Towards falsifiable interpretability research

22 October 2020

Papers citing "Towards falsifiable interpretability research"

50 / 52 papers shown

STREAM (ChemBio): A Standard for Transparently Reporting Evaluations in AI Model Reports

267

13 Aug 2025

Attribution Explanations for Deep Neural Networks: A Theoretical Perspective

172

11 Aug 2025

Enhancing Uncertainty Estimation and Interpretability via Bayesian Non-negative Decision LayerInternational Conference on Learning Representations (ICLR), 2025

360

28 May 2025

A Mathematical Philosophy of Explanations in Mechanistic Interpretability -- The Strange Science Part I.i

Kola Ayonrinde

Louis Jaburi

MILM

494

01 May 2025

Compositionality Unlocks Deep Interpretable Models

222

03 Apr 2025

Mind the Gap: Bridging the Divide Between AI Aspirations and the Reality of Autonomous Characterization

326

25 Feb 2025

Benchmarking XAI Explanations with Human-Aligned Evaluations

...

436

04 Nov 2024

Confident Teacher, Confident Student? A Novel User Study Design for Investigating the Didactic Potential of Explanations and their Impact on Uncertainty

Teodor Chiaburu

Frank Haußer

Felix Bießmann

178

10 Sep 2024

Auditing Local Explanations is Hard

Robi Bhattacharjee

U. V. Luxburg

LRM MLAU FAtt

242

18 Jul 2024

This Probably Looks Exactly Like That: An Invertible Prototypical Network

Zachariah Carmichael

Timothy Redgrave

Daniel Gonzalez Cedre

Walter J. Scheirer

BDL

316

16 Jul 2024

An Actionability Assessment Tool for Explainable AI

Eduardo Velloso

135

19 Jun 2024

Mechanistic Interpretability for AI Safety -- A Review

Leonard Bereska

E. Gavves

AI4CE

335

298

22 Apr 2024

Acoustic characterization of speech rhythm: going beyond metrics with recurrent neural networks

Franccois Deloche

Laurent Bonnasse-Gahot

Judit Gervain

22 Jan 2024

Artificial Neural Nets and the Representation of Human Concepts

Timo Freiesleben

NAI

341

08 Dec 2023

On the Relationship Between Interpretability and Explainability in Machine Learning

Benjamin Leblanc

Pascal Germain

FaML

412

20 Nov 2023

Training Dynamics of Contextual N-Grams in Language Models

242

01 Nov 2023

Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research DirectionsInformation Fusion (Inf. Fusion), 2023

...

494

369

30 Oct 2023

How Well Do Feature-Additive Explainers Explain Feature-Additive Predictors?

Zachariah Carmichael

Walter J. Scheirer

FAtt

249

27 Oct 2023

Identifying Interpretable Visual Features in Artificial and Biological Neural Systems

272

17 Oct 2023

NeuroInspect: Interpretable Neuron-based Debugging Framework through Class-conditional Visualizations

208

11 Oct 2023

The Blame Problem in Evaluating Local Explanations, and How to Tackle it

Amir Hossein Akhavan Rahnama

ELM FAtt

248

05 Oct 2023

Pixel-Grounded Prototypical Part NetworksIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2023

Zachariah Carmichael

Suhas Lohit

A. Cherian

Michael Jeffrey Jones

Walter J. Scheirer

301

25 Sep 2023

The Hydra Effect: Emergent Self-repair in Language Model Computations

219

28 Jul 2023

Scale Alone Does not Improve Mechanistic Interpretability in Vision ModelsNeural Information Processing Systems (NeurIPS), 2023

Roland S. Zimmermann

Thomas Klein

Wieland Brendel

281

11 Jul 2023

Don't trust your eyes: on the (un)reliability of feature visualizationsInternational Conference on Machine Learning (ICML), 2023

Wieland Brendel

452

07 Jun 2023

Language Models Implement Simple Word2Vec-style Vector ArithmeticNorth American Chapter of the Association for Computational Linguistics (NAACL), 2023

330

25 May 2023

Causal Analysis for Robust Interpretability of Neural NetworksIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2023

310

15 May 2023

Why is plausibility surprisingly problematic as an XAI criterion?

Weina Jin

Xiaoxiao Li

Ghassan Hamarneh

367

30 Mar 2023

The Representational Status of Deep Learning Models

Eamon Duede

289

21 Mar 2023

Tracr: Compiled Transformers as a Laboratory for InterpretabilityNeural Information Processing Systems (NeurIPS), 2023

494

12 Jan 2023

Higher-order mutual information reveals synergistic sub-networks for multi-neuron importance

192

01 Nov 2022

SoK: Explainable Machine Learning for Computer Security ApplicationsEuropean Symposium on Security and Privacy (Euro S&P), 2022

362

22 Aug 2022

Do We Need Another Explainable AI Method? Toward Unifying Post-hoc XAI Evaluation Methods into an Interactive and Multi-dimensional Benchmark

Eyke Hüllermeier

175

08 Jun 2022

Additive MIL: Intrinsically Interpretable Multiple Instance Learning for PathologyNeural Information Processing Systems (NeurIPS), 2022

Aaditya (Adi) Prakash

203

03 Jun 2022

Attribution-based Explanations that Provide Recourse Cannot be RobustJournal of machine learning research (JMLR), 2022

366

31 May 2022

Features of Explainability: How users understand counterfactual and causal explanations for categorical and continuous features in XAI

152

21 Apr 2022

An explainability framework for cortical surface-based deep learning

135

15 Mar 2022

Investigating the fidelity of explainable artificial intelligence methods for applications of convolutional neural networks in geoscienceArtificial Intelligence for the Earth Systems (AI4ES), 2022

Antonios Mamalakis

E. Barnes

I. Ebert‐Uphoff

235

07 Feb 2022

Framework for Evaluating Faithfulness of Local ExplanationsInternational Conference on Machine Learning (ICML), 2022

408

01 Feb 2022

From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AIACM Computing Surveys (ACM CSUR), 2022

611

561

20 Jan 2022

HIVE: Evaluating the Human Interpretability of Visual ExplanationsEuropean Conference on Computer Vision (ECCV), 2021

387

131

06 Dec 2021

Acquisition of Chess Knowledge in AlphaZero

429

189

17 Nov 2021

Grounding Representation Similarity with Statistical Testing

Frances Ding

Jean-Stanislas Denain

Jacob Steinhardt

211

03 Aug 2021

How Well do Feature Visualizations Support Causal Understanding of CNN Activations?

Wieland Brendel

318

23 Jun 2021

The effectiveness of feature attribution methods and its correlation with automatic evaluation scoresNeural Information Processing Systems (NeurIPS), 2021

493

105

31 May 2021

XAI Handbook: Towards a Unified Framework for Explainable AI

133

14 May 2021

Leveraging Sparse Linear Layers for Debuggable Deep NetworksInternational Conference on Machine Learning (ICML), 2021

208

11 May 2021

Two4Two: Evaluating Interpretable Machine Learning - A Synthetic Dataset For Controlled Experiments

M. Schuessler

Philipp Weiß

Leon Sixt

147

06 May 2021

Neural Network Attribution Methods for Problems in Geoscience: A Novel Synthetic Benchmark DatasetEnvironmental Data Science (EDS), 2021

357

18 Mar 2021

If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI TechniquesInternational Joint Conference on Artificial Intelligence (IJCAI), 2021

297

165

26 Feb 2021