Papers by Zhang Jinshuai

2 papers
Toolscaler: Scalable Generative Tool Calling via Structure-Aware Semantic Tokenization (2025.findings-emnlp)

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Challenge: Extensive experiments demonstrate the effectiveness of SGTC across various tasks.
Approach: They propose a generative tool invocation framework that introduces structure-aware semantic tokenization to encode tools as discrete code sequences.
Outcome: The proposed framework reduces the size of the representation space and underutilizes collaborative signals among tools in downstream tasks.
Provably Secure Generative Linguistic Steganography (2021.findings-acl)

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Challenge: Existing methods of linguistic steganography generate high-security stegotext with statistical differences between the conditional probability distributions of stegot and natural text, which brings about security risks.
Approach: They propose a method which embeds secret information by Adaptive Dynamic Grouping of tokens according to their probability given by an off-the-shelf language model.
Outcome: The proposed method generates steganographic text with perfect security . it is based on three public corpora and proves its security based upon mathematical tests .

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