arthur-heng / nlgraph

Official repository of "Can Language Models Solve Graph Problems in Natural Language?". NeurIPS 2023 (Spotlight)

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nlgraph's Issues

Shortest_path task problems

When running the shortest_path tasks, I observed two problems:

1. The model is unable to create route directly connecting neighbor nodes. Namely, if the questioned nodes are directly connected, the model will not take this route as the predicted answer. It will always find another longer route.
2. The predicted answers connected nodes with weight = 0. Namely, sometimes the predicted route follows a route that doesn't exist.
   Is there an issue in model training, or is it because of some errors in my operation?
   If it's because of model training, is it possible to clarify in the prompt that "nodes with edge weighing 0 should not be connected"?

process stucked

Hello!

Do you know if this is normal? It has taken 5 minutes and still not moved on the bar. Thanks and I expect your response.

Big Graph can be handeled?

Could the Large Language Model solve bigger graphs, such as Cora or other standard graph settings, which have thousands or more nodes?

file details

Thank you for sharing these data.

I have a few questions regarding the details:

1. Could you kindly clarify on what does the first line number represent in the 'graph*.txt' file?

5 1 2
2 3
2 3
3 2
4 3
4 1

2. As per my understanding, 'main.json' appears to be similar to 'train.json' and 'test.json' in the context of supervised fine-tuning setting?

Maybe add a license

Dear Authors,
Could you please provide a license for this open-source dataset, is it the same as the published paper? Or another, like an MIT license?

Question about the answers of datasets

Dear authors,

Thank you for your amazing contributions to this filed. I'm wondering whether your genration results with cot or bag prompting skills will be released？

Best,
ZY