNs) have become essential tools for analyzing graph-structured data in domains such as drug discovery and financial analysis, leading to growing demands for model transparency. Recent advances in…
Data AugmentationDrug DiscoveryFinancial AnalysisVISTA: Vision-Language Inference for Training-Free Stock Time-Series Analysis
Stock price prediction remains a complex and high-stakes task in financial analysis, traditionally addressed using statistical models or, more recently, language models. In this work, we introduce VISTA (Vision-Language …
Financial AnalysisStock Price PredictionTime SeriesTime Series AnalysisTowards Competent AI for Fundamental Analysis in Finance: A Benchmark Dataset and Evaluation
Generative AI, particularly large language models (LLMs), is beginning to transform the financial industry by automating tasks and helping to make sense of complex financial information. One especially promising use case…
Financial AnalysisLogical ReasoningA Survey of Attacks on Large Language Models
Large language models (LLMs) and LLM-based agents have been widely deployed in a wide range of applications in the real world, including healthcare diagnostics, financial analysis, customer support, robotics, and autonom…
Autonomous DrivingFinancial AnalysisSurveyNon-Stationary Time Series Forecasting Based on Fourier Analysis and Cross Attention Mechanism
Time series forecasting has important applications in financial analysis, weather forecasting, and traffic management. However, existing deep learning models are limited in processing non-stationary time series data beca…
Financial AnalysisTime SeriesTime Series ForecastingWeather ForecastingMiMIC: Multi-Modal Indian Earnings Calls Dataset to Predict Stock Prices
Predicting stock market prices following corporate earnings calls remains a significant challenge for investors and researchers alike, requiring innovative approaches that can process diverse information sources. This st…
Financial AnalysisSECQUE: A Benchmark for Evaluating Real-World Financial Analysis Capabilities
We introduce SECQUE, a comprehensive benchmark for evaluating large language models (LLMs) in financial analysis tasks. SECQUE comprises 565 expert-written questions covering SEC filings analysis across four key categori…
Financial AnalysisSemantic segmentation of forest stands using deep learning
Forest stands are the fundamental units in forest management inventories, silviculture, and financial analysis within operational forestry. Over the past two decades, a common method for mapping stand borders has involve…
Deep LearningFinancial AnalysisSemantic SegmentationFinAudio: A Benchmark for Audio Large Language Models in Financial Applications
Audio Large Language Models (AudioLLMs) have received widespread attention and have significantly improved performance on audio tasks such as conversation, audio understanding, and automatic speech recognition (ASR). Des…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Financial Analysisspeech-recognition+1Exploring the Reliability of Self-explanation and its Relationship with Classification in Language Model-driven Financial Analysis
Language models (LMs) have exhibited exceptional versatility in reasoning and in-depth financial analysis through their proprietary information processing capabilities. Previous research focused on evaluating classificat…
ClassificationFinancial AnalysisLanguage ModelingLanguage ModellingFinancial Analysis: Intelligent Financial Data Analysis System Based on LLM-RAG
In the modern financial sector, the exponential growth of data has made efficient and accurate financial data analysis increasingly crucial. Traditional methods, such as statistical analysis and rule-based systems, often…
Financial AnalysisRAGRetrievalRetrieval-augmented GenerationPrompt Sentiment: The Catalyst for LLM Change
The rise of large language models (LLMs) has revolutionized natural language processing (NLP), yet the influence of prompt sentiment, a latent affective characteristic of input text, remains underexplored. This study sys…
Financial AnalysisPrompt EngineeringSentiment AnalysisBridging Language Models and Financial Analysis
The rapid advancements in Large Language Models (LLMs) have unlocked transformative possibilities in natural language processing, particularly within the financial sector. Financial data is often embedded in intricate re…
Financial AnalysisFinTMMBench: Benchmarking Temporal-Aware Multi-Modal RAG in Finance
Finance decision-making often relies on in-depth data analysis across various data sources, including financial tables, news articles, stock prices, etc. In this work, we introduce FinTMMBench, the first comprehensive be…
ArticlesBenchmarkingEvent DetectionFinancial Analysis+4METAL: A Multi-Agent Framework for Chart Generation with Test-Time Scaling
Chart generation aims to generate code to produce charts satisfying the desired visual properties, e.g., texts, layout, color, and type. It has great potential to empower the automatic professional report generation in f…
Financial AnalysisStock Price Prediction Using a Hybrid LSTM-GNN Model: Integrating Time-Series and Graph-Based Analysis
This paper presents a novel hybrid model that integrates long-short-term memory (LSTM) networks and Graph Neural Networks (GNNs) to significantly enhance the accuracy of stock market predictions. The LSTM component adept…
Financial AnalysisStock Price PredictionTime SeriesIntegrating the implied regularity into implied volatility models: A study on free arbitrage model
Implied volatility IV is a key metric in financial markets, reflecting market expectations of future price fluctuations. Research has explored IV's relationship with moneyness, focusing on its connection to the implied H…
Financial Analysis