Concept Bottleneck Models

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ObstaDiff: Generalizable Diffusion Policy Learning via Obstacle-aware Representations
Sep 10, 2026Jiawen Wang, Kevin Yao, Khalid JawedObstacle Avoidance Diffusion Policies
"World Knowledge" in the Weights: Reading Concept Circuits of Vision Transformers
Sep 8, 2026Yanlin Chen, Tang Li, Xi PengVision Transformer Concept-Based Explainability
Are You Thinking What I am Thinking? : Examining Conceptual Separation in Neural Architectures
Sep 1, 2026Jaee Ponde, Roshni Agarwal, Subhashis BanerjeeNeural Architectures Concept Bottleneck Models
Distilling CT Foundation Models into Editable Concept Bottlenecks for Lung Nodule Malignancy Prediction
Aug 8, 2026Fakrul Islam Tushar, Stephen Adamo, Geoffrey D. RubinLung-Nodule Detector Non-Small Cell Lung Cancer
TEMPER: Tensorized Efficient Manifold-constrained Parameterization for Expressive Residual Routing
Aug 8, 2026Yuxuan Gu, Wuyang Zhou, Huijun Xing +1Residual Connections Tensor Networks
ReCBM: Uncertainty-Gated Relational Reasoning for Concept Bottleneck Models
Aug 7, 2026An Sui, Yuzhu Li, Fuping Wu +1Concept Bottleneck Models Uncertainty-Aware Teachers
Mamba with Hierarchical Memory: Solving Representation Bottleneck in Long Sequence Modeling
Aug 3, 2026Qinwen Wang, Jieping Luo, Aoxiang Qin +5Spatial Reverse Mamba Attention Network Biological Memory
HetRoute Heterogeneous and Cost-aware Collaborative Routing Framework for Distributed Edge MoE Inference
Aug 1, 2026Xin Yuan, Ning Li, Wenchao Xu +2Mixture-Of-Expert Inference Edge Computing
The Gate, Not the Cache: Gate Provenance Bounds the Closed-Loop Reliability of Training-Free VLA Token Skipping
Aug 1, 2026Qi Luo, Shuaijun Liu, Hao Zhao +5Vision-Language-Action Closed Loop
Where Quality Breaks in Compressed Short-Text Generation: Staged Bottleneck Localization
Jul 27, 2026Alexey Gavrilov, Alan-Barsag Gazzaev, Sergey MuravyovGenerative Quality Text Generation
Spatially Grounded Concept Bottleneck Models for Trustworthy Breast Ultrasound Diagnosis
Jul 22, 2026Moshiur Rahman Tonmoy, Dunren Che, Haitham Y. Adarbah +1Concept Bottleneck Models Diagnostic Benchmark
Scaling Interpretable Transformers with Parity Bottleneck Layers
Jul 22, 2026Andrew Mack, Kraig Yuheng Tou, Mark Henry +2Sparse Autoencoders Model Interpretability Methods
$\mathtt{Q^2SAR}$ : overcoming classical bottlenecks in drug discovery via quantum multiple kernel learning\mathtt{Q^2SAR}: overcoming classical bottlenecks in drug discovery via quantum multiple kernel learning
Jul 13, 2026Mariano Caruso, Daniel Ruiz, Alejandro Giraldo +1Quantum Kernels Drug Discovery
Naming the Concepts Classifiers Rely On: Language-Anchored Decomposition for Faithful Explanation
Jul 8, 2026Ahsan Habib Akash, Dipkamal Bhusal, Stacey Jones +3Concept-Based Explainability Concept Bottleneck Models
Bumblebee: Interleaved Mixed-Layer Building Blocks for Large-Scale Recommendation Systems
Jul 6, 2026David Bauer, Cancan Zhang, Wenshun Liu +13Representation Learning Concept Bottleneck Models
Compressing the Validation Bottleneck: An Agentic Self-Driving Lab for Scientific Discovery
Jul 5, 2026Kyunghoon Hur, Chihun LeeAgentic Loop Agentic AI Systems
Caption Bottleneck Models
Jul 1, 2026Seref Baris Cagliyan, Umut Ozdemir, Merve Tapli +1Concept Bottleneck Models Model Interpretability Methods
TRACE: A Concept Bottleneck Model for Longitudinal 3D Glioblastoma Response Assessment
Jun 29, 2026Alia Tarek, Hamsa Saberr, Hamza Elghonemy +6Brain Tumor Concept Bottleneck Models
COCOLogic-V2: Identifying Logical Inconsistencies via Truly Hard-Negatives
Jun 26, 2026David Steinmann, Antonia Wüst, Kristian Kersting +1Concept Bottleneck Models Interpretable Machine Learning
Bridging Vision and Language Concepts through Optimal Transport Semantic Flow
Jun 25, 2026Chenyang Zhang, Anqi Dong, Guangming Zhu +4Cross-Modal Concept Bottleneck Models
Olfactory-Inspired Sparse Combinatorial Coding for Low-Resource Named Entity Recognition
Jun 20, 2026Bhushan DeshpandeNamed-Entity Recognition Olfactory Navigation
Compressing Observation History into Agent Memory: Distilling Transformers into Recurrent Transformers
Jun 19, 2026Philippe Weinzaepfel, Christian Wolf, Bülent Mert Sariyildiz +2Recurrent Model Diffusion Transformers
Multimodal Concept Bottleneck Models
Jun 18, 2026Tongqing Shi, Ge Yan, Tuomas Oikarinen +1Concept Bottleneck Models Model Interpretability Methods
Interpreting Neural Combinatorial Optimization via Evolving Programmatic Bottlenecks
Jun 18, 2026Haocheng Duan, Yuxin Guo, Jieyi Bi +4Concept Bottleneck Models Neural Model
Concept Flow Models: Anchoring Concept-Based Reasoning with Hierarchical Bottlenecks
Jun 17, 2026Ya Wang, Adrian PaschkeClass-Incremental Concept Bottleneck Model Concept Bottleneck Models
Moebius: 0.2B Lightweight Image Inpainting Framework with 10B-Level Performance
Jun 17, 2026Kangsheng Duan, Ziyang Xu, Wenyu Liu +3Context-Conditioned Inpainting Faster Inference
Assessing Reliability of Symbol Detection in Concept Bottleneck Models
Jun 15, 2026Javier Fumanal-Idocin, Javier Andreu-PerezClass-Incremental Concept Bottleneck Model Concept Bottleneck Models
3D-CBM: A Framework for Concept-Based Interpretability in Generative 3D Modeling
Jun 9, 2026Ahmad Al-Kabbany3D Concept Bottleneck Models
Formal Concept Lattices are Good Semantic Scaffolds for Concept-Based Learning
Jun 3, 2026Deepika SN Vemuri, Sayanta Adhikari, Ankit Saha +2Concept Bottleneck Models Deep Learning Models
Spatially Grounded Concept Bottleneck Models via Part-Factorized Attention
Jun 3, 2026Dhanesh RamachandramClass-Incremental Concept Bottleneck Model Concept Bottleneck Models
Measuring What Matters: Synthetic Benchmarks for Concept Bottleneck Models
Jun 3, 2026Julian Skirzynski, Harry Cheon, Shreyas Kadekodi +2Class-Incremental Concept Bottleneck Model Concept Bottleneck Models
Learning Label-Efficient Interpretable Medical Image Diagnosis via Semi-supervised Hypergraph Concept Bottleneck Model
Jun 1, 2026Yijun Yang, Ruiqiang Xiao, Lijie Hu +4Medical Imaging Datasets Interpretable Machine Learning
HASTE: Hardware-Aware Dynamic Sparse Training for Large Output Spaces
May 31, 2026Nasib Ullah, Jinbin Zhang, Jean Lucien Randrianantenaina +2Sparsity Multi-Label Classification
CB-SLICE: Concept-Based Interpretable Error Slice Discovery
May 28, 2026Yael Konforti, Mateo Espinosa Zarlenga, Elaf Almahmoud +1Concept-Based Explainability Concept Bottleneck Models
When Interpretability Becomes a Liability: Adversarial Attacks on CBM Concept Layers
May 25, 2026Aditya SridharConcept Bottleneck Models Model Interpretability Methods
The Concept Allocation Zone: Tracking How Concepts Form Across Transformer Depth
May 24, 2026James HenryTransformer Variant Concept Bottleneck Models
ConceptM $^3$ oE: Concept-Guided Multimodal Mixture of Experts for Interpretable Computational PathologyConceptM^3oE: Concept-Guided Multimodal Mixture of Experts for Interpretable Computational Pathology
May 23, 2026Xuan Wang, Zhongling Xu, Gopi Kannedhara +13Pathology Foundation Models Multimodal Clinical Data
Hoeffding Concept Bottleneck Models with Applications to Overhead Images
May 22, 2026Clément Bénard, Manon Arfib, Christophe Labreuche +1Class-Incremental Concept Bottleneck Model Concept Bottleneck Models
What Semantics Survive the Connector? Diagnosing VLM-to-DiT Alignment in Video Editing
May 20, 2026Hangyu Lin, Chao Wen, Chengming Xu +4Video Models Video Large Language Models
Matryoshka Concept Bottleneck Models
May 20, 2026Ziye Chen, Hongbin Lin, Jie Li +1Class-Incremental Concept Bottleneck Model Concept Bottleneck Models
Mix-Quant: Quantized Prefilling, Precise Decoding for Agentic LLMs
May 19, 2026Haiquan Lu, Zigeng Chen, Gongfan Fang +2LLM Inference Efficiency Prefill
Structured Layout Priors for Robust Out-of-Distribution Visual Document Understanding
May 19, 2026Peter El Hachem, Ahmed Nassar, A. Said Gurbuz +2Visual Document Retrieval Document Parsing
CLIF: Concept-Level Influence Functions for Transparent Bottleneck Models
May 19, 2026Yike Sun, Mingkun Xu, Mu You +5Model Interpretability Methods Efficient Influence Function
The Symmetries of Three-Layer ReLU Networks
May 18, 2026Johanna Marie Gegenfurtner, Moritz Grillo, Guido MontúfarRectified Linear Unit Networks Symmetry
