A5062759258- Digital Rights Management and Security
- Advanced Data Storage Technologies
- Misinformation and Its Impacts
- Information Retrieval and Search Behavior
- Technology and Data Analysis
- Advanced Database Systems and Queries
- Semantic Web and Ontologies
- Data Management and Algorithms
- Diverse Approaches in Healthcare and Education Studies
- Topic Modeling
- Recommender Systems and Techniques
Microsoft (United States)
2024
We present GeoLLM-Squad, a geospatial Copilot that introduces the novel multi-agent paradigm to remote sensing (RS) workflows. Unlike existing single-agent approaches rely on monolithic large language models (LLM), GeoLLM-Squad separates agentic orchestration from task-solving, by delegating RS tasks specialized sub-agents. Built open-source AutoGen and GeoLLM-Engine frameworks, our work enables modular integration of diverse applications, spanning urban monitoring, forestry protection,...
Misinformation regarding climate change is a key roadblock in addressing one of the most serious threats to humanity. This paper investigates factual accuracy large language models (LLMs) information. Using true/false labeled Q&A data for fine-tuning and evaluating LLMs on climate-related claims, we compare open-source models, assessing their ability generate truthful responses questions. We investigate detectability intentionally poisoned with false information, finding that such poisoning...
As Large Language Models (LLMs) broaden their capabilities to manage thousands of API calls, they are confronted with complex data operations across vast datasets significant overhead the underlying system. In this work, we introduce LLM-dCache optimize accesses by treating cache as callable functions exposed tool-augmented agent. We grant LLMs autonomy decisions via prompting, seamlessly integrating existing function-calling mechanisms. Tested on an industry-scale massively parallel...