:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Sivaprasad, Sarath, Fritz, Mario
Format:	Preprint
Published:	2023
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2310.00797
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

COMIX: Compositional Explanations using Prototypes
by: Sivaprasad, Sarath, et al.
Published: (2025)

Cooperation, Competition, and Maliciousness: LLM-Stakeholders Interactive Negotiation
by: Abdelnabi, Sahar, et al.
Published: (2023)

Why Don't Prompt-Based Fairness Metrics Correlate?
by: Zayed, Abdelrahman, et al.
Published: (2024)

Attention Mechanisms Don't Learn Additive Models: Rethinking Feature Importance for Transformers
by: Leemann, Tobias, et al.
Published: (2024)

I Know Therefore I Score: Label-Free Crafting of Scoring Functions using Constraints Based on Domain Expertise
by: Palakkadavath, Ragja, et al.
Published: (2022)

Vendi Novelty Scores for Out-of-Distribution Detection
by: Pasarkar, Amey P., et al.
Published: (2026)

Show, Don't Tell: Detecting Novel Objects by Watching Human Videos
by: Akl, James, et al.
Published: (2026)

Experts Don't Cheat: Learning What You Don't Know By Predicting Pairs
by: Johnson, Daniel D., et al.
Published: (2024)

Whitespaces Don't Lie: Feature-Driven and Embedding-Based Approaches for Detecting Machine-Generated Code
by: Nirob, Syed Mehedi Hasan, et al.
Published: (2026)

If You Don't Understand It, Don't Use It: Eliminating Trojans with Filters Between Layers
by: Hernandez, Adriano
Published: (2024)

Don't Freeze, Don't Crash: Extending the Safe Operating Range of Neural Navigation in Dense Crowds
by: Zhang, Jiefu, et al.
Published: (2026)

Don't Lag, RAG: Training-Free Adversarial Detection Using RAG
by: Kazoom, Roie, et al.
Published: (2025)

Don't Forget Imagination!
by: Vityaev, Evgenii E., et al.
Published: (2025)

Out-of-Distribution Detection through Soft Clustering with Non-Negative Kernel Regression
by: Gulati, Aryan, et al.
Published: (2024)

Don't Break the Boundary: Continual Unlearning for OOD Detection Based on Free Energy Repulsion
by: Peng, Ningkang, et al.
Published: (2026)

Position: Don't be Afraid of Over-Smoothing And Over-Squashing
by: Kormann, Niklas, et al.
Published: (2026)

When Models Don't Collapse: On the Consistency of Iterative MLE
by: Barzilai, Daniel, et al.
Published: (2025)

Grow, Don't Overwrite: Fine-tuning Without Forgetting
by: Adila, Dyah, et al.
Published: (2026)

Robust Novelty Detection through Style-Conscious Feature Ranking
by: Smeu, Stefan, et al.
Published: (2023)

Don't Collapse Your Features: Why CenterLoss Hurts OOD Detection and Multi-Scale Mahalanobis Wins
by: Ray, Rahul D
Published: (2026)

Don't Stop Me Now: Embedding Based Scheduling for LLMs
by: Shahout, Rana, et al.
Published: (2024)

We Still Don't Understand High-Dimensional Bayesian Optimization
by: Doumont, Colin, et al.
Published: (2025)

Don't Explain Noise: Robust Counterfactuals for Randomized Ensembles
by: Forel, Alexandre, et al.
Published: (2022)

Transformers Don't In-Context Learn Least Squares Regression
by: Hill, Joshua, et al.
Published: (2025)

ReducedLUT: Table Decomposition with "Don't Care" Conditions
by: Cassidy, Oliver, et al.
Published: (2024)

Don't Walk the Line: Boundary Guidance for Filtered Generation
by: Ball, Sarah, et al.
Published: (2025)

Position: Measure Dataset Diversity, Don't Just Claim It
by: Zhao, Dora, et al.
Published: (2024)

Towards Multiple Missing Values-resistant Unsupervised Graph Anomaly Detection
by: Chen, Jiazhen, et al.
Published: (2025)

Don't Forget the Nonlinearity: Unlocking Activation Functions in Efficient Fine-Tuning
by: Yin, Bo, et al.
Published: (2025)

LoRA and Privacy: When Random Projections Help (and When They Don't)
by: Hu, Yaxi, et al.
Published: (2026)

Don't Trade Off Safety: Diffusion Regularization for Constrained Offline RL
by: Guo, Junyu, et al.
Published: (2025)

Benchmarking is Broken -- Don't Let AI be its Own Judge
by: Cheng, Zerui, et al.
Published: (2025)

Don't Forget It! Conditional Sparse Autoencoder Clamping Works for Unlearning
by: Khoriaty, Matthew, et al.
Published: (2025)

Reasoning Models Don't Just Think Longer, They Move Differently
by: Gjølbye, Anders, et al.
Published: (2026)

I Don't Know: Explicit Modeling of Uncertainty with an [IDK] Token
by: Cohen, Roi, et al.
Published: (2024)

Do's and Don'ts: Learning Desirable Skills with Instruction Videos
by: Kim, Hyunseung, et al.
Published: (2024)

Don't Waste Your Time: Early Stopping Cross-Validation
by: Bergman, Edward, et al.
Published: (2024)

In-flight Novelty Detection with Convolutional Neural Networks
by: Hartwell, Adam, et al.
Published: (2021)

Reconstruction Error-based Anomaly Detection with Few Outlying Examples
by: Angiulli, Fabrizio, et al.
Published: (2023)

Reasoning Models Don't Always Say What They Think
by: Chen, Yanda, et al.
Published: (2025)