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Found 7 papers, 1 papers with code
Evaluating Zero-Shot GPT-4V Performance on 3D Visual Question Answering Benchmarks
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 influence existing closed-vocabulary datasets.
Unlearning Climate Misinformation in Large Language Models
Misinformation regarding climate change is a key roadblock in addressing one of the most serious threats to humanity.
An LLM-Tool Compiler for Fused Parallel Function Calling
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 thousands of API calls.
GeckOpt: LLM System Efficiency via Intent-Based Tool Selection
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.
GeoLLM-Engine: A Realistic Environment for Building Geospatial Copilots
Geospatial Copilots unlock unprecedented potential for performing Earth Observation (EO) applications through natural language instructions.
Stable Diffusion For Aerial Object Detection
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.
Sign-OPT: A Query-Efficient Hard-label Adversarial Attack
We study the most practical problem setup for evaluating adversarial robustness of a machine learning system with limited access: the hard-label black-box attack setting for generating adversarial examples, where limited model queries are allowed and only the decision is provided to a queried data input.
