Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 10 of 10 for “"Parameter-Efficient Fine-Tuning"”.
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ScPEFT : a parameter-efficient fine-tuning framework for enhancing single-cell large language models in out-of-context
… To address this, we introduce a single-cell parameter-efficient fine-tuning (scPEFT) framework that integrates learnable, low-dimensional adapters into scLLMs. By freezing the backbone model and updating only the adapter parameters, scPEFT efficiently adapts to specific tasks using limited …
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Training a massively multimodal transformer on YouTube data: pre-training and parameter efficient fine-tuning on HPC infrastructure
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms
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DYNAMIC NEURAL NETWORKS FOR EFFICIENT VISION MODEL INFERENCE
… is hindered by high training overhead from full-parameter fine-tuning and limited application beyond visual perception. This thesis addresses these challenges through three key contributions: Parameter-Efficient Fine-Tuning (PEFT): We demonstrate that dynamic networks can be developed with …
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Exploring Fine-Tuning Techniques for Removing Tamper-Resistant Safeguards for Open-Weight LLMs
… repurposed for malicious tasks via adversarial fine-tuning. In this paper, we evaluate the effectiveness of Tampering Attack Resistance (TAR), a safeguard designed to protect against such adversarial attacks, by exploring its resilience to full-parameter and parameter-efficient fine-tuning. Our …
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Fine-tuning a domain-specific language model for truss structural analysis
This research investigates the feasibility of fine-tuning a domain-specific vison-language and large-language for truss structural analysis. General-purpose AI models often struggle with engineering-specific problems due to insufficient domain knowledge. To address this, we propose a hybrid …
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Investigating Fine-Tuning of Language Models for Multiple-Choice Questions
… method of improving the performance of LLMs is fine-tuning, wherein a model is additionally trained on data from a specified distribution or subject area. We specifically investigate training data properties related to positional bias in fine-tuned language model performance on correctly …
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Efficient Knowledge Transfer and Adaptation for Speech and Beyond
This thesis advances the field of efficient knowledge transfer and adaptation in the realm of speech processing. It is structured to address the limitations of transfer learning in dynamically evolving audio and speech processing contexts, particularly through novel approaches for class-incremental …
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Efficient and Composable Adaptation for Cross-Lingual Transfer
Parameter-efficient fine-tuning (PEFT) has emerged as a important technique for moderating the growing cost of fine-tuning state-of-the-art pre-trained language models. The modular properties of some PEFT techniques, such as reusability, composability and resistance to overfitting, lend them to …
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GNN-Enhanced Hierarchical Federated Learning in Device-to-Device Networks
… the development of collaborative strategies for efficiently fine-tuning large foundation models within the D2D-assisted FL framework, enabling effective adaptation to diverse downstream tasks. To address these challenges, this thesis investigates a Graph Neural Networks (GNN)-enhanced …
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Instruction Mining from Images: Constructing a Synthetic Dataset for Multimodal Learning
… στρατηγικές φιλτραρίσματος, reward modeling και fine-tuning επηρεάζουν την τελική απόδοση των μοντέλων. Αρχικά παρουσιάζονται οι θεωρητικές βάσεις της επεξεργασίας φυσικής γλώσσας, της υπολογιστικής όρασης και των multimodal συστημάτων. Αναλύεται η εξέλιξη από τα distributed word embeddings και …