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2020 – today
- 2024
[c8]Marco Schorlemmer, Mohamad Ballout, Kai-Uwe Kühnberger:
Generating Qualitative Descriptions of Diagrams with a Transformer-Based Language Model. Diagrams 2024: 61-75- [c7]Mohamad Ballout, Anne Dedert, Nohayr Abdelmoneim, Ulf Krumnack, Gunther Heidemann, Kai-Uwe Kühnberger:
FOOL ME IF YOU CAN! An Adversarial Dataset to Investigate the Robustness of LMs in Word Sense Disambiguation. EMNLP 2024: 5042-5059 - [c6]Mohamad Ballout, Ulf Krumnack, Gunther Heidemann, Kai-Uwe Kühnberger:
Efficient Knowledge Distillation: Empowering Small Language Models with Teacher Model Insights. NLDB (1) 2024: 32-46 - [c5]Tom Pieper
, Mohamad Ballout, Ulf Krumnack, Gunther Heidemann, Kai-Uwe Kühnberger:
Enhancing Small Language Models via ChatGPT and Dataset Augmentation. NLDB (2) 2024: 269-279 - [i6]Mohamad Ballout, Ulf Krumnack, Gunther Heidemann, Kai-Uwe Kühnberger:
Show Me How It's Done: The Role of Explanations in Fine-Tuning Language Models. CoRR abs/2402.07543 (2024) - [i5]Mohamad Ballout, Ulf Krumnack, Gunther Heidemann, Kai-Uwe Kühnberger:
Efficient Knowledge Distillation: Empowering Small Language Models with Teacher Model Insights. CoRR abs/2409.12586 (2024) - [i4]Tom Pieper, Mohamad Ballout, Ulf Krumnack, Gunther Heidemann, Kai-Uwe Kühnberger:
Enhancing SLM via ChatGPT and Dataset Augmentation. CoRR abs/2409.12599 (2024) - 2023
- [c4]Mohamad Ballout, Ulf Krumnack, Gunther Heidemann, Kai-Uwe Kühnberger:
Show Me How It's Done: The Role of Explanations in Fine-Tuning Language Models. ACML 2023: 90-105 - [c3]Mohamad Ballout, Ulf Krumnack, Gunther Heidemann, Kai-Uwe Kühnberger:
Investigating Pre-trained Language Models on Cross-Domain Datasets, a Step Closer to General AI. INNS DLIA@IJCNN 2023: 94-103 - [c2]Mohamad Ballout, Ulf Krumnack, Gunther Heidemann, Kai-Uwe Kühnberger:
Opening the Black Box: Analyzing Attention Weights and Hidden States in Pre-trained Language Models for Non-language Tasks. xAI (3) 2023: 3-25 - [i3]Mohamad Ballout, Ulf Krumnack, Gunther Heidemann, Kai-Uwe Kühnberger:
Opening the Black Box: Analyzing Attention Weights and Hidden States in Pre-trained Language Models for Non-language Tasks. CoRR abs/2306.12198 (2023) - [i2]Mohamad Ballout, Ulf Krumnack, Gunther Heidemann, Kai-Uwe Kühnberger:
Investigating Pre-trained Language Models on Cross-Domain Datasets, a Step Closer to General AI. CoRR abs/2306.12205 (2023) - 2020
- [c1]Mohamad Ballout, Mohammad Tuqan, Daniel C. Asmar, Elie A. Shammas, George E. Sakr:
The benefits of synthetic data for action categorization. IJCNN 2020: 1-8 - [i1]Mohamad Ballout, Mohammad Tuqan, Daniel C. Asmar, Elie A. Shammas, George E. Sakr:
The benefits of synthetic data for action categorization. CoRR abs/2001.11091 (2020)
Coauthor Index
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