Search Results for author:
Found 11 papers, 6 papers with code
BattleAgent: Multi-modal Dynamic Emulation on Historical Battles to Complement Historical Analysis
This novel system aims to simulate complex dynamic interactions among multiple agents, as well as between agents and their environments, over a period of time.
Large Language Models in Biomedical and Health Informatics: A Bibliometric Review
Large Language Models (LLMs) have rapidly become important tools in Biomedical and Health Informatics (BHI), enabling new ways to analyze data, treat patients, and conduct research.
NPHardEval4V: A Dynamic Reasoning Benchmark of Multimodal Large Language Models
Understanding the reasoning capabilities of Multimodal Large Language Models (MLLMs) is an important area of research.
Health-LLM: Personalized Retrieval-Augmented Disease Prediction System
Compared to traditional health management applications, our system has three main advantages: (1) It integrates health reports and medical knowledge into a large model to ask relevant questions to large language model for disease prediction; (2) It leverages a retrieval augmented generation (RAG) mechanism to enhance feature extraction; (3) It incorporates a semi-automated feature updating framework that can merge and delete features to improve accuracy of disease prediction.
NPHardEval: Dynamic Benchmark on Reasoning Ability of Large Language Models via Complexity Classes
Complex reasoning ability is one of the most important features of current LLMs, which has also been leveraged to play an integral role in complex decision-making tasks.
War and Peace (WarAgent): Large Language Model-based Multi-Agent Simulation of World Wars
Can we avoid wars at the crossroads of history?
DataChat: Prototyping a Conversational Agent for Dataset Search and Visualization
Data users need relevant context and research expertise to effectively search for and identify relevant datasets.
"HOT" ChatGPT: The promise of ChatGPT in detecting and discriminating hateful, offensive, and toxic comments on social media
To investigate this potential, we used ChatGPT and compared its performance with MTurker annotations for three frequently discussed concepts related to harmful content: Hateful, Offensive, and Toxic (HOT).
A Bibliometric Review of Large Language Models Research from 2017 to 2023
Large language models (LLMs) are a class of language models that have demonstrated outstanding performance across a range of natural language processing (NLP) tasks and have become a highly sought-after research area, because of their ability to generate human-like language and their potential to revolutionize science and technology.
A Natural Language Processing Pipeline for Detecting Informal Data References in Academic Literature
The pipeline increases recall for literature to review for inclusion in data-related collections of publications and makes it possible to detect informal data references at scale.
Librarian-in-the-Loop: A Natural Language Processing Paradigm for Detecting Informal Mentions of Research Data in Academic Literature
The librarian-in-the-loop paradigm is centered in the data work performed by ICPSR librarians, supporting broader efforts to build a more comprehensive bibliography of data-related literature that reflects the scholarly communities of research data users.
