Conference

Bridging Crypto with ML-based Solvers: the SAT Formulation and Benchmarks
The Boolean Satisfiability Problem (SAT) plays a crucial role in cryptanalysis, enabling tasks like key recovery and distinguisher …
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GEM: Gaussian Embedding Modeling for Out-of-Distribution Detection in GUI Agents
Graphical user interface (GUI) agents have recently emerged as an intriguing paradigm for human-computer interaction, capable of …
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GuideBench: Benchmarking Domain-Oriented Guideline Following for LLM Agents
Large language models (LLMs) have been widely deployed as autonomous agents capable of following user instructions and making decisions …
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Efficient and Effective Model Extraction
Model extraction aims to steal a functionally similar copy from a machine learning as a service (MLaaS) API with minimal overhead, …
Efficient and Effective Model Extraction
Enhancing Visual Forced Alignment with Local Context-Aware Feature Extraction and Multi-Task Learning
This paper introduces a novel approach to Visual Forced Alignment (VFA), aiming to accurately synchronize utterances with corresponding …
Enhancing Visual Forced Alignment with Local Context-Aware Feature Extraction and Multi-Task Learning
Membership Encoding for Black-Box Neural Network Watermarking
Deep neural network watermarking is an emerging technique for protecting the copyright of models. Most existing black-box watermarking …
Membership Encoding for Black-Box Neural Network Watermarking
MIFAE-Forensics: Masked lmage-Frequency AutoEncoder for DeepFake Detection
With continuously evolving generative models and increasingly diverse face forgery products, there is a growing demand for DeepFake …
MIFAE-Forensics: Masked lmage-Frequency AutoEncoder for DeepFake Detection
Rethinking the Fragility and Robustness of Fingerprints of Deep Neural Networks
Fingerprints characterize deep neural networks that are deployed as black-boxes. To achieve copyright tracing and integrity …
Rethinking the Fragility and Robustness of Fingerprints of Deep Neural Networks
ALIS: Aligned LLM Instruction Security Strategy for Unsafe Input Prompt
In large language models, existing instruction tuning methods may fail to balance the performance with robustness against attacks from …
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Acquiring Clean Language Models from Backdoor Poisoned Datasets by Downscaling Frequency Space
Despite the notable success of language models (LMs) in various natural language processing (NLP) tasks, the reliability of LMs is …
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Acquiring Clean Language Models from Backdoor Poisoned Datasets by Downscaling Frequency Space