Search Results
DeepFund: Will LLM be Professional at Fund Investment? A Live Arena Perspective
Large Language Models (LLMs) have demonstrated impressive capabilities across various domains, but their effectiveness in financial decision making, particularly in fund investment, remains inadequately evaluated.
Time Travel is Cheating: Going Live with DeepFund for Real-Time Fund Investment Benchmarking
Large Language Models (LLMs) have demonstrated notable capabilities across financial tasks, including financial report summarization, earnings call transcript analysis, and asset classification.
Cryptocurrency Portfolio Management with Deep Reinforcement Learning
Portfolio management is the decision-making process of allocating an amount of fund into different financial investment products.
Why AI is Harder Than We Think
Since its beginning in the 1950s, the field of artificial intelligence has cycled several times between periods of optimistic predictions and massive investment ("AI spring") and periods of disappointment, loss of confidence, and reduced funding ("AI winter").
SpaceML: Distributed Open-source Research with Citizen Scientists for the Advancement of Space Technology for NASA
With research organizations focused on an exploding array of fields and resources spread thin, opportunities for the maturation of interdisciplinary research reduce.
Temporal-Relational Hypergraph Tri-Attention Networks for Stock Trend Prediction
Extensive experiments on real-world data demonstrate the effectiveness of our approach.
Refinement type contracts for verification of scientific investigative software
Formal methods for software verification have seen great success in ensuring code correctness but generally require more specialized training, development time, and funding than is available in the natural and social sciences.
Software Engineering
Mean-Variance Efficient Collaborative Filtering for Stock Recommendation
In this regard, we propose a mean-variance efficient collaborative filtering (MVECF) model for stock recommendations that consider both aspects.
Causal Analysis of Customer Churn Using Deep Learning
Causal analysis of the churn model can predict whether a customer will churn in the foreseeable future and assist enterprises to identify effects and possible causes for churn and subsequently use that knowledge to apply tailored incentives.
InvestLM: A Large Language Model for Investment using Financial Domain Instruction Tuning
We present a new financial domain large language model, InvestLM, tuned on LLaMA-65B (Touvron et al., 2023), using a carefully curated instruction dataset related to financial investment.
