Copertina

Bridging Critical Gaps in Convergent Learning: How Representational Alignment Evolves Across Layers, Training, and Distribution Shifts

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Kapoor, Chaitanya, Srivastava, Sudhanshu, Khosla, Meenakshi
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Neurons and Cognition Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Evaluating Representational Similarity Measures from the Lens of Functional Correspondence
di: Bo, Yiqing, et al.
Pubblicazione: (2024)

Integrated representational signatures strengthen specificity in brains and models
di: Wu, Jialin, et al.
Pubblicazione: (2025)

Metalearning-Informed Competence in Children: Implications for Responsible Brain-Inspired Artificial Intelligence
di: Singh, Chaitanya
Pubblicazione: (2023)

Scale-Invariance Drives Convergence in AI and Brain Representations
di: Yu, Junjie, et al.
Pubblicazione: (2025)

Brain-Language Model Alignment: Insights into the Platonic Hypothesis and Intermediate-Layer Advantage
di: López-Cardona, Ángela, et al.
Pubblicazione: (2025)

Brain-Model Evaluations Need the NeuroAI Turing Test
di: Feather, Jenelle, et al.
Pubblicazione: (2025)

Feature Integration Spaces: Joint Training Reveals Dual Encoding in Neural Network Representations
di: Claflin, Omar
Pubblicazione: (2025)

How Much is Brain Data Worth for Machine Learning?
di: Lewis, Lane, et al.
Pubblicazione: (2026)

Semi-supervised Multimodal Representation Learning through a Global Workspace
di: Devillers, Benjamin, et al.
Pubblicazione: (2023)

Shifting Attention to You: Personalized Brain-Inspired AI Models
di: Zhao, Stephen Chong, et al.
Pubblicazione: (2025)

Disentangling the Factors of Convergence between Brains and Computer Vision Models
di: Raugel, Joséphine, et al.
Pubblicazione: (2025)

An Affective-Taxis Hypothesis for Alignment and Interpretability
di: Sennesh, Eli, et al.
Pubblicazione: (2025)

CRCC: Contrast-Based Robust Cross-Subject and Cross-Site Representation Learning for EEG
di: Wong, Xiaobin, et al.
Pubblicazione: (2026)

Modulating Cross-Modal Convergence with Single-Stimulus, Intra-Modal Dispersion
di: Hosseini, Eghbal A., et al.
Pubblicazione: (2026)

Convergent Representations of Linguistic Constructions in Human and Artificial Neural Systems
di: Ramezani, Pegah, et al.
Pubblicazione: (2026)

Bridging Minds and Machines: Toward an Integration of AI and Cognitive Science
di: Mao, Rui, et al.
Pubblicazione: (2025)

Artificial Consciousness as Interface Representation
di: Prentner, Robert
Pubblicazione: (2025)

Bridging Neuroscience and AI: Environmental Enrichment as a Model for Forward Knowledge Transfer
di: Saxena, Rajat, et al.
Pubblicazione: (2024)

Reason to Play: Behavioral and Brain Alignment Between Frontier LRMs and Human Game Learners
di: Csaba, Botos, et al.
Pubblicazione: (2026)

Bridging scalp and intracranial EEG in BCI via pretrained neural representations and geometric constraint embedding
di: Dong, Yihang, et al.
Pubblicazione: (2026)

Modeling Autonomous Shifts Between Focus State and Mind-Wandering Using a Predictive-Coding-Inspired Variational RNN Model
di: Oyama, Henrique, et al.
Pubblicazione: (2024)

Explaining Human Choice Probabilities with Simple Vector Representations
di: DiBerardino, Peter, et al.
Pubblicazione: (2025)

Bridging Foundation Models and Efficient Architectures: A Modular Brain Imaging Framework with Local Masking and Pretrained Representation Learning
di: Wang, Yanwen, et al.
Pubblicazione: (2025)

Non-Invasive Reconstruction of Intracranial EEG Across the Deep Temporal Lobe from Scalp EEG based on Conditional Normalizing Flow
di: He, Dongyi, et al.
Pubblicazione: (2026)

Exploring Action-Centric Representations Through the Lens of Rate-Distortion Theory
di: Varona, Miguel de Llanza, et al.
Pubblicazione: (2024)

Noumenal Labs White Paper: How To Build A Brain
di: Ramstead, Maxwell J. D., et al.
Pubblicazione: (2025)

AI-Enhanced High-Density NIRS Patch for Real-Time Brain Layer Oxygenation Monitoring in Neurological Emergencies
di: Ji, Minsu, et al.
Pubblicazione: (2025)

Manifolds and Modules: How Function Develops in a Neural Foundation Model
di: Bertram, Johannes, et al.
Pubblicazione: (2025)

The DIME Architecture: A Unified Operational Algorithm for Neural Representation, Dynamics, Control and Integration
di: Vladu, Ionel Cristian, et al.
Pubblicazione: (2026)

Expectation and Acoustic Neural Network Representations Enhance Music Identification from Brain Activity
di: Noguchi, Shogo, et al.
Pubblicazione: (2026)

Predictive Coding Enhances Meta-RL To Achieve Interpretable Bayes-Optimal Belief Representation Under Partial Observability
di: Kuo, Po-Chen, et al.
Pubblicazione: (2025)

Learning Human-Aligned Representations with Contrastive Learning and Generative Similarity
di: Marjieh, Raja, et al.
Pubblicazione: (2024)

A Foundational Theory for Decentralized Sensory Learning
di: Mårtensson, Linus, et al.
Pubblicazione: (2025)

Possible Principles for Aligned Structure Learning Agents
di: Da Costa, Lancelot, et al.
Pubblicazione: (2024)

Critical Learning Periods Emerge Even in Deep Linear Networks
di: Kleinman, Michael, et al.
Pubblicazione: (2023)

Disentangling Representations through Multi-task Learning
di: Vafidis, Pantelis, et al.
Pubblicazione: (2024)

Exploring a Cognitive Architecture for Learning Arithmetic Equations
di: Gawin, Cole
Pubblicazione: (2024)

Concept Alignment
di: Rane, Sunayana, et al.
Pubblicazione: (2024)

Learning in Focus: Detecting Behavioral and Collaborative Engagement Using Vision Transformers
di: Penchala, Sindhuja, et al.
Pubblicazione: (2025)

Deep Learning Classification of EEG Responses to Multi-Dimensional Transcranial Electrical Stimulation
di: Pastor, Alexis Pomares, et al.
Pubblicazione: (2025)