v1v2 (latest)

Relative representations enable zero-shot latent space communication

International Conference on Learning Representations (ICLR), 2022

30 September 2022

Valentino Maiorca

Francesco Locatello

ArXiv (abs)PDF HTML HuggingFace (1 upvotes)Github (31053★)

Papers citing "Relative representations enable zero-shot latent space communication"

50 / 109 papers shown

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Order-Level Attention Similarity Across Language Models: A Latent Commonality

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Revisiting the Relation Between Robustness and Universality

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Semantic Channel Equalization Strategies for Deep Joint Source-Channel Coding

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202

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Uncovering the Computational Ingredients of Human-Like Representations in LLMs

219

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Beyond Token Probes: Hallucination Detection via Activation Tensors with ACT-ViT

234

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204

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344

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SafeSteer: Adaptive Subspace Steering for Efficient Jailbreak Defense in Vision-Language Models

220

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$$\boldsymbolλ$-Orthogonality Regularization for Compatible Representation Learning$

\boldsymbolλ

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299

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Graph Alignment via Dual-Pass Spectral Encoding and Latent Space Communication

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198

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Transferable Model-agnostic Vision-Language Model Adaptation for Efficient Weak-to-Strong Generalization

222

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Cross-Model Semantics in Representation Learning

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240

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Dynamic Scoring with Enhanced Semantics for Training-Free Human-Object Interaction Detection

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Latent Space Alignment for AI-Native MIMO Semantic Communications

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334

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RIS-aided Latent Space Alignment for Semantic Channel Equalization

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375

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Deep Hidden Cognition Facilitates Reliable Chain-of-Thought Reasoning

227

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With Limited Data for Multimodal Alignment, Let the STRUCTURE Guide You

329

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When Does Closeness in Distribution Imply Representational Similarity? An Identifiability Perspective

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355

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TokAlign: Efficient Vocabulary Adaptation via Token AlignmentAnnual Meeting of the Association for Computational Linguistics (ACL), 2025

256

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Connecting Neural Models Latent Geometries with Relative Geodesic Representations

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Navigating the Latent Space Dynamics of Neural Models

475

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement

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315

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Inference-Time Decomposition of Activations (ITDA): A Scalable Approach to Interpreting Large Language Models

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396

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Causes and Consequences of Representational Similarity in Machine Learning Models

677

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Harnessing the Universal Geometry of Embeddings

661

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LDIR: Low-Dimensional Dense and Interpretable Text Embeddings with Relative RepresentationsAnnual Meeting of the Association for Computational Linguistics (ACL), 2025

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502

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DeepInsert: Early Layer Bypass for Efficient and Performant Multimodal Understanding

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Optimizing LLMs for Italian: Reducing Token Fertility and Enhancing Efficiency Through Vocabulary AdaptationNorth American Chapter of the Association for Computational Linguistics (NAACL), 2025

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TruthPrInt: Mitigating Large Vision-Language Models Object Hallucination Via Latent Truthful-Guided Pre-Intervention

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I Predict Therefore I Am: Is Next Token Prediction Enough to Learn Human-Interpretable Concepts from Data?

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402

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Escaping Plato's Cave: Towards the Alignment of 3D and Text Latent SpacesComputer Vision and Pattern Recognition (CVPR), 2025

403

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Semantic Alignment of Unimodal Medical Text and Vision Representations

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480

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