conftrace_

model interpretability

519 papers

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Co-occurring keywords

feature attribution (280) text classification (6793) neural network (6616) large language model (13587) explainable ai (480) model explanation (155) language model (4599) attention mechanism (4001) shapley value (206) representation learning (6206)

Papers

On Counterfactual Explanations under Predictive Multiplicity UAI 2020
Interpretations are Useful: Penalizing Explanations to Align Neural Networks with Prior Knowledge ICML 2020
The Explanation Game: Towards Prediction Explainability through Sparse Communication EMNLP 2020
Learning Variational Word Masks to Improve the Interpretability of Neural Text Classifiers EMNLP 2020
BERT-Based Neural Collaborative Filtering and Fixed-Length Contiguous Tokens Explanation AACL 2020
Make Up Your Mind! Adversarial Generation of Inconsistent Natural Language Explanations ACL 2020
Learning Deep Attribution Priors Based On Prior Knowledge NIPS 2020
Interpretable Companions for Black-Box Models AISTATS 2020
LS-Tree: Model Interpretation When the Data Are Linguistic AAAI 2020
NILE : Natural Language Inference with Faithful Natural Language Explanations ACL 2020
Learning to Deceive with Attention-Based Explanations ACL 2020
Causal Shapley Values: Exploiting Causal Knowledge to Explain Individual Predictions of Complex Models NIPS 2020
Gradient-based Analysis of NLP Models is Manipulable EMNLP 2020
An Information Bottleneck Approach for Controlling Conciseness in Rationale Extraction EMNLP 2020
ERASER: A Benchmark to Evaluate Rationalized NLP Models ACL 2020
Generating Hierarchical Explanations on Text Classification via Feature Interaction Detection ACL 2020
Quantifying Attention Flow in Transformers ACL 2020
Perturbed Masking: Parameter-free Probing for Analyzing and Interpreting BERT ACL 2020
A Survey of the State of Explainable AI for Natural Language Processing AACL 2020
Towards Visually Explaining Variational Autoencoders CVPR 2020
Towards Global Explanations of Convolutional Neural Networks With Concept Attribution CVPR 2020
Dynamic Network Pruning with Interpretable Layerwise Channel Selection AAAI 2020
AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models JMLR 2020
SQuINTing at VQA Models: Introspecting VQA Models With Sub-Questions CVPR 2020
Transparent Classification with Multilayer Logical Perceptrons and Random Binarization AAAI 2020