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20222026
most citedExploring Transfer Learning in Medical Image Segmentation using Vision-Language Models

8 citations · 27 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG2026

Where LLM Annotators Fail: Label-Free Learning on Graphs with LLMs

Safal Thapaliya, Jiatan Huang, Chuxu Zhang

Node classification on graphs often requires labeled nodes, yet obtaining labels at graph scale is expensive. When node attributes contain semantic content, such as paper abstracts…

cs.CL2025

Semantic Refinement with LLMs for Graph Representations

Safal Thapaliya, Zehong Wang, Jiazheng Li +3

Graph-structured data exhibit substantial heterogeneity in where their predictive signals originate: in some domains, node-level semantics dominate, while in others, structural pat…

cs.CV2024

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…

cs.CV2024★ 1 cited

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…

cs.CV2023★ 8 cited

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…

cs.CV2023★ 8 cited

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…

eess.IV2023★ 6 cited

Deep-learning Assisted Detection and Quantification of (oo)cysts of Giardia and Cryptosporidium on Smartphone Microscopy Images

Suprim Nakarmi, Sanam Pudasaini, Safal Thapaliya +5

The consumption of microbial-contaminated food and water is responsible for the deaths of millions of people annually. Smartphone-based microscopy systems are portable, low-cost, a…

cs.CL2022★ 4 cited

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…