qagnn
LinkBERT
| qagnn | LinkBERT | |
|---|---|---|
| 6 | 2 | |
| 588 | 389 | |
| - | - | |
| 0.0 | 1.8 | |
| about 1 year ago | about 2 years ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
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qagnn
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[D] what percent of top conference papers fudge results?
QA-GNN (https://github.com/michiyasunaga/qagnn from a Stanford lab) had some issues with their evaluation, but more importantly this work 'GNN is counting?...' (https://openreview.net/forum?id=hzmQ4wOnSb) showed that they can achieve better results with an extremely simplistic 1-dim GNN model - so the performance of QA-GNN was mainly due to data. AFAIK there were discussions around this, but now if you go to QA-GNN repo they have disabled issues tab.
- Stanford’s AI Researchers Introduce QA-GNN Model That Jointly Reasons With Language Models And Knowledge Graphs
- [R] Stanford’s AI Researchers Introduce QA-GNN Model That Jointly Reasons With Language Models And Knowledge Graphs
LinkBERT
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[D] Fine tuning LLM - VM requirements.
I am quite new to this - at the stage of experimenting. I would like to fine tune some large language model like LinkBert for instance: https://github.com/michiyasunaga/LinkBERT
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Stanford AI Researchers Propose ‘LinkBERT’: A New Pretraining Method That Improves Language Model Training with Document Links
Continue reading | Check out the paper, github and blog post
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