🎭 Domain Adaptation - emschwartz · Scour

✖️Cross-encoders arXiv·

Unsupervised Domain Adaptation for Sim-to-Real Object Pose Estimation with Contrastive Alignment and Pseudo-Label Refinement

📦Batch Embeddings arXiv·

Cluster-Specific Localized Drift Detection for Efficient Batch Model Adaptation under Controlled Distribution Shift

🎯Qdrant arXiv·

Scoring Backends Matter More Than Pooling: A Systematic Study of Training-Free Anomalous Sound Detection under Domain Shift

Multi-cancer detection using a computationally efficient CNN with transfer learning

🐘pgvector arXiv·

Deconfounding via Profiled Transfer Learning

🔗ONNX arXiv·

Domain-Shift Aware Neural Networks for Unbalance Characterization in Rotating Systems

📊Vector Databases arXiv·

Neural Architecture Search of Sample Reweighting Networks for Complex Distribution Shift

DSSCNet: A Transfer Learning Framework for Cross-Corpus Dysarthric Speech Severity Classification

Less-relevant results

🎯Qdrant arXiv·

An LLM-based Two-Stage Transformer Framework for Cross-Domain Bearing Fault Diagnosis with Limited Data

🎯Retrieval Systems arXiv·

PETRA: Transforming Web Text for Petroleum-Engineering Domain Adaptation

🔓Open Source AI arXiv·

Simple Domain Generalization Methods are Strong Baselines for Open Domain Generalization

🔤Tokenization arXiv·

Convergence Analysis of Nystr\"om Subsampling in Covariate Shift Adaptation for Misspecified case

Trade-offs in Medical LLM Adaptation: An Empirical Study in French QA

🧠LLM Inference arXiv·

Target-Aware Linear Regression Under Distribution Shift

Domain Generalizable Adaptation of 3D Vision-Language Models via Regularized Fine-Tuning

📊Vector Databases arXiv·

MedTS-TTT: Test-Time Training for Medical Time Series Classification

📇Vector Indexing arXiv·

Invariant Graph Representations for Continuous-Time Dynamic Graphs Under Distribution Shifts

Robust Zero-Shot Generalization for Open-Vocabulary Action Recognition via Task Arithmetic

Toward Parking Spot Occupancy Recognition: A Self-Supervised Approach

Performance and Interpretability of Convolutional, Transformer, and Hybrid Deep Learning Models in Colorectal Histology Classification

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