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 20 of 319 for “"Language Model"”.
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Learning to Interpret Language Model Diffs
Finetuning-induced changes to a model’s weights (a “model diff”) are semantically meaningful but often difficult to interpret. This makes us wonder: can we describe the content of an unknown model diff using natural language? We introduce diff interpretation training, a method that teaches a model …
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An unsupervised head-dependency language model
Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.
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Large language model for programming by example
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-19 without embargo terms
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Input Adaptive Allocation of Language Model Computation
… and self-critique— can improve the quality of language model (LM) outputs in problems spanning code generation, numerical reasoning, and dialog. Existing work typically applies the same decoding procedure for every input to an LM. But not all inputs require the same amount of computation to …
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Large Language Model Routing with Benchmark Datasets
… is a rapidly growing number of open-source Large Language Models (LLMs) and benchmark datasets to compare them. While some models dominate these benchmarks, no single model typically achieves the best accuracy in all tasks and use cases. With a new dataset, it can be difficult to determine which …
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Bail Reform, Large Language Model Risk and Reasoning
… contains three studies. Each asks how rules or language change the choices people and machines make when outcomes are uncertain. The first study, written with Kiran John, evaluates California’s 2020 cashless bail reform. We use propensity score matching on arrestee records from the windows …
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Empower entity set expansion via language model probing
… negative class names by probing a pre-trained language model, and further score each candidate entity based on selected class names. Experiments on two datasets show that our framework generates high-quality class names and outperforms previous state-of-the-art methods significantly.
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Portability of a class-based backoff language model
Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.
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Large Language Model Tools for Project-based Learning
… artificial intelligence (AI), particularly large language models (LLMs), holds promise for addressing these challenges by en- hancing personalized learning, automating administrative tasks, and providing real-time feed- back. To ensure that these AI tools are sustainable and conducive to diverse …
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Surface Realization Using a Featurized Syntactic Statistical Language Model
An important challenge in natural language surface realization is the generation of grammatical sentences from incomplete sentence plans. Realization can be broken into a two-stage process consisting of an over-generating rule-based module followed by a ranker that outputs the most probable …
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Single-Cell Language Model for Transcriptomics & Cell Type Annotation
… grow in size and biological complexity, current models for cell type annotation remain limited in their generalizability and are often evaluated on only a small fraction of the standardized cell types defined in modern ontologies. Current state-of-the-art models for transcriptomic representation …
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Towards an Artificial Neuroscience: Analytics for Language Model Interpretability
The growing deployment of neural language models demands greater understanding of their internal mechanisms. The goal of this thesis is to make progress on understanding the latent computations within large language models (LLMs) to lay the groundwork for monitoring, controlling, and aligning …
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Persuasiveness of text messages generated by machine learning language model
… of our algorithm that applies a machine learning language model to convert the message to be memorable and persuasive. We designed an algorithm that takes an input sentence, and by changing the sentence to be more general in the syntax level, and more distinctive at the lexical level with the …
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Document expansion and language model re-estimation for information retrieval
… from which document representations, such as language models, may be estimated. While document expansion has been shown to improve the effectiveness of ad-hoc document retrieval, our work differs from previous work in a variety of ways. We propose a consistent language modeling approach to …
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Addressing Misalignment in Language Model Deployments through Context-Specific Evaluations
Language model-based applications are increasingly being deployed in the real world across a variety of contexts. While their rapid success has realized benefits for society, ensuring that they are trained to perform according to societal values and expectations is imperative given their potential …
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Analysis of Memory Access Patterns for Large Language Model Inference
… while only a few focus on inference for large models. The training and inference workloads for the same type of model are quite different: in training, the task is to continuously update the weights matrices with knowledge gained from each training datum, while in inference, the workload only …
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Fine-tuning a domain-specific language model for truss structural analysis
… 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 workflow for truss analysis via the …
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Improving problem-solving capabilities of language model: data, architecture and algorithms
Artificial intelligence (AI), particularly large language models (LLMs), has exhibited formidable problem-solving abilities across a myriad of domains. These range from constrained arenas, such as sentiment analysis, to expansive fields including coding and mathematical reasoning. Furthermore, LLMs …
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Towards Interpretable, Equitable, and Safe Language Model Applications in Healthcare and Beyond
Over the past few years, large language models (LLMs) have taken the landscape of natural language processing (NLP) by storm, delivering promising results across various tasks. However, their deployment in high-stakes settings remains challenging due to concerns about interpretability, fairness, …
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Comparative evaluation of conventional search architectures and large language model-based approaches
… in more complex queries. In contrast, large language model (LLM)-based systems, including Gemini and chat generative pre-trained transformer (ChatGPT) with browsing, employ neural embeddings and generative reasoning to deliver contextualised and conversational outputs. While these advances …
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