Abstract: Text steganography inherently grapples with a trade-off between embedding capacity and text quality. Although prior work has explored Huffman coding to mitigate this issue, we observe that ...
Abstract: The paper investigated the Huffman coding behavior across datasets consisting of 5 symbols (38,225 rows), 10 symbols (2,977,866 rows), and 15 symbols (9,921,212 rows), under varying ...
An agent is a neural network -- a Transformer, an RNN, a learned function -- that has been trained, through billions of gradient updates on action-sequence data, to perceive an environment, reason ...
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