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Code and data for the ACL 2023 NLReasoning Workshop paper "Saliency Map Verbalization: Comparing Feature Importance Representations from Model-free and Instruction-based Methods" (Feldhus et al., 2023)

Python 100.00%
chatgpt explainability explainable-nlp feature-attribution integrated-gradients interpretability saliency-maps saliency-methods text-classification transformers

smv's Issues

Add requirements.txt

Please add a requirements file to the repo.

List may be incomplete:

numba
numpy
transformers

Problems keeping track of input-id order

Add thermostat.load option

Hey,

Could you add an option to load arbitrary configurations from Thermostat using thermostat.load()?

Thanks a lot!

Major issue; broken return shape

https://github.com/MNasert/dfki-verbalizer/blob/ced7c268290fffcf658afecbe251b24be05fb2eb/test.py#L50

When running the code as is, the verbalizations and corresponding index, values dictionary gets fused into one dictionary somehow.
Backtrace stops at dataloader.convolution_search / dataloader.span_search

https://github.com/MNasert/dfki-verbalizer/blob/ced7c268290fffcf658afecbe251b24be05fb2eb/dataloader.py#L207
which backtraces to:
https://github.com/MNasert/dfki-verbalizer/blob/ced7c268290fffcf658afecbe251b24be05fb2eb/dataloader.py#L240

These two methods return a tuple that should be unpacked implicitly but it doesnt resulting in dictionary shape:
({any: tuple({any : list})})

Only code changed was in dataloader.py and test.py
yet the problem already occurs in dataloader.py

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