Watermarkability: Measuring and Improving Language-Model Compatibility with Logit-Based Watermarks
Language-model watermarks can help identify model-generated text, encode provenance information, and detect post-generat
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← 返回归档列表Language-model watermarks can help identify model-generated text, encode provenance information, and detect post-generat
Methods for training language models on sensitive data differ in how they balance capability gains against the risk of l
Advanced persistent threats (APTs) are a major concern in federated learning (FL) deployments in critical sectors such a
Personally Identifiable Information (PII) detection models must efficiently find identifiers across diverse contexts whi
The Model Context Protocol (MCP) standardizes how AI agents invoke external tools. MCP servers expose tools through a de
We study the problem of approximately counting subgraphs under local node differential privacy (LNDP), a recently introd
Step-level guards decide, before each tool call, whether an agent's next action is safe given the user's request and the
AI agents take actions through tools. Some actions are sensitive, so guards that supervise them must themselves be evalu
Backdoors are among the most impactful attacks against Machine Learning (ML), yet most existing methods assume some form
Recent advances in video generation have increased the demand for reliable watermarking for copyright protection, yet th
Mobile apps have become ubiquitous in daily life. Despite communication encryption, app fingerprinting (AF) attacks can
Proof-of-Work blockchains increasingly rely on transaction fees to keep miners engaged as block subsidies decline. An im
Secure Multi-Party Computation (MPC) is an important enabling technology for data privacy in modern distributed applicat
Generative models now synthesise video that is hard to distinguish from genuine footage, and learned detectors that key
Language embeddings are increasingly used in recommenders to represent item content, but their privacy risks remain poor
Federated learning (FL) is increasingly used to adapt a pretrained, centrally fine-tuned model to data that remain on us
Privacy-preserving protocols can repair a vulnerability without establishing whether it was exploited beforehand, even w
Modern platforms such as Ethereum and Polkadot nowadays execute Byzantine fault-tolerant consensus protocols over large
Tokenized equities trade while listed markets are closed, so their marks could improve off-hours measurement along layer
Let $E$ be chosen uniformly from the geometric isomorphism classes of supersingular elliptic curves over $\overline{\mat