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09/11/2023
Hi Model, generating 'nice' instead of 'good' is not as bad as generating 'rice'! Towards Context and Semantic Infused Dialogue Generation Loss Function and Evaluation Metric
Over the past two decades, dialogue modeling has made significant stride...
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07/31/2023
L3DMC: Lifelong Learning using Distillation via Mixed-Curvature Space
The performance of a lifelong learning (L3) model degrades when it is tr...
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07/31/2023
Subspace Distillation for Continual Learning
An ultimate objective in continual learning is to preserve knowledge lea...
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07/21/2023
EV-Planner: Energy-Efficient Robot Navigation via Event-Based Physics-Guided Neuromorphic Planner
Vision-based object tracking is an essential precursor to performing aut...
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07/11/2023
Memorization Through the Lens of Curvature of Loss Function Around Samples
Neural networks are overparametrized and easily overfit the datasets the...
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06/27/2023
S-TLLR: STDP-inspired Temporal Local Learning Rule for Spiking Neural Networks
Spiking Neural Networks (SNNs) are biologically plausible models that ha...
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06/24/2023
IERL: Interpretable Ensemble Representation Learning – Combining CrowdSourced Knowledge and Distributed Semantic Representations
Large Language Models (LLMs) encode meanings of words in the form of dis...
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06/23/2023
Knowledge-Infused Self Attention Transformers
Transformer-based language models have achieved impressive success in va...
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06/16/2023
Process Knowledge-infused Learning for Clinician-friendly Explanations
Language models have the potential to assess mental health using social ...
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06/05/2023
Best of Both Worlds: Hybrid SNN-ANN Architecture for Event-based Optical Flow Estimation
Event-based cameras offer a low-power alternative to frame-based cameras...
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06/01/2023
Cook-Gen: Robust Generative Modeling of Cooking Actions from Recipes
As people become more aware of their food choices, food computation mode...
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05/22/2023
FEDORA: Flying Event Dataset fOr Reactive behAvior
The ability of living organisms to perform complex high speed manoeuvers...
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05/13/2023
ProKnow: Process Knowledge for Safety Constrained and Explainable Question Generation for Mental Health Diagnostic Assistance
Current Virtual Mental Health Assistants (VMHAs) provide counseling and ...
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05/08/2023
Knowledge Graph Guided Semantic Evaluation of Language Models For User Trust
A fundamental question in natural language processing is - what kind of ...
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05/08/2023
Global Update Tracking: A Decentralized Learning Algorithm for Heterogeneous Data
Decentralized learning enables the training of deep learning models over...
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05/01/2023
Neurosymbolic AI - Why, What, and How
Humans interact with the environment using a combination of perception -...
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04/14/2023
Fairness in Visual Clustering: A Novel Transformer Clustering Approach
Promoting fairness for deep clustering models in unsupervised clustering...
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04/09/2023
Homogenizing Non-IID datasets via In-Distribution Knowledge Distillation for Decentralized Learning
Decentralized learning enables serverless training of deep neural networ...
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03/31/2023
Demo Alleviate: Demonstrating Artificial Intelligence Enabled Virtual Assistance for Telehealth: The Mental Health Case
After the pandemic, artificial intelligence (AI) powered support for men...
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03/27/2023
CoDeC: Communication-Efficient Decentralized Continual Learning
Training at the edge utilizes continuously evolving data generated at di...
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03/13/2023
X-Former: In-Memory Acceleration of Transformers
Transformers have achieved great success in a wide variety of natural la...
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02/03/2023
HADES: Hardware/Algorithm Co-design in DNN accelerators using Energy-efficient Approximate Alphabet Set Multipliers
Edge computing must be capable of executing computationally intensive al...
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02/02/2023
Continual Learning with Scaled Gradient Projection
In neural networks, continual learning results in gradient interference ...
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12/09/2022
A Comparative Performance Analysis of Explainable Machine Learning Models With And Without RFECV Feature Selection Technique Towards Ransomware Classification
Ransomware has emerged as one of the major global threats in recent days...
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11/19/2022
HALSIE - Hybrid Approach to Learning Segmentation by Simultaneously Exploiting Image and Event Modalities
Standard frame-based algorithms fail to retrieve accurate segmentation m...
