Development of a Legal Document AI-Chatbot
November 21, 2023 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Pranav Nataraj Devaraj, Rakesh Teja P, Aaryav Gangrade, Manoj Kumar R
arXiv ID
2311.12719
Category
cs.AI: Artificial Intelligence
Citations
6
Venue
arXiv.org
Last Checked
4 months ago
Abstract
With the exponential growth of digital data and the increasing complexity of legal documentation, there is a pressing need for efficient and intelligent tools to streamline the handling of legal documents.With the recent developments in the AI field, especially in chatbots, it cannot be ignored as a very compelling solution to this problem.An insight into the process of creating a Legal Documentation AI Chatbot with as many relevant features as possible within the given time frame is presented.The development of each component of the chatbot is presented in detail.Each component's workings and functionality has been discussed.Starting from the build of the Android app and the Langchain query processing code till the integration of both through a Flask backend and REST API methods.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Artificial Intelligence
π
π
The Cartographer
R.I.P.
π»
Ghosted
Explanation in Artificial Intelligence: Insights from the Social Sciences
R.I.P.
π»
Ghosted
Federated Machine Learning: Concept and Applications
R.I.P.
π»
Ghosted
Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR
R.I.P.
π»
Ghosted
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
R.I.P.
π»
Ghosted
Rainbow: Combining Improvements in Deep Reinforcement Learning
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted