Dennis Wei

Identifiers

• name variant Dennis Wei 0.60 · backfill

Papers (66)

1. Local Causal Attribution of Chain-of-Thought Reasoning cs.LG · 2026 · author #1
2. Multi-component Causal Tracing in Large Language Models cs.LG · 2026 · author #2
3. Entropy-Aware On-Policy Distillation of Language Models cs.LG · 2026 · author #6
4. CoFrGeNet: Continued Fraction Architectures for Language Generation cs.CL · 2026 · author #3
5. Highlight All the Phrases: Enhancing LLM Transparency through Visual Factuality Indicators cs.HC · 2025 · author #5
6. CoFrNets: Interpretable Neural Architecture Inspired by Continued Fractions cs.LG · 2025 · author #5
7. Agentic AI Needs a Systems Theory cs.AI · 2025 · author #11
8. Identifying Sub-networks in Neural Networks via Functionally Similar Representations cs.LG · 2024 · author #4
9. Split, Unlearn, Merge: Leveraging Data Attributes for More Effective Unlearning in LLMs cs.LG · 2024 · author #3
10. Interventional Causal Discovery in a Mixture of DAGs cs.LG · 2024 · author #3
11. Facilitating Human-LLM Collaboration through Factuality Scores and Source Attributions cs.HC · 2024 · author #6
12. Selective Explanations cs.CY · 2024 · author #2
13. The RealHumanEval: Evaluating Large Language Models' Abilities to Support Programmers cs.SE · 2024 · author #6
14. Multi-Level Explanations for Generative Language Models cs.CL · 2024 · author #2
15. Detectors for Safe and Reliable LLMs: Implementations, Uses, and Limitations cs.LG · 2024 · author #36
16. Causal Bandits with General Causal Models and Interventions stat.ML · 2024 · author #2
17. Trust Regions for Explanations via Black-Box Probabilistic Certification cs.LG · 2024 · author #3
18. Effective Human-AI Teams via Learned Natural Language Rules and Onboarding cs.LG · 2023 · author #3
19. SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation cs.LG · 2023 · author #5
20. Interpretable Differencing of Machine Learning Models cs.LG · 2023 · author #3
21. A Statistical Interpretation of the Maximum Subarray Problem stat.ME · 2023 · author #1
22. Convex Bounds on the Softmax Function with Applications to Robustness Verification cs.LG · 2023 · author #1
23. Who Should Predict? Exact Algorithms For Learning to Defer to Humans cs.LG · 2023 · author #3
24. On the Safety of Interpretable Machine Learning: A Maximum Deviation Approach cs.LG · 2022 · author #1
25. Downstream Fairness Caveats with Synthetic Healthcare Data cs.LG · 2022 · author #3
26. Analogies and Feature Attributions for Model Agnostic Explanation of Similarity Learners cs.LG · 2022 · author #3
27. FROTE: Feedback Rule-Driven Oversampling for Editing Models cs.LG · 2022 · author #2
28. Ground-Truth, Whose Truth? -- Examining the Challenges with Annotating Toxic Text Datasets cs.CL · 2021 · author #3
29. Interpretable and Fair Boolean Rule Sets via Column Generation cs.LG · 2021 · author #4
30. AI Explainability 360: Impact and Design cs.LG · 2021 · author #19
31. Your fairness may vary: Pretrained language model fairness in toxic text classification cs.CL · 2021 · author #2
32. Treatment Effect Estimation using Invariant Risk Minimization cs.LG · 2021 · author #4
33. Optimal Policies for the Homogeneous Selective Labels Problem cs.LG · 2020 · author #1
34. DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks cs.LG · 2020 · author #1
35. Deciding Fast and Slow: The Role of Cognitive Biases in AI-assisted Decision-making cs.HC · 2020 · author #3
36. Consumer-Driven Explanations for Machine Learning Decisions: An Empirical Study of Robustness cs.LG · 2020 · author #2
37. Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing stat.ML · 2019 · author #2
38. One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques cs.AI · 2019 · author #19
39. Characterization of Overlap in Observational Studies cs.LG · 2019 · author #3
40. Teaching AI to Explain its Decisions Using Embeddings and Multi-Task Learning cs.LG · 2019 · author #7
41. Generalized Linear Rule Models cs.LG · 2019 · author #1
42. Optimized Score Transformation for Consistent Fair Classification cs.LG · 2019 · author #1
43. Interpretable Subgroup Discovery in Treatment Effect Estimation with Application to Opioid Prescribing Guidelines cs.LG · 2019 · author #2
44. TED: Teaching AI to Explain its Decisions cs.AI · 2018 · author #2
45. Teaching Meaningful Explanations cs.AI · 2018 · author #7
46. Boolean Decision Rules via Column Generation cs.AI · 2018 · author #3
47. On the Supermodularity of Active Graph-based Semi-supervised Learning with Stieltjes Matrix Regularization stat.ML · 2018 · author #2
48. Distribution-Preserving k-Anonymity stat.ML · 2017 · author #1
49. Optimized Data Pre-Processing for Discrimination Prevention stat.ML · 2017 · author #2
50. Interpretable Two-level Boolean Rule Learning for Classification stat.ML · 2016 · author #2
51. A Constant-Factor Bi-Criteria Approximation Guarantee for $k$-means++ cs.LG · 2016 · author #1
52. Interpretable Two-level Boolean Rule Learning for Classification cs.LG · 2015 · author #2
53. Statistical Estimation and Clustering of Group-invariant Orientation Parameters stat.ML · 2015 · author #2
54. A Dictionary Approach to EBSD Indexing cs.CV · 2015 · author #3
55. Coercive Region-level Registration for Multi-modal Images cs.CV · 2015 · author #2
56. Parameter estimation in spherical symmetry groups stat.ML · 2014 · author #2
57. Robust Binary Hypothesis Testing Under Contaminated Likelihoods cs.IT · 2014 · author #1
58. Adaptive Sensing Resource Allocation Over Multiple Hypothesis Tests stat.ME · 2014 · author #1
59. Resource-Constrained Adaptive Search for Sparse Multi-Class Targets with Varying Importance cs.IT · 2014 · author #3
60. Jointly Sparse Global SIMPLS Regression stat.ME · 2014 · author #4
61. Spectral Correlation Hub Screening of Multivariate Time Series stat.OT · 2014 · author #2
62. Performance Guarantees for Adaptive Estimation of Sparse Signals cs.IT · 2013 · author #1
63. Marginal Likelihoods for Distributed Parameter Estimation of Gaussian Graphical Models stat.ML · 2013 · author #2
64. On two relaxations of quadratically-constrained cardinality minimization math.OC · 2012 · author #1
65. Multistage Adaptive Estimation of Sparse Signals stat.ME · 2012 · author #1
66. Ensemble estimators for multivariate entropy estimation math.ST · 2012 · author #2

