arXiv (All)
open access
From Topology to Retrieval: Decoding Embedding Spaces with Unified Signatures
Studying the shape of text embedding spaces enhances our understanding of model behavior and how geometry affects downstream task performance. While a range of topological and geometric metrics have been explored, they are typically analyzed in isolation, and the connections between them remain larg
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Aggregating Neighbor Embedding Projection and Rank-Based Manifold Learning for Image Retrieval#822375
- Learning Multimodal Embeddings with Evidence-Aligned Readout#1118732
- Reason What Matters: Retrieval-Grounded Reasoning for Universal Multimodal Embeddings#1258008
- Exploring Attention Sinks in Text-to-Image Transformers from Diffusion and Autoregressive Models#1297689
- Your Prompt Should Do More: Effects of Retrieval Instructions in Embedding Models#1234933
Record · ID 1328351
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive