arXiv (All)
open access
Still There, No Longer Seen: Exposing Compression-Induced Risk in Large Vision-Language Models
Visual token compression reduces the inference cost of Large Vision-Language Models (LVLMs). However, aggregate robustness measures do not reveal whether a particular adversarial failure is induced by compression or inherited from the underlying model. We define a compression-specific failure (CSF)
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
- Still There, No Longer Seen: Exposing Compression-Induced Risk in Large Vision-Language Models#1108624
- What Makes Adversarial Examples Transfer Across Deepfake Detectors?#996800
- Uncheatable Eval: Dynamic Compression-Based Evaluation of Language Models#1064054
- The Flaw of Averages: Measuring Benchmark-Level Distributional Robustness#972966
- Why Are LLM Backdoor Defenses Fragmented? A Feature-Level Explanation with Sparse Autoencoders#799607
Record · ID 1129606
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