State-Of-The-Art

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State-of-the-Art in Learning-by-Demonstration with Passive Observation for Industrial Assembly Automation
Sep 7, 2026David Koetter, Oliver Petrovic, Christian BrecherManufacturing Perception-Action Loop
LIBERO-RECOVER: Beyond Task Success Towards Failure Recovery in Robotic Manipulation Models
Sep 4, 2026Lin Liu, Zhicheng Bao, Lu Zhang +7State-Of-The-Art
Improved Automatic Target Recognition in Synthetic Aperture Sonar Imagery Using Large Deep Neural Networks
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A Hybrid Neural-Microfacet BRDF Model for Real-Time Rendering
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TCS-BENCH: Benchmarking State-of-the-Art Generative AI Theoretical Computer Science Research Ability
Aug 10, 2026Vincent Cohen-Addad, Dimitris Paparas, Ernest van Wijland +13Benchmarking Large Language Models Reasoning Benchmark
CARE: A Cascaded Framework for Efficient and Reliable Time Series Anomaly Detection
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Semantics of Subterfuge: Benchmarking Legal Deception Detection Against General-domain State-of-the-Art
Jul 31, 2026Theekshana Samaradiwakara, Nisansa de Silva, George C. LobbDeception Natural Language Processing
Parallel Decoding Distillation for Fast Image and Video Generation
Jul 28, 2026Neta Shaul, Chao Liu, Arash Vahdat +1Few-Step Generation Chain-Of-Thought Distillation
Towards Robust Reinforcement Learning for Small-Scale Language Model Agents
Jul 27, 2026Md Rezwanul Haque, Md. Milon Islam, Fakhri KarraySmall Language Models Proximal Policy Optimization
Casting Everything to Online API Services? A Survey of Integrating Localized Speech Recognition Models in Robotic Systems
Jul 13, 2026Sheng Li, Jing Li, Felix Schijve +2Automatic Speech Recognition Systems Llm-Based Automatic Speech Recognition
NatureBench: Can Coding Agents Match the Published SOTA of Nature-Family Papers?
Jun 23, 2026Yuru Wang, Lejun Cheng, Yuxin Zuo +14Scientific Discovery Agentic Benchmarks
Advancing the State-of-the-Art in Empirical Privacy Auditing
Jun 9, 2026Nicole Mitchell, Galen Andrew, Arun Ganesh +2Efficient Privacy Loss Algorithm Auditing
Proposal Refinement for Few-Shot Object Detection
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ProHiFlo: Hierarchical Flow Matching with Functional Guidance for De Novo Protein Generation
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SANA-Streaming: Real-time Streaming Video Editing with Hybrid Diffusion Transformer
May 28, 2026Yuyang Zhao, Yicheng Pan, Qiyuan He +6Video Editing Streaming Video
Laguna M.1/XS.2 Technical Report
May 26, 2026Julien Abadji, Marah Abdin, Connor Adams +93Mixture-Of-Expert Language Models Mle-Bench Lite
Compliant Non-Prehensile Pushing Manipulation
May 25, 2026Francesco Cufino, Mario Selvaggio, Fabio Amadio +1Robust Manipulation Impedance Control
Artificial Intelligence Reshapes Microwave Photonics
May 20, 2026Peng Li, Xihua Zou, Jia Ye +2Photonic Devices State-Of-The-Art
Position: State-of-the-Art Claims Require State-of-the-Art Evidence
May 17, 2026YongKyung OhArtificial Intelligence Benchmarks State-Of-The-Art
ArtifactLinker: Linking Scientific Artifacts for Automatic State-of-the-Art Discovery
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The SMC Blind Spot: A Failure Mode Analysis of State-of-the-Art Beat Tracking
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May 8, 2026Jonathan Hong Jin Ng, Anh Tu Ngo, Anupam ChattopadhyayLarge Language Model Watermarks Watermarking
Look Once, Beam Twice: Camera-Primed Real-Time Double-Directional mmWave Beam Management for Vehicular Connectivity
May 6, 2026Avhishek Biswas, Apala Pramanik, Eylem Ekici +1V2X Millimeter Wave
VLA-ATTC: Adaptive Test-Time Compute for VLA Models with Relative Action Critic Model
May 2, 2026Wenhao Li, Xiu Su, Yichao Cao +5Vision-Language-Action Models Critic-Free Reinforcement Learning
Sentinel-VLA: A Metacognitive VLA Model with Active Status Monitoring for Dynamic Reasoning and Error Recovery
May 2, 2026Wenhao Li, Xiu Su, Dan Niu +6Pretrained Vision-Language-Action Perception-Action Loop
GaMMA: Towards Joint Global-Temporal Music Understanding in Large Multimodal Models
May 1, 2026Zuyao You, Zhesong Yu, Mingyu Liu +3Music Understanding Audio Encoders
Time-series Meets Complex Motion Modeling: Robust and Computational-effective Motion Predictor for Multi-object Tracking
May 1, 2026Nhat-Tan Do, Le-Huy Tu, Nhi Ngoc-Yen Nguyen +2Multi-Object Tracking Human Motion Prediction
Towards Unified Multi-task EEG Analysis with Low-Rank Adaptation
Apr 28, 2026Sicheng Dai, Kai Chen, Hongwang Xiao +2Electroencephalography Spatial Super-Resolution Brain-Computer Interface
PExA: Parallel Exploration Agent for Complex Text-to-SQL
Apr 24, 2026Tanmay Parekh, Ella Hofmann-Coyle, Shuyi Wang +3Text-To-Sql Sql
Breaking Bad: Interpretability-Based Safety Audits of State-of-the-Art LLMs
Apr 22, 2026Krishiv Agarwal, Ramneet Kaur, Colin Samplawski +6Jailbreak Evaluations Llm-As-A-Judge
AutoPPA: Automated Circuit PPA Optimization via Contrastive Code-based Rule Library Learning
Apr 20, 2026Chongxiao Li, Pengwei Jin, Di Huang +14Power Method Register Transfer Level
Audio-Visual Continual Test-Time Adaptation without Forgetting
Feb 20, 2026Sarthak Kumar Maharana, Akshay Mehra, Bhavya Ramakrishna +2Cross-Modal Learning State-Of-The-Art
PERTINENCE: Input-based Opportunistic Neural Network Dynamic Execution
Jul 2, 2025Omkar Shende, Gayathri Ananthanarayanan, Marcello TraiolaGraph Neural Network Inference Neural Network

Sep 7, 2026 · cs.ROJ/K move · Enter open · S save

State-of-the-Art in Learning-by-Demonstration with Passive Observation for Industrial Assembly Automation

David Koetter, Oliver Petrovic, Christian Brecher

RWTH Aachen University, Laboratory for Machine Tools and Production Engineering, Steinbachstraße 19, 52074 Aachen, Germany · Fraunhofer Intitute for Production Technology IPT, Steinbachstraße 17, 52074 Aachen, Germany

Learning-by-Demonstration (LbD) enables intuitive robot programming by capturing expert skills, which is crucial for agility in high-mix, low- volume manufacturing. This systematic literature review analyzes passive LbD for industrial assembly processes, focusing on the perception architecture and the generalization of the perceived demonstration. We specifically investigate one-shot approaches where only a single demonstration is required. The review evaluates how systems adapt to new assemblies using this limited data. We identify a shift towards object-centric perception, allowing learned primitives to be transferred to new product variants with minimal training.

Manufacturing Perception-Action Loop Passive Automated Observation State-Of-The-Art

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