arXiv (All)
open access
Tracing the Evidence: Faithful Token Attribution Through Vision-Language Reasoning
Large vision-language models (LVLMs) exhibit strong reasoning capabilities, yet the visual and textual evidence supporting the generated responses remains difficult to identify. Faithful token attribution explains an LVLM's response by assigning scores that rank image and prompt tokens by how much t
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
- Lost at the End: Primacy Bias in Multimodal Retrieval-Augmented Question Answering#1110273
- Evaluating Explanation-Driven Vision-Language Reasoning via Generation Order Interventions#1077424
- Twin Worlds: Equivariance-Based Abstention for Evidence-Grounded Reasoning#784787
- Twin Worlds: Equivariance-Based Abstention for Evidence-Grounded Reasoning#783197
- MM-OPD: Towards One More Bottleneck Between Perception and Reasoning#1117021
Record · ID 1141969
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