Towards Fine-Grained and Verifiable Concept Bottleneck Models
May 14, 2026Yingying Fang, Haijie Xu, Shuang Wu +2Class-Incremental Concept Bottleneck Model Concept Bottleneck Models
Concepts Worth Having: Refining VLM-Guided Concept Bottleneck Models with Minimal Annotations
May 13, 2026Nicola Debole, Andrea Passerini, Stefano Teso +2Concept Bottleneck Models Interpretable Machine Learning
OceanCBM: A Concept Bottleneck Model for Mechanistic Interpretability in Ocean Forecasting
May 12, 2026Sanah Suri, Kieran Ringel, Maike SonnewaldClass-Incremental Concept Bottleneck Model Ocean Dynamics
CATS: Cascaded Adaptive Tree Speculation for Memory-Limited LLM Inference Acceleration
May 11, 2026Yuning Han, Yangchenchen Jin, Dylan Zhao +1Speculative Decoding LLM Inference Efficiency
SLASH the Sink: Sharpening Structural Attention Inside LLMs
May 11, 2026Yiming Liu, Bin Lu, Xinbing Wang +2Concept Bottleneck Models Semantic Reasoning
Architecture, Not Scale: Circuit Localization in Large Language Models
May 9, 2026Sohan VenkateshMechanistic Interpretability Large Language Model Scale
ShifaMind: A Multiplicative Concept Bottleneck for Interpretable ICD-10 Coding
May 8, 2026Mohammed Sameer Syed, Xuan LuInternational Classification Of Disease Codes Concept Bottleneck Models
Radiologist-Guided Causal Concept Bottleneck Models for Chest X-Ray Interpretation
May 8, 2026Amy Rafferty, Rishi Ramaesh, Ajitha RajanChest X-Ray Class-Incremental Concept Bottleneck Model
What If We Let Forecasting Forget? A Sparse Bottleneck for Cross-Variable Dependencies
May 8, 2026Fan Zhang, Shiming Fan, Hua WangTime Series Forecasting Information-Flow Control
Hyperbolic Concept Bottleneck Models
May 7, 2026Daniel Uyterlinde, Swasti Shreya Mishra, Pascal MettesClass-Incremental Concept Bottleneck Model Concept Bottleneck Models
TinySSL: Distilled Self-Supervised Pretraining for Sub-Megabyte MCU Models
May 7, 2026Bibin WilsonSelf-Supervised Learning Model Pretraining
Conceptors for Semantic Steering
May 6, 2026Ilias Triantafyllopoulos, Young-Min Cho, Ren Tao +6Linear Activation Steering Steering
MEMTIER: Tiered Memory Architecture and Retrieval Bottleneck Analysis for Long-Running Autonomous AI Agents
May 5, 2026Bronislav Sidik, Lior RokachAgent Memory Episodic Memory
When Continual Learning Moves to Memory: A Study of Experience Reuse in LLM Agents
Apr 29, 2026Qisheng Hu, Quanyu Long, Wenya WangContinual Learning Large Language Model Agents
Credal Concept Bottleneck Models for Epistemic-Aleatoric Uncertainty Decomposition
Apr 27, 2026Tanmoy Mukherjee, Thomas Bailleux, Pierre Marquis +1Class-Incremental Concept Bottleneck Model Concept Bottleneck Models
REC-CBM: Rubric-Aware Error-Correction Concept Bottleneck Models for Trustworthy Open-Ended Grading
Apr 24, 2026Chengshuai Zhao, Fan Zhang, Kumar Satvik Chaudhary +4Grading Concept Bottleneck Models

Sep 10, 2026 · cs.ROJ/K move · Enter open · S save

ObstaDiff: Generalizable Diffusion Policy Learning via Obstacle-aware Representations

Jiawen Wang, Kevin Yao, Khalid Jawed

Imitation learning has achieved impressive results in robotic manipulation, yet most existing approaches assume clean backgrounds and lack explicit mechanisms for obstacle-aware motion generation. Extending such policies to cluttered, real-world scenes with unstructured obstacles remains a key generalization challenge. We present ObstaDiff, a decomposed diffusion-policy framework with a lightweight obstacle-aware visual encoder. ObstaDiff extracts a structured target-obstacle-background representation, enabling the downstream alignment policy to generate end-effector trajectories toward a target-centered bottleneck pose while reasoning about surrounding obstacles. We evaluate ObstaDiff on 61 real-robot greenhouse trials per method (366 executions in total). ObstaDiff achieves 75.41% average task success and 8.20% average obstacle collision rate, outperforming representative imitation-learning baselines and improving generalization in cluttered agricultural scenes.

Obstacle Avoidance Diffusion Policies Imitation Learning Concept Bottleneck Models

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