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Evaluation

509 papers

Papers per year

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Papers

Towards Verifying Robustness of Neural Networks Against A Family of Semantic Perturbations CVPR 2020
Effectively Unbiased FID and Inception Score and Where to Find Them CVPR 2020
There and Back Again: Revisiting Backpropagation Saliency Methods CVPR 2020
SAM: The Sensitivity of Attribution Methods to Hyperparameters CVPR 2020
Attribution in Scale and Space CVPR 2020
Dataless Model Selection With the Deep Frame Potential CVPR 2020
Learning to Evaluate Perception Models Using Planner-Centric Metrics CVPR 2020
MOCHA: A Dataset for Training and Evaluating Generative Reading Comprehension Metrics EMNLP 2020
What Do Position Embeddings Learn? An Empirical Study of Pre-Trained Language Model Positional Encoding EMNLP 2020
Attention is Not Only a Weight: Analyzing Transformers with Vector Norms EMNLP 2020
Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics EMNLP 2020
Gradient-based Analysis of NLP Models is Manipulable EMNLP 2020
On the Interplay Between Fine-tuning and Sentence-level Probing for Linguistic Knowledge in Pre-trained Transformers EMNLP 2020
WER we are and WER we think we are EMNLP 2020
Assessing Human-Parity in Machine Translation on the Segment Level EMNLP 2020
What Happens To BERT Embeddings During Fine-tuning? EMNLP 2020
On the Interplay Between Fine-tuning and Sentence-Level Probing for Linguistic Knowledge in Pre-Trained Transformers EMNLP 2020
diagNNose: A Library for Neural Activation Analysis EMNLP 2020
Analyzing Neural Discourse Coherence Models EMNLP 2020
Cold Case: The Lost MNIST Digits NIPS 2019
Demystifying Black-box Models with Symbolic Metamodels NIPS 2019
Certifying Geometric Robustness of Neural Networks NIPS 2019
A Benchmark for Interpretability Methods in Deep Neural Networks NIPS 2019
Analyzing Compositionality-Sensitivity of NLI Models AAAI 2019
QADiver: Interactive Framework for Diagnosing QA Models AAAI 2019