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11/03/2022
Hardware/Software co-design with ADC-Less In-memory Computing Hardware for Spiking Neural Networks
Spiking Neural Networks (SNNs) are bio-plausible models that hold great ...
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10/16/2022
Interpretable Machine Learning for Detection and Classification of Ransomware Families Based on API Calls
Ransomware has appeared as one of the major global threats in recent day...
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10/09/2022
KSAT: Knowledge-infused Self Attention Transformer – Integrating Multiple Domain-Specific Contexts
Domain-specific language understanding requires integrating multiple pie...
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10/03/2022
Event-based Temporally Dense Optical Flow Estimation with Sequential Neural Networks
Prior works on event-based optical flow estimation have investigated sev...
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10/03/2022
DOTIE – Detecting Objects through Temporal Isolation of Events using a Spiking Architecture
Vision-based autonomous navigation systems rely on fast and accurate obj...
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09/28/2022
Neighborhood Gradient Clustering: An Efficient Decentralized Learning Method for Non-IID Data Distributions
Decentralized learning over distributed datasets can have significantly ...
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09/21/2022
Adaptive-SpikeNet: Event-based Optical Flow Estimation using Spiking Neural Networks with Learnable Neuronal Dynamics
Event-based cameras have recently shown great potential for high-speed m...
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09/19/2022
RAMP-Net: A Robust Adaptive MPC for Quadrotors via Physics-informed Neural Network
Model Predictive Control (MPC) is a state-of-the-art (SOTA) control tech...
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06/18/2022
Can Language Models Capture Graph Semantics? From Graphs to Language Model and Vice-Versa
Knowledge Graphs are a great resource to capture semantic knowledge in t...
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06/03/2022
A Co-design view of Compute in-Memory with Non-Volatile Elements for Neural Networks
Deep Learning neural networks are pervasive, but traditional computer ar...
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05/27/2022
Learning to Automate Follow-up Question Generation using Process Knowledge for Depression Triage on Reddit Posts
Conversational Agents (CAs) powered with deep language models (DLMs) hav...
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05/06/2022
Norm-Scaling for Out-of-Distribution Detection
Out-of-Distribution (OoD) inputs are examples that do not belong to the ...
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04/26/2022
Process Knowledge-infused Learning for Suicidality Assessment on Social Media
Improving the performance and natural language explanations of deep lear...
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03/25/2022
Cryogenic Neuromorphic Hardware
The revolution in artificial intelligence (AI) brings up an enormous sto...
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01/21/2022
TOFU: Towards Obfuscated Federated Updates by Encoding Weight Updates into Gradients from Proxy Data
Advances in Federated Learning and an abundance of user data have enable...
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12/20/2021
Encoding Hierarchical Information in Neural Networks helps in Subpopulation Shift
Over the past decade, deep neural networks have proven to be adept in im...
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11/17/2021
L4-Norm Weight Adjustments for Converted Spiking Neural Networks
Spiking Neural Networks (SNNs) are being explored for their potential en...
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11/17/2021
Low Precision Decentralized Distributed Training over IID and non-IID Data
Decentralized distributed learning is the key to enabling large-scale ma...
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10/18/2021
BERMo: What can BERT learn from ELMo?
We propose BERMo, an architectural modification to BERT, which makes pre...
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10/01/2021
One Timestep is All You Need: Training Spiking Neural Networks with Ultra Low Latency
Spiking Neural Networks (SNNs) are energy efficient alternatives to comm...
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09/19/2021
On the Noise Stability and Robustness of Adversarially Trained Networks on NVM Crossbars
Applications based on Deep Neural Networks (DNNs) have grown exponential...
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09/16/2021
RAPID-RL: A Reconfigurable Architecture with Preemptive-Exits for Efficient Deep-Reinforcement Learning
Present-day Deep Reinforcement Learning (RL) systems show great promise ...
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09/14/2021
Oscillatory Fourier Neural Network: A Compact and Efficient Architecture for Sequential Processing
Tremendous progress has been made in sequential processing with the rece...
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09/14/2021
Complexity-aware Adaptive Training and Inference for Edge-Cloud Distributed AI Systems
The ubiquitous use of IoT and machine learning applications is creating ...
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09/10/2021