PLUM-Lab/Incremental_Prompting
[COLING2022] Incremental Prompting: Episodic Memory Prompt for Lifelong Event Detection
This project helps researchers in Natural Language Processing (NLP) analyze text to identify specific events as they continuously learn from new information. It takes text datasets, such as news articles or documents, and outputs an event detection model that improves over time without forgetting previous knowledge. NLP practitioners and researchers focused on dynamic event recognition and machine learning adaptation would find this useful.
No commits in the last 6 months.
Use this if you need an NLP model that can detect new types of events in text data while retaining its ability to recognize previously learned events, adapting continuously.
Not ideal if you are looking for a pre-trained, ready-to-use event detection model for static datasets, or if you don't have access to specialized NLP datasets like ACE.
Stars
10
Forks
1
Language
Python
License
MIT
Category
Last pushed
Aug 03, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/prompt-engineering/PLUM-Lab/Incremental_Prompting"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
THUDM/P-tuning-v2
An optimized deep prompt tuning strategy comparable to fine-tuning across scales and tasks
ucinlp/autoprompt
AutoPrompt: Automatic Prompt Construction for Masked Language Models.
zjunlp/KnowPrompt
[WWW 2022] KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation...
zjunlp/PromptKG
PromptKG Family: a Gallery of Prompt Learning & KG-related research works, toolkits, and paper-list.
princeton-nlp/OptiPrompt
[NAACL 2021] Factual Probing Is [MASK]: Learning vs. Learning to Recall https://arxiv.org/abs/2104.05240