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@AISL-at-Imperial-College-London

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buseskorkmaz/README.md

πŸ‘‹ Hi there! I'm Buse

Welcome to my GitHub profile! I'm a PhD student at Imperial College London, with a focus on Large Language Models. My research aims to improve LLMs by identifying their limitations and enhancing their understanding capabilities.

πŸ” Research Interests

  1. Scientific Language Models

    • Developing models tailored for scientific literature and discourse.
    • Enhancing the accuracy and efficiency of LLMs in understanding and generating scientific content.
  2. Factually Correct Fair Representations

    • Ensuring LLMs generate factually accurate and unbiased outputs.
    • Researching methodologies to mitigate biases and enhance fairness in model predictions.

πŸ§‘β€πŸ’» Professional Experience

  • AI Research Intern @ IBM Research

    • Developed a computational feedback based fine-tuning method for harnessing generative capabilities of large language models on sensitive downstream tasks where human evaluations are ambigious and expensive to obtain.
  • Machine Learning Engineer II @ Comcast NBCUniversal

    • Implemented machine learning solutions to improve the forecasting models for click-rate, video-completion rate and as such metrics.

πŸš€ Current Projects

πŸ“Š GitHub Activity

Buse's GitHub Activity Summary Top Langs


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  1. Integrating-Table-Representations-into-LLMs Integrating-Table-Representations-into-LLMs Public

    This repository hosts the source code and data of paper "Integrating Table Representations into LLMs for Improved Scholarly Document Comprehension" (ACL 2024, Scholarly Document Processing Workshop).

    Python

  2. FMs-at-work FMs-at-work Public

    Jupyter Notebook 1 1

  3. ARTEO ARTEO Public

    This repository hosts the source code of the paper: "Adaptive Real Time Optimization and Exploration for Safety-Critical Systems".

    Jupyter Notebook 3 1

  4. Sentiment-Analysis-with-Deep-Learning Sentiment-Analysis-with-Deep-Learning Public

    Sentiment analysis of financial news by state-of-the-art NLP models and various machine learning models

    Jupyter Notebook 2

  5. Hotel-Recommendation-with-Recommender-Systems Hotel-Recommendation-with-Recommender-Systems Public

    ACM Competition Theme: Providing hotel recommendations through session-based click data.

    Python 1

  6. Return-Detection-with-Machine-Learning Return-Detection-with-Machine-Learning Public

    Data Mining Cup Competition: Detect e-commercial products with a high returning probability based on past data with machine learning models

    Python 1