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Found 4 papers, 1 papers with code
Performance Trade-offs of Watermarking Large Language Models
However, implanting such signals alters the model's output distribution and can have unintended effects when watermarked LLMs are used for downstream applications.
Detecting Pretraining Data from Large Language Models
Min-K% Prob can be applied without any knowledge about the pretraining corpus or any additional training, departing from previous detection methods that require training a reference model on data that is similar to the pretraining data.
InstructEval: Systematic Evaluation of Instruction Selection Methods
In-context learning (ICL) performs tasks by prompting a large language model (LLM) using an instruction and a small set of annotated examples called demonstrations.
Adapting Language Models to Compress Contexts
Transformer-based language models (LMs) are powerful and widely-applicable tools, but their usefulness is constrained by a finite context window and the expensive computational cost of processing long text documents.
