{"total":64,"rows":[{"id":"2406.14479","title":"Tracing Representation Progression: Analyzing and Enhancing Layer-Wise Similarity","created":"2024-06-20","cited_by_count":36,"area":null},{"id":"2211.12491","title":"ModelDiff: A Framework for Comparing Learning Algorithms","created":"2022-11-22","cited_by_count":30,"area":null},{"id":"2310.01211","title":"From Bricks to Bridges: Product of Invariances to Enhance Latent Space Communication","created":"2023-10-02","cited_by_count":21,"area":null},{"id":"2405.01012","title":"Correcting Biased Centered Kernel Alignment Measures in Biological and Artificial Neural Networks","created":"2024-05-02","cited_by_count":18,"area":null},{"id":"2405.17022","title":"Compositional Few-Shot Class-Incremental Learning","created":"2024-05-27","cited_by_count":18,"area":null},{"id":"2411.08197","title":"What Representational Similarity Measures Imply about Decodable Information","created":"2024-11-12","cited_by_count":18,"area":null},{"id":"2311.11436","title":"Duality of Bures and Shape Distances with Implications for Comparing Neural Representations","created":"2023-11-19","cited_by_count":15,"area":null},{"id":"2510.05184","title":"Representation Potentials of Foundation Models for Multimodal Alignment: A Survey","created":"2025-10-05","cited_by_count":11,"area":null},{"id":"2605.06510","title":"Is One Layer Enough? Understanding Inference Dynamics in Tabular Foundation Models","created":"2026-05-07","cited_by_count":10,"area":null},{"id":"2503.21150","title":"The Devil is in Low-Level Features for Cross-Domain Few-Shot Segmentation","created":"2025-03-27","cited_by_count":8,"area":null},{"id":"2304.01999","title":"Revisiting the Evaluation of Image Synthesis with GANs","created":"2023-04-04","cited_by_count":7,"area":null},{"id":"2306.07397","title":"Adversarial Attacks on the Interpretation of Neuron Activation Maximization","created":"2023-06-12","cited_by_count":7,"area":null},{"id":"2407.03681","title":"HyperSpace: Hypernetworks for spacing-adaptive image segmentation","created":"2024-07-04","cited_by_count":6,"area":null},{"id":"2503.05283","title":"Escaping Plato's Cave: Towards the Alignment of 3D and Text Latent Spaces","created":"2025-03-07","cited_by_count":6,"area":null},{"id":"2402.01514","title":"Mapping the Multiverse of Latent Representations","created":"2024-02-02","cited_by_count":5,"area":null},{"id":"2511.22150","title":"From Topology to Retrieval: Decoding Embedding Spaces with Unified Signatures","created":"2025-11-27","cited_by_count":5,"area":null},{"id":"2512.04779","title":"YingMusic-Singer: Zero-shot Singing Voice Synthesis and Editing with Annotation-free Melody Guidance","created":"2025-12-04","cited_by_count":5,"area":null},{"id":"2406.15812","title":"Intrinsic Dimension Correlation: uncovering nonlinear connections in multimodal representations","created":"2024-06-22","cited_by_count":4,"area":null},{"id":"2506.02843","title":"Random Registers for Cross-Domain Few-Shot Learning","created":"2025-06-03","cited_by_count":4,"area":null},{"id":"2603.14833","title":"Ablate and Rescue: A Causal Analysis of Residual Stream Hyper-Connections","created":"2026-03-16","cited_by_count":4,"area":null},{"id":"2410.04941","title":"TOAST: Transformer Optimization using Adaptive and Simple Transformations","created":"2024-10-07","cited_by_count":3,"area":null},{"id":"2502.15104","title":"Estimating Neural Representation Alignment from Sparsely Sampled Inputs and Features","created":"2025-02-20","cited_by_count":3,"area":null},{"id":"2506.03110","title":"Revisiting Continuity of Image Tokens for Cross-domain Few-shot Learning","created":"2025-06-03","cited_by_count":3,"area":null},{"id":"2602.23353","title":"SOTAlign: Semi-Supervised Alignment of Unimodal Vision and Language Models via Optimal Transport","created":"2026-02-26","cited_by_count":3,"area":null},{"id":"2605.09969","title":"The Truth Lies Somewhere in the Middle (of the Generated Tokens)","created":"2026-05-11","cited_by_count":3,"area":null},{"id":"2308.10099","title":"Geometric instability of graph neural networks on large graphs","created":"2023-08-19","cited_by_count":2,"area":null},{"id":"2312.03642","title":"Transformer-Powered Surrogates Close the ICF Simulation-Experiment Gap with Extremely Limited Data","created":"2023-12-06","cited_by_count":2,"area":null},{"id":"2507.09839","title":"Stabilizing Black-Box Prompt Optimization with Textual Regularization and Signal Aggregation","created":"2025-07-14","cited_by_count":2,"area":null},{"id":"2601.21624","title":"Training Memory in Deep Neural Networks: Mechanisms, Evidence, and Measurement Gaps","created":"2026-01-29","cited_by_count":2,"area":null},{"id":"2602.01626","title":"Toward Enhancing Representation Learning in Federated Multi-Task Settings","created":"2026-02-02","cited_by_count":2,"area":null},{"id":"2310.11439","title":"From Alexnet to Transformers: Measuring the Non-linearity of Deep Neural Networks with Affine Optimal Transport","created":"2023-10-17","cited_by_count":1,"area":null},{"id":"2406.14183","title":"Latent Functional Maps: a spectral framework for representation alignment","created":"2024-06-20","cited_by_count":1,"area":null},{"id":"2408.13482","title":"MPruner: Optimizing Neural Network Size with CKA-Based