8 citations · 21 across the 6 of their papers we have counts for
6 papers
Emergence of Minimal Circuits for Indirect Object Identification in Attention-Only Transformers
Rabin Adhikari
Mechanistic interpretability aims to reverse-engineer large language models (LLMs) into human-understandable computational circuits. However, the complexity of pretrained models of…
TuneVLSeg: Prompt Tuning Benchmark for Vision-Language Segmentation Models
Rabin Adhikari, Safal Thapaliya, Manish Dhakal +1
Vision-Language Models (VLMs) have shown impressive performance in vision tasks, but adapting them to new domains often requires expensive fine-tuning. Prompt tuning techniques, in…
VLSM-Adapter: Finetuning Vision-Language Segmentation Efficiently with Lightweight Blocks
Manish Dhakal, Rabin Adhikari, Safal Thapaliya +1
Foundation Vision-Language Models (VLMs) trained using large-scale open-domain images and text pairs have recently been adapted to develop Vision-Language Segmentation Models (VLSM…
Synthetic Boost: Leveraging Synthetic Data for Enhanced Vision-Language Segmentation in Echocardiography
Rabin Adhikari, Manish Dhakal, Safal Thapaliya +3
Accurate segmentation is essential for echocardiography-based assessment of cardiovascular diseases (CVDs). However, the variability among sonographers and the inherent challenges…
Exploring Transfer Learning in Medical Image Segmentation using Vision-Language Models
Kanchan Poudel, Manish Dhakal, Prasiddha Bhandari +3
Medical image segmentation allows quantifying target structure size and shape, aiding in disease diagnosis, prognosis, surgery planning, and comprehension.Building upon recent adva…
COVID-19-related Nepali Tweets Classification in a Low Resource Setting
Rabin Adhikari, Safal Thapaliya, Nirajan Basnet +3
Billions of people across the globe have been using social media platforms in their local languages to voice their opinions about the various topics related to the COVID-19 pandemi…