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 11 of 11 for “"instruction-tuning"”.
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Instructify: Demystifying Metadata to Visual Instruction Tuning Data Conversion Supplementary Materials
Visual Instruction Tuning (VisIT) data, commonly available as human-assistant conversations with images interleaved in the human turns, are currently the most widespread vehicle for aligning strong LLMs to understand visual inputs, converting them to strong LMMs. While many such VisIT datasets are …
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Advancing Language Equity and Sample Efficiency in Task-Oriented Dialogue Systems
… we propose a question-answering-based supervised instruction tuning approach, with questions capturing the semantics of seen and unseen classes. Proposed approaches were empirically validated across diverse (dialogue and non-dialogue) natural language understanding tasks and languages, …
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Foundation Models for Protein Phenotype Prediction
… a dataset of 33 million protein phenotype instructions, representing a comprehensive resource for multiscale protein phenotypes. By co-training a large language model with multimodal molecular encoders, ProCyon integrates phenotypic and protein data. A novel architecture and instruction …
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Structural Robustness of Transformer Models for Clinical Text Summarization on MIMIC-III
… MedAlpaca exhibited the most severe failures. Instruction-tuning on diverse tasks outperforms biomedical pre-training for structural resilience.
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Domain Adaptation of LLMs for Materials Science: Dataset Curation, Fine-Tuning, and Evaluation Benchmark
… this challenge, the thesis introduces a curated instruction-tuning dataset composed of diverse question-answer (QA) pairs drawn from various materials science sources such as textbooks, property databases, and expert forums. This dataset was used to fine-tune the LLaMA-3-8B-Instruct model, to …
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Towards Large Language Models for Everyone: Instruction Following, Knowledge Retrieval and Multilingualism
… all three challenges. We begin by studying the Instruction Meta-Learning (IML) approach, enabling LLMs to perform an array of tasks by fine-tuning them over pairs of natural language instructions and responses. Our study highlights the efficacy of scaling IML along three axes: fine-tuning task …
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Scalable Data Paradigms for Steering General-Purpose Language Models
… downstream applications, such as following instructions, chatting with users, using tools, or performing complex reasoning, poses another set of challenges that require diverse, high-quality, and increasingly costly training data. This dissertation explores scalable paradigms for …
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Adversarial Risks and Stereotype Mitigation at Scale in Generative Models
… learned stereotypes. This approach uses instruction tuning on general-purpose datasets and mitigates stereotypes implicitly without relying on targeted debiasing techniques. Extensive evaluations on state-of-the-art models demonstrate that our methods substantially reduce harmful …
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Robust foundation model for healthcare
… and Llemr introduces a general framework for instruction-tuning large language models (LLMs) to process and interpret clinical data with complex structures. Building upon these methodological contributions, I co-led the development of PyHealth, an open-source Python library that provides a …
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Next-Generation Intelligent Portfolio Management
… framework for LLMs, finely tuned through instruction tuning to align with human instructions and incorporate market feedback. This approach enables dynamic weight adjustments within the Retrieval-Augmented Generation (RAG) module, showcasing the synergy between extracting more accurate …
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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 …