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20222026
most citedTime Travel in LLMs: Tracing Data Contamination in Large Language Models

24 citations · 51 across the 11 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.CL2024★ 20 cited

Using Large Language Models for Automated Grading of Student Writing about Science

Chris Impey, Matthew Wenger, Nikhil Garuda +2

Assessing writing in large classes for formal or informal learners presents a significant challenge. Consequently, most large classes, particularly in science, rely on objective as…

cs.CL2024

Data Contamination Report from the 2024 CONDA Shared Task

Oscar Sainz, Iker García-Ferrero, Alon Jacovi +25

The 1st Workshop on Data Contamination (CONDA 2024) focuses on all relevant aspects of data contamination in natural language processing, where data contamination is understood as…

cs.CL2024

Memorization in In-Context Learning

Shahriar Golchin, Mihai Surdeanu, Steven Bethard +2

In-context learning (ICL) has proven to be an effective strategy for improving the performance of large language models (LLMs) with no additional training. However, the exact mecha…

cs.CL2024★ 1 cited

Grading Massive Open Online Courses Using Large Language Models

Shahriar Golchin, Nikhil Garuda, Christopher Impey +1

Massive open online courses (MOOCs) offer free education globally. Despite this democratization of learning, the massive enrollment in these courses makes it impractical for an ins…

cs.CL2024★ 2 cited

Large Language Models As MOOCs Graders

Shahriar Golchin, Nikhil Garuda, Christopher Impey +1

Massive open online courses (MOOCs) unlock the doors to free education for anyone around the globe with access to a computer and the internet. Despite this democratization of learn…