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Showing 1 to 9 of 9 for “"small language models"”.

  1. Reasoning beyond scale: Structured inference for small language models

    Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01

    uiuc Repository record for Reasoning beyond scale: Structured inference for small language models (opens in a new tab)

  2. Towards the Efficient, Scientific and Accessible Development of Small Language Models

    Language models continue to grow in size, yet our understanding of their inner workings and ability to train them efficiently, particularly smaller models, remains limited. Small (sub-1 billion parameter) models offer practical advantages, including reduced financial and environmental costs, and …

    cambridge Repository record for Towards the Efficient, Scientific and Accessible Development of Small Language Models (opens in a new tab)

  3. Prompt Injection Generation Using Small Language Models with Reinforcement Learning with Artificial Intelligence Feedback

    Large language models (LLMs) have become an integral part of many fields from customer support automation to research assistants. However, despite their growing adoption, they face significant challenges, particularly when it comes to safety in sensitive contexts. Existing methods like …

    mit Repository record for Prompt Injection Generation Using Small Language Models with Reinforcement Learning with Artificial Intelligence Feedback (opens in a new tab)

  4. Towards Label-Efficient Learning: Exploiting Limited Labels and Abundant Unlabeled Data

    … is critical for advancing the capabilities of language models and their downstream systems. This thesis first presents novel methodologies for label-efficient learning, introducing three frameworks: (1) JointMatch, which employs collaborative pseudo-labeling to leverage limited labeled examples …

    uic

  5. Study of Output and Behavior of LLMs Using Confidence Framing in Prompt Engineering

    … prompt engineering is pivotal for shaping Large Language Model (LLM) outputs, the impact of confidence framing on behavioral calibration remains underexplored. This study investigates the ways in which psychological framing, utilizing techniques such as capability praise, role amplification, and …

    embry-riddle Repository record for Study of Output and Behavior of LLMs Using Confidence Framing in Prompt Engineering (opens in a new tab)

  6. Tailoring large language models for zero-shot relation extraction

    Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-19 without embargo terms

    uiuc Repository record for Tailoring large language models for zero-shot relation extraction (opens in a new tab)

  7. Adapting Transformers for Structured Data Domains

    … domains beyond their traditional use in natural language processing (NLP). We revisit key elements of the transformer framework - including input representations, attention formulations, auxiliary tasks, prediction layers and loss functions - and adapt them to better suit the structure and …

    vt Repository record for Adapting Transformers for Structured Data Domains (opens in a new tab)

  8. Advancing Information Extraction with Large Language Models: The Role of Structured Understanding in Knowledge Management and AI Safety

    … scarcity of linguistic resources for non-English languages. This thesis investigates how Large Language Models (LLMs) can overcome these limitations and, conversely, how IE can enhance their reliability and safety. It examines the symbiotic relationship between structured knowledge extraction and …

    cagliari Repository record for Advancing Information Extraction with Large Language Models: The Role of Structured Understanding in Knowledge Management and AI Safety (opens in a new tab)

  9. Extracting thermoelectric materials information using natural language processing

    … this dataset was used to fine-tune a variety of small language models to support information extraction in the thermoelectric materials domain. Throughout this work, a range of methods and resources have been introduced which are novel in their specialised materials science scope. Chapter 1 …

    cambridge Repository record for Extracting thermoelectric materials information using natural language processing (opens in a new tab)