Mutual Information Pruning","created":"2024-08-24","cited_by_count":1,"area":null},{"id":"2412.20798","title":"Reconciling Privacy and Explainability in High-Stakes: A Systematic Inquiry","created":"2024-12-30","cited_by_count":1,"area":null},{"id":"2506.06904","title":"Can Biologically Plausible Temporal Credit Assignment Rules Match BPTT for Neural Similarity? E-prop as an Example","created":"2025-06-07","cited_by_count":1,"area":null},{"id":"2602.09826","title":"From FusHa to Folk: Exploring Cross-Lingual Transfer in Arabic Language Models","created":"2026-02-10","cited_by_count":1,"area":null},{"id":"2605.15607","title":"Syntax Without Semantics: Teaching Large Language Models to Code in an Unseen Language","created":"2026-05-15","cited_by_count":1,"area":null},{"id":"2605.21324","title":"Stimulus symmetries can confound representational similarity analyses","created":"2026-05-20","cited_by_count":1,"area":null},{"id":"2606.16379","title":"Scalable and Interpretable Representation Alignment with Ordinal Similarity","created":"2026-06-15","cited_by_count":1,"area":null},{"id":"2609.15498","title":"Same path, different: a mechanistic comparison of looped and stacked transformer encoders on 12-lead ECG","created":"2026-09-14","cited_by_count":1,"area":null},{"id":"2405.03244","title":"Examining Changes in Internal Representations of Continual Learning Models Through Tensor Decomposition","created":"2024-05-06","cited_by_count":0,"area":null},{"id":"2409.14131","title":"Are Music Foundation Models Better at Singing Voice Deepfake Detection? Far-Better Fuse them with Speech Foundation Models","created":"2024-09-21","cited_by_count":0,"area":null},{"id":"2410.00524","title":"Deep Model Interpretation with Limited Data : A Coreset-based Approach","created":"2024-10-01","cited_by_count":0,"area":null},{"id":"2503.02147","title":"Frankenstein Optimizer: Harnessing the Potential by Revisiting Optimization Tricks","created":"2025-03-04","cited_by_count":0,"area":null},{"id":"2510.19427","title":"Revisiting the Relation Between Robustness and Universality","created":"2025-10-22","cited_by_count":0,"area":null},{"id":"2512.12744","title":"Resting Neurons, Active Insights: Robustifying Activation Sparsity in LLMs via Spontaneity","created":"2025-12-14","cited_by_count":0,"area":null},{"id":"2604.17177","title":"Decomposing the Depth Profile of Fine-Tuning","created":"2026-04-19","cited_by_count":0,"area":null},{"id":"2604.22334","title":"FILTR: Extracting Topological Features from Pretrained 3D Models","created":"2026-04-24","cited_by_count":0,"area":null},{"id":"2605.03222","title":"Beyond Activation Alignment: The Geometry of Neural Sensitivity","created":"2026-05-04","cited_by_count":0,"area":null},{"id":"2605.07345","title":"Mean-Pooled Cosine Similarity is Not Length-Invariant: Theory and Cross-Domain Evidence for a Length-Invariant Alternative","created":"2026-05-08","cited_by_count":0,"area":null},{"id":"2605.11608","title":"PRISM: A Geometric Risk Bound for Decomposing Drift into Scale, Shape, and Head","created":"2026-05-12","cited_by_count":0,"area":null},{"id":"2606.14997","title":"AI Engram: In Search of Memory Traces in Artificial Intelligence","created":"2026-06-12","cited_by_count":0,"area":null},{"id":"2608.03690","title":"LAEF: A Lead-Agnostic ECG Foundation Model Towards Point-of-Care Diagnostics","created":"2026-08-04","cited_by_count":0,"area":null},{"id":"2608.14227","title":"Attributing Preprocessing Invariance in Spectral Foundation Models","created":"2026-08-14","cited_by_count":0,"area":null},{"id":"2608.27115","title":"Cross-Lingual Alignment Without Joint Training: Do Monolingual Language Models Converge on Universal Representations?","created":"2026-08-27","cited_by_count":0,"area":null},{"id":"2608.30720","title":"Tracing distinguishability through transformer processing with stochastic LayerNorm","created":"2026-08-31","cited_by_count":0,"area":null},{"id":"2609.03322","title":"How Perturbations Propagate: A Multi-Level Analysis of Robustness in Large Language Models","created":"2026-09-03","cited_by_count":0,"area":null},{"id":"2609.03604","title":"On the Interaction Between Model Compression and Test-Time Adaptation","created":"2026-09-03","cited_by_count":0,"area":null},{"id":"2609.34166","title":"Hidden Activations are not Enough I: Knowledge Matrices as Higher Representations","created":"2026-09-28","cited_by_count":0,"area":null},{"id":"2609.37642","title":"Flattening the Connectome Spectrum: A Spectral Filter for FC Induces a Pretraining Target for fMRI Encoders","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2609.38205","title":"The System Prompt Illusion: How Instruction Preambles Modify Computation in Language Models","created":"2026-09-23","cited_by_count":0,"area":null},{"id":"2610.13476","title":"A Better Metric Will Not Save You: What You Compare Beats How You Compare It","created":"2026-10-09","cited_by_count":0,"area":null},{"id":"2610.17269","title":"Measuring Learned Equivariance: An Information Theoretic Approach","created":"2026-10-12","cited_by_count":0,"area":null},{"id":"2610.18331","title":"Probing the Geometry of Color Representations in Multilingual Language Models","created":"2026-10-13","cited_by_count":0,"area":null}],"next_cursor":null}