Parameter-Efficient Construction of the Rashomon Slice for Concept Bottleneck Models

arXiv:2511.19636 · cs.LG, cs.AI · Submitted 2025-11-24 · Read on arXiv

cs.LG, cs.AI

Submitted: 2025-11-24

Updated: 2026-09-22

Comments: Accepted to TMLR

Code: https://github.com/ShihanF0/CBMRashomon-Slice

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Accuracy — 60× in this paper · explained in 1 episode
• Cosine Similarity — 11× in this paper · explained in 3 episodes
• Abstention — 9× in this paper · explained in 1 episode
• Regularization — 9× in this paper · explained in 3 episodes
• Adaptation — 5× in this paper · explained in 1 episode
• Alignment — 3× in this paper · explained in 1 episode
• Benchmark — 3× in this paper · explained in 2 episodes
• Calibration — 3× in this paper · explained in 7 episodes
• Downstream Tasks — 3× in this paper · explained in 2 episodes
• International Conference on Machine Learning — 3× in this paper
• Ablation — 2× in this paper · explained in 1 episode
• Accountability — 2× in this paper · explained in 2 episodes
• Centered Kernel Alignment — 2× in this paper
• Consistency — 2× in this paper · explained in 3 episodes
• Equal Opportunity — 2× in this paper
• Generalizability — 2× in this paper · explained in 6 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Interpretability — 2× in this paper · explained in 15 episodes
• LoRA Adapters — 2× in this paper · explained in 3 episodes
• Objective Function — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Basel Cell Carcinoma — 1× in this paper
• Caltech-UCSD Birds-200-2011 — 1× in this paper
• Core — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Low-Rank Adaptation (LoRA) — 1× in this paper · explained in 9 episodes
• Parameter Efficiency — 1× in this paper · explained in 3 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Transferability — 1× in this paper · explained in 4 episodes
• Two-Stage Architecture — 1× in this paper · explained in 2 episodes
• Vision Transformer (ViT) — 1× in this paper · explained in 2 episodes

Sources

• Deep Ensembles: A Loss Landscape Perspective
• Diversity regularization in deep ensembles

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