Search Results for author:
Found 9 papers, 3 papers with code
FLARE: FP-Less PTQ and Low-ENOB ADC Based AMS-PiM for Error-Resilient, Fast, and Efficient Transformer Acceleration
Analog-Mixed-Signal Process-in-Memory (AMS-PiM) architectures address these challenges by enabling efficient on-chip processing.
MARS: Matching Attribute-aware Representations for Text-based Sequential Recommendation
MARS extracts detailed user and item representations through attribute-aware text encoding, capturing diverse user intents with multiple attribute-aware representations.
ConCSE: Unified Contrastive Learning and Augmentation for Code-Switched Embeddings
This paper examines the Code-Switching (CS) phenomenon where two languages intertwine within a single utterance.
Uncertainty-aware Semantic Mapping in Off-road Environments with Dempster-Shafer Theory of Evidence
Semantic mapping with Bayesian Kernel Inference (BKI) has shown promise in providing a richer understanding of environments by effectively leveraging local spatial information.
Evidential Semantic Mapping in Off-road Environments with Uncertainty-aware Bayesian Kernel Inference
Robotic mapping with Bayesian Kernel Inference (BKI) has shown promise in creating semantic maps by effectively leveraging local spatial information.
Assessing the Utility of Large Language Models for Phenotype-Driven Gene Prioritization in Rare Genetic Disorder Diagnosis
A similar increasing trend was observed for the task completion rate, with complicated prompts more likely to increase task completeness in models smaller than GPT-4.
AMULET: Adaptive Matrix-Multiplication-Like Tasks
Many useful tasks in data science and machine learning applications can be written as simple variations of matrix multiplication.
Differentiated Backprojection Domain Deep Learning for Conebeam Artifact Removal
Conebeam CT using a circular trajectory is quite often used for various applications due to its relative simple geometry.
CollaGAN : Collaborative GAN for Missing Image Data Imputation
In many applications requiring multiple inputs to obtain a desired output, if any of the input data is missing, it often introduces large amounts of bias.
