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Found 21 papers, 7 papers with code
CLPT: A Universal Annotation Scheme and Toolkit for Clinical Language Processing
With the abundance of natural language processing (NLP) frameworks and toolkits being used in the clinical arena, a new challenge has arisen - how do technologists collaborate across several projects in an easy way?
Adaptive Urban Planning: A Hybrid Framework for Balanced City Development
Urban planning faces a critical challenge in balancing city-wide infrastructure needs with localized demographic preferences, particularly in rapidly developing regions.
LoRA-Mini : Adaptation Matrices Decomposition and Selective Training
The rapid advancements in large language models (LLMs) have revolutionized natural language processing, creating an increased need for efficient, task-specific fine-tuning methods.
Are VLMs Really Blind
Vision Language Models excel in handling a wide range of complex tasks, including Optical Character Recognition (OCR), Visual Question Answering (VQA), and advanced geometric reasoning.
Beyond Captioning: Task-Specific Prompting for Improved VLM Performance in Mathematical Reasoning
We incorporated this pipeline for tasks involving geometry, algebra, and counting.
Robustness of LLMs to Perturbations in Text
This is a departure from pre-trained models like BERT or RoBERTa whose performance has been shown to be sensitive to deteriorating noisy text.
Can GPT Redefine Medical Understanding? Evaluating GPT on Biomedical Machine Reading Comprehension
Experiments show that modern-day LLMs like GPT even in a zero-shot setting can outperform supervised models, leading to new state-of-the-art (SoTA) results on two of the benchmarks.
LLM-Based Section Identifiers Excel on Open Source but Stumble in Real World Applications
Electronic health records (EHR) even though a boon for healthcare practitioners, are growing convoluted and longer every day.
Ranked #1 on
Classification
on MedSecId
Prediction of Cryptocurrency Prices through a Path Dependent Monte Carlo Simulation
In this paper, our focus lies on the Merton's jump diffusion model, employing jump processes characterized by the compound Poisson process.
Can GPT Improve the State of Prior Authorization via Guideline Based Automated Question Answering?
Health insurance companies have a defined process called prior authorization (PA) which is a health plan cost-control process that requires doctors and other healthcare professionals to get clearance in advance from a health plan before performing a particular procedure on a patient in order to be eligible for payment coverage.
Semi-supervised Active Learning for Video Action Detection
First, we demonstrate its effectiveness on video action detection where the proposed approach outperforms prior works in semi-supervised and weakly-supervised learning along with several baseline approaches in both UCF101-24 and JHMDB-21.
Latent Graph Attention for Enhanced Spatial Context
In this paper, we present Latent Graph Attention (LGA) a computationally inexpensive (linear to the number of nodes) and stable, modular framework for incorporating the global context in the existing architectures, especially empowering small-scale architectures to give performance closer to large size architectures, thus making the light-weight architectures more useful for edge devices with lower compute power and lower energy needs.
Ultrasound based Gas Detection: Analyzing Acoustic Impedance for High-Performance and Low-Cost Solutions
In this paper, a novel non-contact gas detection technique based on a 40 kHz ultrasonic signal is described.
A Prototype System for High Frame Rate Ultrasound Imaging based Prosthetic Arm Control
The creation of unique control methods for a hand prosthesis is still a problem that has to be addressed.
Addressing Distribution Shift at Test Time in Pre-trained Language Models
However, PLMs have been found to degrade in performance under distribution shift, a phenomenon that occurs when data at test-time does not come from the same distribution as the source training set.
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions.
BigBIO: A Framework for Data-Centric Biomedical Natural Language Processing
Training and evaluating language models increasingly requires the construction of meta-datasets --diverse collections of curated data with clear provenance.
Semantic Parsing Natural Language into Relational Algebra
Natural interface to database (NLIDB) has been researched a lot during the past decades.
Single image dehazing for a variety of haze scenarios using back projected pyramid network
Learning to dehaze single hazy images, especially using a small training dataset is quite challenging.
Ranked #2 on
Image Dehazing
on Dense-Haze
Deep Predictive Motion Tracking in Magnetic Resonance Imaging: Application to Fetal Imaging
Nevertheless, visual monitoring of fetal motion based on displayed slices, and navigation at the level of stacks-of-slices is inefficient.
Sentiment Transfer using Seq2Seq Adversarial Autoencoders
Language style transfer is a way to preserve the meaning of a text and change the way it is expressed.
