Search Results
OR-Gym: A Reinforcement Learning Library for Operations Research Problems
Reinforcement learning (RL) has been widely applied to game-playing and surpassed the best human-level performance in many domains, yet there are few use-cases in industrial or commercial settings.
FinQA: A Dataset of Numerical Reasoning over Financial Data
In contrast to existing tasks on general domain, the finance domain includes complex numerical reasoning and understanding of heterogeneous representations.
Ranked #4 on
Question Answering
on FinQA
BizFinBench: A Business-Driven Real-World Financial Benchmark for Evaluating LLMs
Our evaluation reveals distinct capability patterns: (1) In Numerical Calculation, Claude-3. 5-Sonnet (63. 18) and DeepSeek-R1 (64. 04) lead, while smaller models like Qwen2. 5-VL-3B (15. 92) lag significantly; (2) In Reasoning, proprietary models dominate (ChatGPT-o3: 83. 58, Gemini-2. 0-Flash: 81. 15), with open-source models trailing by up to 19. 49 points; (3) In Information Extraction, the performance spread is the largest, with DeepSeek-R1 scoring 71. 46, while Qwen3-1. 7B scores 11. 23; (4) In Prediction Recognition, performance variance is minimal, with top models scoring between 39. 16 and 50. 00.
Predicting the Effects of News Sentiments on the Stock Market
Stock market forecasting is very important in the planning of business activities.
AX-MABSA: A Framework for Extremely Weakly Supervised Multi-label Aspect Based Sentiment Analysis
Aspect Based Sentiment Analysis is a dominant research area with potential applications in social media analytics, business, finance, and health.
Aspect-Based Sentiment Analysis
Aspect Category Sentiment Analysis
+3
OmniEcon Nexus: Global Microeconomic Simulation Engine
Risk Analysis: Assesses market volatility and systemic risk using network analysis.
Twitter-Based Gender Recognition Using Transformers
User demographics provide rich information that could help study the subject further.
Optimizing Large Language Models for ESG Activity Detection in Financial Texts
In this paper, we investigate the ability of current-generation LLMs to identify text related to environmental activities.
Removing Non-Stationary Knowledge From Pre-Trained Language Models for Entity-Level Sentiment Classification in Finance
Extraction of sentiment signals from news text, stock message boards, and business reports, for stock movement prediction, has been a rising field of interest in finance.
A Survey of Deep Learning Approaches for OCR and Document Understanding
Documents are a core part of many businesses in many fields such as law, finance, and technology among others.
