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Cursor makes its biggest India push yet ahead of SpaceX acquisition with localized pricing4h◆Photonic reservoir computing with complex networks4h◆XS-VLA: Coupling Coarse-grained Spatial Distillation with Latent Flow Matching for Lightweight Robotic Control4h◆Agentic Permissions Policy Algebra for Taint Confinement in LLM Agents4h◆Beyond Squared Error: Exploring Loss Design for Enhanced Training of Generative Flow Networks4h◆The One-Word Census: Answer-Choice Conformity Across 44 Language Models4h◆Creative Integration: A Decidable Criterion of Creativity4h◆BERT-based Models vs. Large Language Models for Low-Resource Named Entity Recognition: A Comparative Study on Marathi4h◆Joint Optimization for Greedy Longest-match Tokenization4h◆Kimi K3: Open Frontier Intelligence4h◆The Few-shot Dilemma: Over-prompting Large Language Models4h◆Speculative Pipeline Decoding: Higher-Accuracy Drafting with Hidden Latency via Pipeline Parallelism4h◆Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram4h◆StageGuard: Physiologically Constrained Sleep Staging4h◆Soft-Constrained Optimization of Latent Space in Variational Autoencoders4h◆Beyond Error-vs-Discard Characteristic: Toward Stable and Reliable Evaluation for Face Image Quality Assessment4h◆Analyzing the Importance of Blank for CTC-Based Knowledge Distillation4h◆Predicting Channel Closures in the Lightning Network with Machine Learning4h◆Evaluation of Blood Vessel Segmentation Methods on Hard-to-Detect Vascular Structures4h◆MOCA: A Transformer-based Modular Causal Inference Framework with One-way Cross-attention and Cutting Feedback4h◆Cursor makes its biggest India push yet ahead of SpaceX acquisition with localized pricing4h◆Photonic reservoir computing with complex networks4h◆XS-VLA: Coupling Coarse-grained Spatial Distillation with Latent Flow Matching for Lightweight Robotic Control4h◆Agentic Permissions Policy Algebra for Taint Confinement in LLM Agents4h◆Beyond Squared Error: Exploring Loss Design for Enhanced Training of Generative Flow Networks4h◆The One-Word Census: Answer-Choice Conformity Across 44 Language Models4h◆Creative Integration: A Decidable Criterion of Creativity4h◆BERT-based Models vs. Large Language Models for Low-Resource Named Entity Recognition: A Comparative Study on Marathi4h◆Joint Optimization for Greedy Longest-match Tokenization4h◆Kimi K3: Open Frontier Intelligence4h◆The Few-shot Dilemma: Over-prompting Large Language Models4h◆Speculative Pipeline Decoding: Higher-Accuracy Drafting with Hidden Latency via Pipeline Parallelism4h◆Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram4h◆StageGuard: Physiologically Constrained Sleep Staging4h◆Soft-Constrained Optimization of Latent Space in Variational Autoencoders4h◆Beyond Error-vs-Discard Characteristic: Toward Stable and Reliable Evaluation for Face Image Quality Assessment4h◆Analyzing the Importance of Blank for CTC-Based Knowledge Distillation4h◆Predicting Channel Closures in the Lightning Network with Machine Learning4h◆Evaluation of Blood Vessel Segmentation Methods on Hard-to-Detect Vascular Structures4h◆MOCA: A Transformer-based Modular Causal Inference Framework with One-way Cross-attention and Cutting Feedback4h◆
Tag

#transfer-learning

8 articles tagged #transfer-learning

arxivJul 13

Pitfalls and Remedies for Multi-Task Bayesian Optimization

arXiv:2607.09073v1 Announce Type: new Abstract: Bayesian optimization routinely warm-starts a target experiment with data from related source tasks, and the multi-task Gaussian process is the textbook surrogate for the job. We revisit this default in a controlled setting and find that it misestimate

GA1 model#machine-learning#optimization#transfer-learningRead on arxiv →
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arxivJul 2bullish

Efficient Multilingual Reasoning Transfer via Progressive Code-Switching

arXiv:2607.00485v1 Announce Type: new Abstract: Large reasoning models (LRMs) have achieved strong reasoning capabilities in English, yet their performance degrades significantly when required to reason in other languages. A natural solution is to transfer the model's English reasoning ability to ta

#language-models#transfer-learning#reasoningRead on arxiv →
arxivJun 25bullish

NeuroShield: A Device-Agnostic Foundation Model for EEG Authentication

arXiv:2606.20673v2 Announce Type: replace Abstract: A central challenge in EEG authentication is that models are typically tied to the acquisition settings in which they are trained. In particular, variations in headset hardware, channel layout, and signal duration create heterogeneous recordings th

NE1 model#eeg#authentication#transfer-learningRead on arxiv →
arxivJun 11bullish

UniReason-Med: A Shared Grounded Reasoning Interface for 2D-to-3D Transfer in Medical VQA

arXiv:2606.11740v1 Announce Type: cross Abstract: We study whether grounded reasoning supervision from abundant 2D medical images can improve 3D medical VQA when both input types are aligned through a common reasoning interface. We introduce UniReason-Med, a single-checkpoint framework that processe

UN1 model#medical-imaging#vqa#grounded-reasoningRead on arxiv →
arxivMay 29

Uncertainty-Aware Transfer Learning for Cross-Building Energy Forecasting: Toward Robust and Scalable District-Level Energy Management

arXiv:2605.29733v1 Announce Type: new Abstract: Scaling data-driven energy forecasting to district level requires models that can be re-used across buildings with minimal target-domain data and honest uncertainty estimates. We present an uncertainty-aware transfer learning (TL) framework for cross-b

TE1 model#energy-forecasting#transfer-learning#uncertainty-estimationRead on arxiv →
arxivMay 26

Universal Activation Verbalizer: A Unified Framework for Cross-Model Activation Explanation

arXiv:2605.25903v1 Announce Type: new Abstract: Activation verbalization explains hidden representations in natural language, but existing methods are mostly limited to self-explanation, where each model explains only its own activations. We introduce Universal Activation Verbalizer (UAV), a framewo

UN1 model#explanation#transfer-learning#natural-languageRead on arxiv →
arxivMay 11bullish

Don't Retrain, Align: Adapting Autoregressive LMs to Diffusion LMs via Representation Alignment

arXiv:2605.06885v1 Announce Type: cross Abstract: Diffusion language models (DLMs) have recently demonstrated capabilities that complement standard autoregressive (AR) models, particularly in non-sequential generation and bidirectional editing. Although recent work has shown that pretrained autoregr

DIAU2 models#diffusion#language-models#representation-learningRead on arxiv →
arxivApr 16

Guided Transfer Learning for Discrete Diffusion Models

arXiv:2512.10877v4 Announce Type: replace Abstract: Discrete diffusion models (DMs) have achieved strong performance in language and other discrete domains, offering a compelling alternative to autoregressive modeling. Yet this performance typically depends on large training datasets, challenging th

#diffusion-models#transfer-learning#language-modelingRead on arxiv →