Mentions

• 2508.06846 #5 · arxiv_oai · confidence 0.70 Dennis Wei
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• 1410.0950 #1 · arxiv_oai · confidence 0.70 Dennis Wei
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• 1210.1473 #1 · arxiv_oai · confidence 0.70 Dennis Wei
• 1203.5829 #2 · arxiv_oai · confidence 0.70 Dennis Wei
• 1210.5225 #1 · arxiv_oai · confidence 0.70 Dennis Wei
• 2606.21821 #1 · arxiv_oai · confidence 0.70 Dennis Wei
• 1511.07361 #2 · backfill · confidence 0.70 Dennis Wei
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• 2603.07079 #6 · arxiv_oai · confidence 0.70 Dennis Wei
• 2601.21766 #3 · arxiv_oai · confidence 0.70 Dennis Wei
• 1210.5225 #1 · backfill · confidence 0.70 Dennis Wei
• 1210.1473 #1 · backfill · confidence 0.70 Dennis Wei
• 1203.5829 #2 · backfill · confidence 0.70 Dennis Wei
• 2310.12508 #5 · arxiv_oai · confidence 0.70 Dennis Wei

Frequent Coauthors

• Kush R. Varshney 18 shared papers
• Amit Dhurandhar 15 shared papers
• Karthikeyan Natesan Ramamurthy 14 shared papers
• Prasanna Sattigeri 12 shared papers
• Michael Hind 8 shared papers
• Alfred O. Hero III 6 shared papers
• Pin-Yu Chen 6 shared papers
• Elizabeth M. Daly 5 shared papers
• Moninder Singh 5 shared papers
• David Sontag 4 shared papers
• Gregory Newstadt 4 shared papers
• Ioana Baldini 4 shared papers
• Rahul Nair 4 shared papers
• Subhro Das 4 shared papers
• Tian Gao 4 shared papers
• Werner Geyer 4 shared papers
• Yu-hui Chen 4 shared papers
• Yunfeng Zhang 4 shared papers
• Aleksandra Mojsilovi\'c 3 shared papers
• Alfred Hero 3 shared papers