Measuring the Mixing of Contextual Information in the Transformer

8 March 2022

Papers citing "Measuring the Mixing of Contextual Information in the Transformer"

7 / 7 papers shown

Title
Counterfactuals As a Means for Evaluating Faithfulness of Attribution Methods in Autoregressive Language Models Sepehr Kamahi Yadollah Yaghoobzadeh 30 0 0 21 Aug 2024
Evaluating Human Alignment and Model Faithfulness of LLM Rationale Mohsen Fayyaz Fan Yin Jiao Sun Nanyun Peng 30 3 0 28 Jun 2024
Computational modeling of semantic change Nina Tahmasebi Haim Dubossarsky 26 6 0 13 Apr 2023
"Will You Find These Shortcuts?" A Protocol for Evaluating the Faithfulness of Input Salience Methods for Text Classification Jasmijn Bastings Sebastian Ebert Polina Zablotskaia Anders Sandholm Katja Filippova 102 75 0 14 Nov 2021
Evaluating the Faithfulness of Importance Measures in NLP by Recursively Masking Allegedly Important Tokens and Retraining Andreas Madsen Nicholas Meade Vaibhav Adlakha Siva Reddy 93 35 0 15 Oct 2021
Incorporating Residual and Normalization Layers into Analysis of Masked Language Models Goro Kobayashi Tatsuki Kuribayashi Sho Yokoi Kentaro Inui 153 45 0 15 Sep 2021
All Bark and No Bite: Rogue Dimensions in Transformer Language Models Obscure Representational Quality William Timkey Marten van Schijndel 213 110 0 09 Sep 2021