Is My Model Using the Right Evidence? Systematic Probes for Examining Evidence-Based Tabular Reasoning

Vivek Gupta, Riyaz A. Bhat, Atreya Ghosal, Manish Shrivastava, Maneesh Singh, Vivek Srikumar


Abstract
Neural models command state-of-the-art performance across NLP tasks, including ones involving “reasoning”. Models claiming to reason about the evidence presented to them should attend to the correct parts of the input while avoiding spurious patterns therein, be self-consistent in their predictions across inputs, and be immune to biases derived from their pre-training in a nuanced, context- sensitive fashion. Do the prevalent *BERT- family of models do so? In this paper, we study this question using the problem of reasoning on tabular data. Tabular inputs are especially well-suited for the study—they admit systematic probes targeting the properties listed above. Our experiments demonstrate that a RoBERTa-based model, representative of the current state-of-the-art, fails at reasoning on the following counts: it (a) ignores relevant parts of the evidence, (b) is over- sensitive to annotation artifacts, and (c) relies on the knowledge encoded in the pre-trained language model rather than the evidence presented in its tabular inputs. Finally, through inoculation experiments, we show that fine- tuning the model on perturbed data does not help it overcome the above challenges.
Anthology ID:
2022.tacl-1.38
Volume:
Transactions of the Association for Computational Linguistics, Volume 10
Month:
Year:
2022
Address:
Cambridge, MA
Venue:
TACL
SIG:
Publisher:
MIT Press
Note:
Pages:
659–679
Language:
URL:
https://aclanthology.org/2022.tacl-1.38
DOI:
10.1162/tacl_a_00482
Bibkey:
Cite (ACL):
Vivek Gupta, Riyaz A. Bhat, Atreya Ghosal, Manish Shrivastava, Maneesh Singh, and Vivek Srikumar. 2022. Is My Model Using the Right Evidence? Systematic Probes for Examining Evidence-Based Tabular Reasoning. Transactions of the Association for Computational Linguistics, 10:659–679.
Cite (Informal):
Is My Model Using the Right Evidence? Systematic Probes for Examining Evidence-Based Tabular Reasoning (Gupta et al., TACL 2022)
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PDF:
https://aclanthology.org/2022.tacl-1.38.pdf