Malikeh Ehghaghi — accepted AI-conference papers

2026

TokSuite: Measuring the Impact of Tokenizer Choice on Language Model Behavior

Gül Sena Altıntaş, Malikeh Ehghaghi, Brian Lester, Fengyuan Liu, Wanru Zhao, Marco Ciccone +1

ICML 2026oral

Tokenizers provide the fundamental basis through which text is represented and processed by language models (LMs). Despite the importance of tokenization, its role in LM performance and behavior is poorly understood due to the challenge of measuring the impact of tokenization in isolation. To addres…

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2024

Arcee’s MergeKit: A Toolkit for Merging Large Language Models

Charles Goddard, Shamane Siriwardhana, Malikeh Ehghaghi, Luke Meyers, Vladimir Karpukhin, Brian Benedict +2

EMNLP 2024industry

The rapid growth of open-source language models provides the opportunity to merge model checkpoints, combining their parameters to improve performance and versatility. Advances in transfer learning have led to numerous task-specific models, which model merging can integrate into powerful multitask m…

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