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SemTrace: Source-Grounded Semantic Signatures for Tracing LLM Exposure to Protected Documents

Paper recorded by Signals 4 on 2026-08-30 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-08-30 on arXiv · recorded by Signals 4 on 2026-09-01

Category: cs.CL · 自然语言处理 · first seen 2026-09-01

Abstract

Large language models are increasingly used to read documents and produce downstream text, creating a provenance problem when the document owner cannot control or inspect the model that performs the generation. We introduce SemTrace, a source-grounded semantic watermark for detecting whether a generated review was influenced by a known protected manuscript copy. Rather than biasing token probabili

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#167 most recent of 186 cs.CL papers we have recorded · ↑ newer: How You Ask Shapes What You Get: A Theory-Seeded Measurement of Articu · ↓ older: Which one is banana man? Evaluating vision-language models in multi-tu
Cite this page: SemTrace: Source-Grounded Semantic Signatures for Tracing LLM Exposure to Protected Documents: the #167 most recent of 186 cs.CL papers we have recorded (as of 2026-08-30). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/semtrace-source-grounded-semantic-signatures-for-tracing-llm-exposure-to-protect.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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