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Creators/Authors contains: "Chiu, Justin"

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  1. ; ; ; ; ; ; (, ICLR)
    Free, publicly-accessible full text available April 30, 2026
  2. ; ; ; ; ; ; ; (, ICLR)
    Free, publicly-accessible full text available April 21, 2026
  3. ; ; ; ; ; ; ; (, Neurips)
    Free, publicly-accessible full text available December 9, 2025
  4. ; ; ; ; (, ICLR)
    Language models produce a distribution over the next token; can we use this information to recover the prompt tokens? We consider the problem of language model inversion and show that next-token probabilities contain a surprising amount of information about the preceding text. Often we can recover the text in cases where it is hidden from the user, motivating a method for recovering unknown prompts given only the model's current distribution output. We consider a variety of model access scenarios, and show how even without predictions for every token in the vocabulary we can recover the probability vector through search. On Llama-2 7b, our inversion method reconstructs prompts with a BLEU of 59 and token-level F1 of 78 and recovers 27% of prompts exactly. Code for reproducing all experiments is available at this http URL. 
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    Accepted Manuscript Full Text Available
  5. ; ; ; ; ; (, ACM SIGCOMM)
    Full Text Available 
  6. ; ; ; ; ; ; ; ; ; ; et al (, Association for Computational Linguistics)
    Full Text Available 
  7. ; ; ; (, Association for Computational Linguistics)
  8. ; ; ; (, Association for Computational Linguistics)
    Full Text Available 
  9. ; ; ; ; ; (, Association for Computational Linguistics)
  10. ; ; (, NeuIPS)
    Accepted Manuscript Full Text Available