{"total":44,"rows":[{"id":"2505.12540","title":"Harnessing the Universal Geometry of Embeddings","created":"2025-05-18","cited_by_count":55,"area":null},{"id":"2211.07394","title":"Composed Image Retrieval with Text Feedback via Multi-grained Uncertainty Regularization","created":"2022-11-14","cited_by_count":45,"area":null},{"id":"2401.05224","title":"Do Vision and Language Encoders Represent the World Similarly?","created":"2024-01-10","cited_by_count":44,"area":null},{"id":"2403.16005","title":"Knowledge-Enhanced Dual-stream Zero-shot Composed Image Retrieval","created":"2024-03-24","cited_by_count":36,"area":null},{"id":"2412.04616","title":"Assessing and Learning Alignment of Unimodal Vision and Language Models","created":"2024-12-05","cited_by_count":32,"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":"2503.24129","title":"It's a (Blind) Match! Towards Vision-Language Correspondence without Parallel Data","created":"2025-03-31","cited_by_count":14,"area":null},{"id":"2410.07610","title":"CSA: Data-efficient Mapping of Unimodal Features to Multimodal Features","created":"2024-10-10","cited_by_count":12,"area":null},{"id":"2403.16986","title":"Dynamic Relative Representations for Goal-Oriented Semantic Communications","created":"2024-03-25","cited_by_count":11,"area":null},{"id":"2406.15057","title":"Latent Space Translation via Inverse Relative Projection","created":"2024-06-21","cited_by_count":10,"area":null},{"id":"2504.13101","title":"Position: An Empirically Grounded Identifiability Theory Will Accelerate Self-Supervised Learning Research","created":"2025-04-17","cited_by_count":9,"area":null},{"id":"2303.00721","title":"Bootstrapping Parallel Anchors for Relative Representations","created":"2023-03-01","cited_by_count":8,"area":null},{"id":"2310.01691","title":"Zero-Shot Continuous Prompt Transfer: Generalizing Task Semantics Across Language Models","created":"2023-10-02","cited_by_count":7,"area":null},{"id":"2411.01494","title":"Finding NeMo: Negative-mined Mosaic Augmentation for Referring Image Segmentation","created":"2024-11-03","cited_by_count":7,"area":null},{"id":"2411.19719","title":"Relative Representations of Latent Spaces enable Efficient Semantic Channel Equalization","created":"2024-11-29","cited_by_count":7,"area":null},{"id":"2505.17101","title":"A quantitative analysis of semantic information in deep representations of text and images","created":"2025-05-21","cited_by_count":7,"area":null},{"id":"2304.14514","title":"Understanding Shared Speech-Text Representations","created":"2023-04-27","cited_by_count":6,"area":null},{"id":"2411.00246","title":"ResiDual Transformer Alignment with Spectral Decomposition","created":"2024-10-31","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":"2305.15483","title":"Weakly Supervised Vision-and-Language Pre-training with Relative Representations","created":"2023-05-24","cited_by_count":5,"area":null},{"id":"2602.06205","title":"Multi-Way Representation Alignment","created":"2026-02-05","cited_by_count":5,"area":null},{"id":"2305.05208","title":"Getting More Juice Out of Your Data: Hard Pair Refinement Enhances Visual-Language Models Without Extra Data","created":"2023-05-09","cited_by_count":4,"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":"2506.01599","title":"Connecting Neural Models Latent Geometries with Relative Geodesic Representations","created":"2025-06-02","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":"2310.00672","title":"GeRA: Label-Efficient Geometrically Regularized Alignment","created":"2023-10-01","cited_by_count":2,"area":null},{"id":"2410.07173","title":"Better Language Models Exhibit Higher Visual Alignment","created":"2024-10-09","cited_by_count":2,"area":null},{"id":"2505.23709","title":"Skin Lesion Phenotyping via Nested Multi-modal Contrastive Learning","created":"2025-05-29","cited_by_count":2,"area":null},{"id":"2312.12641","title":"Robust Point Matching with Distance Profiles","created":"2023-12-19","cited_by_count":1,"area":null},{"id":"2402.19339","title":"Stitching Gaps: Fusing Situated Perceptual Knowledge with Vision Transformers for High-Level Image Classification","created":"2024-02-29","cited_by_count":1,"area":null},{"id":"2505.10354","title":"LDIR: Low-Dimensional Dense and Interpretable Text Embeddings with Relative Representations","created":"2025-05-15","cited_by_count":1,"area":null},{"id":"2510.01030","title":"Uncovering the Computational Ingredients of Human-Like Representations in LLMs","created":"2025-10-01","cited_by_count":1,"area":null},{"id":"2605.16834","title":"Learning Relative Representations for Fine-Grained Multimodal Alignment with Limited Data","created":"2026-05-16","cited_by_count":1,"area":null},{"id":"2607.16789","title":"MultiLoReFT: Decoupling Shared and Modality-Specific Subspaces in Multimodal Learning via Low-Rank Representation Fine-Tuning","created":"2026-07-18","cited_by_count":1,"area":null},{"id":"2411.15557","title":"Semantically Guided Action Anticipation","created":"2024-11-23","cited_by_count":0,"area":null},{"id":"2503.01881","title":"Mapping representations in Reinforcement Learning via Semantic Alignment for Zero-Shot Stitching","created":"2025-02-26","cited_by_count":0,"area":null},{"id":"2601.10096","title":"Multilingual-To-Multimodal (M2M): Unlocking New Languages with Monolingual Text","created":"2026-01-15","cited_by_count":0,"area":null},{"id":"2602.15676","title":"Relative Geometry of Neural Forecasters: Linking Accuracy and Alignment in Learned Latent Geometry","created":"2026-02-17","cited_by_count":0,"area":null},{"id":"2602.19756","title":"Multimodal Dataset Distillation Made Simple by Prototype-Guided Data Synthesis","created":"2026-02-23","cited_by_count":0,"area":null},{"id":"2606.05109","title":"RePercENT: Scaling Disentangled Representation Learning Beyond Two Modalities","created":"2026-06-03","cited_by_count":0,"area":null},{"id":"2609.17094","title":"Hub-Spectral Activation of Latent Multimodal Knowledge","created":"2026-09-15","cited_by_count":0,"area":null},{"id":"2609.24209","title":"Displacement Geometry Captures Platonic Shared Reality Across Models and Modalities","created":"2026-09-21","cited_by_count":0,"area":null},{"id":"2610.03109","title":"Emergent Structure in the Marginal Attention Space of Language Models","created":"2026-10-02","cited_by_count":0,"area":null},{"id":"2610.12781","title":"Representation Alignment from a Few Paired Data via Distilled Optimal Transport","created":"2026-10-08","cited_by_count":0,"area":null}],"next_cursor":null}