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Found 11 papers, 3 papers with code
Safeguarding System Prompts for LLMs
Large language models (LLMs) are increasingly utilized in applications where system prompts, which guide model outputs, play a crucial role.
JailbreakHunter: A Visual Analytics Approach for Jailbreak Prompts Discovery from Large-Scale Human-LLM Conversational Datasets
To tackle these challenges, we introduce JailbreakHunter, a visual analytics approach for identifying jailbreak prompts in large-scale human-LLM conversational datasets.
CommonsenseVIS: Visualizing and Understanding Commonsense Reasoning Capabilities of Natural Language Models
Specifically, we extract relevant commonsense knowledge in inputs as references to align model behavior with human knowledge.
HAPI: A Large-scale Longitudinal Dataset of Commercial ML API Predictions
HAPI is the first large-scale dataset of ML API usages and is a unique resource for studying ML-as-a-service (MLaaS).
ShortcutLens: A Visual Analytics Approach for Exploring Shortcuts in Natural Language Understanding Dataset
Since shortcuts vary in coverage, productivity, and semantic meaning, it is challenging for NLU experts to systematically understand and avoid them when creating benchmark datasets.
NumGPT: Improving Numeracy Ability of Generative Pre-trained Models
However, those models do not consider the numerical properties of numbers and cannot perform robustly on numerical reasoning tasks (e. g., math word problems and measurement estimation).
M2Lens: Visualizing and Explaining Multimodal Models for Sentiment Analysis
Much research focuses on modeling the complex intra- and inter-modal interactions between different communication channels.
BiGCN: A Bi-directional Low-Pass Filtering Graph Neural Network
Graph convolutional networks (GCNs) have achieved great success on graph-structured data.
GNNLens: A Visual Analytics Approach for Prediction Error Diagnosis of Graph Neural Networks
Two case studies and interviews with domain experts demonstrate the effectiveness of GNNLens in facilitating the understanding of GNN models and their errors.
DeepDrawing: A Deep Learning Approach to Graph Drawing
Node-link diagrams are widely used to facilitate network explorations.
ATMSeer: Increasing Transparency and Controllability in Automated Machine Learning
To guide the design of ATMSeer, we derive a workflow of using AutoML based on interviews with machine learning experts.
