Search Results for author:
Found 16 papers, 7 papers with code
Surface Defect Saliency of Magnetic Tile
Vision-based detection on surface defects has long postulated in the magnetic tile automation process.
Ranked #1 on
Anomaly Detection
on Surface Defect Saliency of Magnetic Tile
(Segmentation AUROC metric, using extra
training data)
Learning Modulated Loss for Rotated Object Detection
Popular rotated detection methods usually use five parameters (coordinates of the central point, width, height, and rotation angle) to describe the rotated bounding box and l1-loss as the loss function.
Ranked #43 on
Object Detection In Aerial Images
on DOTA
(using extra training data)
Retrieval augmentation of large language models for lay language generation
Recent lay language generation systems have used Transformer models trained on a parallel corpus to increase health information accessibility.
Automated Lay Language Summarization of Biomedical Scientific Reviews
Health literacy has emerged as a crucial factor in making appropriate health decisions and ensuring treatment outcomes.
Personalized Algorithm Generation: A Case Study in Learning ODE Integrators
As a case study, we develop a machine learning approach that automatically learns effective solvers for initial value problems in the form of ordinary differential equations (ODEs), based on the Runge-Kutta (RK) integrator architecture.
Explainable Action Advising for Multi-Agent Reinforcement Learning
This allows the student to self-reflect on what it has learned, enabling advice generalization and leading to improved sample efficiency and learning performance - even in environments where the teacher is sub-optimal.
Multi-agent Reinforcement Learning
reinforcement-learning
+2
Auto-Debias: Debiasing Masked Language Models with Automated Biased Prompts
Specifically, we propose a variant of the beam search method to automatically search for biased prompts such that the cloze-style completions are the most different with respect to different demographic groups.
A Recursively Recurrent Neural Network (R2N2) Architecture for Learning Iterative Algorithms
Meta-learning of numerical algorithms for a given task consists of the data-driven identification and adaptation of an algorithmic structure and the associated hyperparameters.
APPLS: Evaluating Evaluation Metrics for Plain Language Summarization
In response, we introduce POMME, a new metric designed to assess text simplification in PLS; the metric is calculated as the normalized perplexity difference between an in-domain and out-of-domain language model.
Introspective Action Advising for Interpretable Transfer Learning
Transfer learning can be applied in deep reinforcement learning to accelerate the training of a policy in a target task by transferring knowledge from a policy learned in a related source task.
Explaining Agent Behavior with Large Language Models
Intelligent agents such as robots are increasingly deployed in real-world, safety-critical settings.
Is ChatGPT a Financial Expert? Evaluating Language Models on Financial Natural Language Processing
This study compares the performance of encoder-only language models and the decoder-only language models.
Predict the Future from the Past? On the Temporal Data Distribution Shift in Financial Sentiment Classifications
Temporal data distribution shift is prevalent in the financial text.
Personalized Jargon Identification for Enhanced Interdisciplinary Communication
We collect a dataset of over 10K term familiarity annotations from 11 computer science researchers for terms drawn from 100 paper abstracts.
Understanding Your Agent: Leveraging Large Language Models for Behavior Explanation
Intelligent agents such as robots are increasingly deployed in real-world, safety-critical settings.
Advancing Abductive Reasoning in Knowledge Graphs through Complex Logical Hypothesis Generation
Although many applications require the use of knowledge for explanations, the utilization of abductive reasoning in conjunction with structured knowledge, such as a knowledge graph, remains largely unexplored.
