1 citations · 5 across the 9 of their papers we have counts for
9 papers
Retrieval Mechanisms Surpass Long-Context Scaling in Time Series Forecasting
Rishi Ahuja, Kumar Prateek, Simranjit Singh +1
Time Series Foundation Models (TSFMs) have borrowed the long context paradigm from natural language processing under the premise that feeding more history into the model improves f…
LLM-dCache: Improving Tool-Augmented LLMs with GPT-Driven Localized Data Caching
Simranjit Singh, Michael Fore, Andreas Karatzas +6
As Large Language Models (LLMs) broaden their capabilities to manage thousands of API calls, they are confronted with complex data operations across vast datasets with significant…
Unlearning Climate Misinformation in Large Language Models
Michael Fore, Simranjit Singh, Chaehong Lee +3
Misinformation regarding climate change is a key roadblock in addressing one of the most serious threats to humanity. This paper investigates factual accuracy in large language mod…
Evaluating Zero-Shot GPT-4V Performance on 3D Visual Question Answering Benchmarks
Simranjit Singh, Georgios Pavlakos, Dimitrios Stamoulis
As interest in "reformulating" the 3D Visual Question Answering (VQA) problem in the context of foundation models grows, it is imperative to assess how these new paradigms influenc…
An LLM-Tool Compiler for Fused Parallel Function Calling
Simranjit Singh, Andreas Karatzas, Michael Fore +2
State-of-the-art sequential reasoning in Large Language Models (LLMs) has expanded the capabilities of Copilots beyond conversational tasks to complex function calling, managing th…
GeckOpt: LLM System Efficiency via Intent-Based Tool Selection
Michael Fore, Simranjit Singh, Dimitrios Stamoulis
In this preliminary study, we investigate a GPT-driven intent-based reasoning approach to streamline tool selection for large language models (LLMs) aimed at system efficiency. By…
Evaluating Tool-Augmented Agents in Remote Sensing Platforms
Simranjit Singh, Michael Fore, Dimitrios Stamoulis
Tool-augmented Large Language Models (LLMs) have shown impressive capabilities in remote sensing (RS) applications. However, existing benchmarks assume question-answering input tem…
GeoLLM-Engine: A Realistic Environment for Building Geospatial Copilots
Simranjit Singh, Michael Fore, Dimitrios Stamoulis
Geospatial Copilots unlock unprecedented potential for performing Earth Observation (EO) applications through natural language instructions. However, existing agents rely on overly…
Stable Diffusion For Aerial Object Detection
Yanan Jian, Fuxun Yu, Simranjit Singh +1
Aerial object detection is a challenging task, in which one major obstacle lies in the limitations of large-scale data collection and the long-tail distribution of certain classes.…