Generating semantic hashes using a language model
AssigneeMicrosoft Technology Licensing, LLC
InventorsJoseph Subhi MANSOUR, Malachi Gabriel JONES
Life of this patent
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Abstract
Systems, methods, and computer program products are disclosed for generating semantic hashes using a language model (LM). A semantic hash is generated for an input by determining a plurality of strings from the input, combining the plurality of strings to generate input text, and chunking the input text into a plurality of chunks based on an input limit of the LM. Chunk embeddings are determined for the plurality of chunks using the LM, and combined to generate the semantic hash.
Claims20
A system comprising:
- a processor;
- and
- a memory device comprising program code executable to cause the processor to:
- determine a plurality of strings from an input;
- combine the plurality of strings to generate input text;
- chunk the input text into a plurality of chunks based on an input limit of a language model (LM), the LM configured to generate embeddings based on the semantics of input provided to the LM;
- determine, using the LM, chunk embeddings for the plurality of chunks;
- combine the chunk embeddings to generate a first hash value;
- and
- perform an action based on the first hash value.
A method comprising:
- determining a plurality of strings from an input;
- combining the plurality of strings to generate input text;
- chunking the input text into a plurality of chunks;
- determining, using a language model (LM), embeddings for the plurality of chunks;
- combining the embeddings to generate a first hash value;
- and
- performing an action based on the first hash value.
A computer-readable storage medium comprising executable instructions that are executed by a processor to cause the processor to:
- determine a plurality of strings from an executable;
- combine the plurality of strings to generate input text;
- chunk the input text into a plurality of chunks based on an input limit of a language model (LM), the LM configured to generate embeddings based on the semantics of input provided to the LM;
- determine, using the LM, chunk embeddings for the plurality of chunks;
- combine the chunk embeddings to generate a first hash value;
- and
- determine whether the executable comprises malicious software based on the first hash value.
Dependencies are inferred from the claim text.