5 citations · 13 across the 10 of their papers we have counts for
11 papers
DA-RAC: Distance-Aware Calibration of LLM Judges for Trustworthy AI Auditing
Cheng Wu, Vishal Anand, Jaya Krishna Mandivarapu +2
Generative AI systems are increasingly producing real-world artifacts, however their efficacy and validity are often evaluated via context-free LLM-scoring. These judges can be mis…
COLA: Continual Learning via Autoencoder Retrieval of Adapters
Jaya Krishna Mandivarapu
Learning a set of tasks over time, also known as continual learning (CL), is one of the most challenging problems in artificial intelligence due to catastrophic forgetting. Large l…
From Reddit to Generative AI: Evaluating Large Language Models for Anxiety Support Fine-tuned on Social Media Data
Ugur Kursuncu, Trilok Padhi, Gaurav Sinha +3
The growing demand for accessible mental health support, compounded by workforce shortages and logistical barriers, has led to increased interest in utilizing Large Language Models…
Trustful LLMs: Customizing and Grounding Text Generation with Knowledge Bases and Dual Decoders
Xiaofeng Zhu, Jaya Krishna Mandivarapu
Although people are impressed by the content generation skills of large language models, the use of LLMs, such as ChatGPT, is limited by the domain grounding of the content. The co…
Deep Active Learning Using Barlow Twins
Jaya Krishna Mandivarapu, Blake Camp, Rolando Estrada
The generalisation performance of a convolutional neural networks (CNN) is majorly predisposed by the quantity, quality, and diversity of the training images. All the training data…
Real-time Interface Control with Motion Gesture Recognition based on Non-contact Capacitive Sensing
Hunmin Lee, Jaya Krishna Mandivarapu, Nahom Ogbazghi +1
Capacitive sensing is a prominent technology that is cost-effective and low power consuming with fast recognition speed compared to existing sensing systems. On account of these ad…
Domain Agnostic Few-Shot Learning For Document Intelligence
Jaya Krishna Mandivarapu, Eric bunch, Glenn fung
Few-shot learning aims to generalize to novel classes with only a few samples with class labels. Research in few-shot learning has borrowed techniques from transfer learning, metri…
Efficient Document Image Classification Using Region-Based Graph Neural Network
Jaya Krishna Mandivarapu, Eric Bunch, Qian You +1
Document image classification remains a popular research area because it can be commercialized in many enterprise applications across different industries. Recent advancements in l…
Continual Learning with Deep Artificial Neurons
Blake Camp, Jaya Krishna Mandivarapu, Rolando Estrada
Neurons in real brains are enormously complex computational units. Among other things, they're responsible for transforming inbound electro-chemical vectors into outbound action po…
Deep Active Learning via Open Set Recognition
Jaya Krishna Mandivarapu, Blake Camp, Rolando Estrada
In many applications, data is easy to acquire but expensive and time-consuming to label prominent examples include medical imaging and NLP. This disparity has only grown in recent…
Self-Net: Lifelong Learning via Continual Self-Modeling
Blake Camp, Jaya Krishna Mandivarapu, Rolando Estrada
Learning a set of tasks over time, also known as continual learning (CL), is one of the most challenging problems in artificial intelligence. While recent approaches achieve some d…