conftrace_

model debugging

24 papers

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Co-occurring keywords

influence function (143) model interpretability (519) training datum (124) spurious correlation (279) feature attribution (280) out-of-distribution detection (617) training data attribution (10) vision-language model (2348) neural network (6616) instance attribution (6)

Papers

TAB: Transformer Attention Bottlenecks enable User Intervention and Debugging in Vision-Language Models ICCV 2025
Training with Confidence: Catching Silent Errors in Deep Learning Training with Automated Proactive Checks OSDI 2025
Token-wise Influential Training Data Retrieval for Large Language Models ACL 2024
Theoretical and Practical Perspectives on what Influence Functions Do NIPS 2023
Red Teaming Deep Neural Networks with Feature Synthesis Tools NIPS 2023
IAEval: A Comprehensive Evaluation of Instance Attribution on Natural Language Understanding EMNLP 2023
Error Discovery By Clustering Influence Embeddings NIPS 2023
HiBug: On Human-Interpretable Model Debug NIPS 2023
Class based Influence Functions for Error Detection ACL 2023
3DB: A Framework for Debugging Computer Vision Models NIPS 2022
“Will You Find These Shortcuts?” A Protocol for Evaluating the Faithfulness of Input Salience Methods for Text Classification EMNLP 2022
Debugging and Explaining Metric Learning Approaches: An Influence Function Based Perspective NIPS 2022
Meaningfully debugging model mistakes using conceptual counterfactual explanations ICML 2022
Model Doctor: A Simple Gradient Aggregation Strategy for Diagnosing and Treating CNN Classifiers AAAI 2022
Use-Case-Grounded Simulations for Explanation Evaluation NIPS 2022
Robust Feature-Level Adversaries are Interpretability Tools NIPS 2022
Leveraging Sparse Linear Layers for Debuggable Deep Networks ICML 2021
Understanding Failures of Deep Networks via Robust Feature Extraction CVPR 2021
An Empirical Comparison of Instance Attribution Methods for NLP NAACL 2021
Towards Benchmarking the Utility of Explanations for Model Debugging NAACL 2021
Debugging Tests for Model Explanations NIPS 2020
Debugging Sequence-to-Sequence Models with Seq2Seq-Vis EMNLP 2018
Semantically Equivalent Adversarial Rules for Debugging NLP models ACL 2018
Understanding Black-box Predictions via Influence Functions ICML 2017