OLMoTrace: Tracing Language Model Outputs Back to Trillions of Training Tokens · HackerPapers discussions

OLMoTrace: Tracing Language Model Outputs Back to Trillions of Training Tokens — mentioned by lambda

Tue, 08 Sep 2026 18:26:18 GMT

So, one way to prove that the data played no part is to trace and show that it wasn't used in the training process at all. If the data was never used in training, then it couldn't have played a part in the training process. You're right; if the data was used in training, then it gets much trickier; it would be very difficult to show whether some particular data had a significant effect on the outcome. This is one of the big problems with giant models like these; it becomes nearly impossible to discern what is and isn't plagiarism, or copyright violation. It would in theory be possible to have…

Paper and discussion history. A mention is not an endorsement.

OLMoTrace: Tracing Language Model Outputs Back to Trillions of Training Tokens — mentioned by lambda

Tue, 08 Sep 2026 18:12:22 GMT

Yeah, I'm sure it's completely automated. But that doesn't preclude being able to index and track what the sources of data are. For your data sets, I would hope you are including source information for where the data came frome. And at OpenAI's scale, I would presume they are doing some amount of rolling hashing or similar to weed out duplication, training on too much duplicate data can cause problems. AllenAI have at least attempted to add some amount of traceability to their models with OLMoTrace (https://arxiv.org/abs/2504.07096), by letting you find n-gram matches from the outputs in…

Paper and discussion history. A mention is not an endorsement.

OLMoTrace: Tracing Language Model Outputs Back to Trillions of Training Tokens — mentioned by ijk

Mon, 05 May 2025 15:31:04 GMT

A difficult, but not intractable problem: OLMoTrace claims to be able to trace from output to training data in seconds [1]. Notably, it can do this because OLMo itself was intentionally designed to be open and transparent [2]; it was trained on 4.6 trillion tokens of entirely open data (which you can download yourself) [3]. There's nothing stopping Meta or OpenAI from creating a similar tool, other than the obvious detail of that showing their exact training data. [1] https://arxiv.org/abs/2504.07096 [2] https://allenai.org/blog/olmotrace [3]…

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OLMoTrace: Tracing Language Model Outputs Back to Trillions of Training Tokens — mentioned by erlend_sh

Sat, 26 Apr 2025 14:34:14 GMT

Paper: https://arxiv.org/pdf/2504.07096 (original blog title was too long so I used the paper’s title) HF: https://huggingface.co/allenai/OLMo-2-0325-32B-Instruct GH: https://github.com/allenai/infinigram-api

Paper and discussion history. A mention is not an endorsement.