Search Results for author:
Found 10 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.
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?
Modeling Link-level Road Traffic Resilience to Extreme Weather Events Using Crowdsourced Data
Climate changes lead to more frequent and intense weather events, posing escalating risks to road traffic.
Investigating disaster response through social media data and the Susceptible-Infected-Recovered (SIR) model: A case study of 2020 Western U.S. wildfire season
Our study details how the SIR model and topic modeling using social media data can provide decision-makers with a quantitative approach to measure disaster response and support their decision-making processes.
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.
