19 citations · 40 across the 21 of their papers we have counts for
6 papers · 1 filter
Local K-Similarity Constraint for Federated Learning with Label Noise
Sanskar Amgain, Prashant Shrestha, Bidur Khanal +5
Federated learning on clients with noisy labels is a challenging problem, as such clients can infiltrate the global model, impacting the overall generalizability of the system. Exi…
Noise, Adaptation, and Strategy: Assessing LLM Fidelity in Decision-Making
Yuanjun Feng, Vivek Choudhary, Yash Raj Shrestha
Large language models (LLMs) are increasingly used in social science simulations. While their performance on reasoning and optimization tasks has been extensively evaluated, less a…
Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models
Bidur Khanal, Sandesh Pokhrel, Sanjay Bhandari +7
Vision-Language Models (VLMs) are becoming increasingly popular in the medical domain, bridging the gap between medical images and clinical language. Existing VLMs demonstrate an i…
Human aversion? Do AI Agents Judge Identity More Harshly Than Performance
Yuanjun Feng, Vivek Chodhary, Yash Raj Shrestha
This study examines the understudied role of algorithmic evaluation of human judgment in hybrid decision-making systems, a critical gap in management research. While extant literat…
Surgical Vision World Model
Saurabh Koju, Saurav Bastola, Prashant Shrestha +4
Realistic and interactive surgical simulation has the potential to facilitate crucial applications, such as medical professional training and autonomous surgical agent training. In…
Contextualizing Recommendation Explanations with LLMs: A User Study
Yuanjun Feng, Stefan Feuerriegel, Yash Raj Shrestha
Large language models (LLMs) are increasingly prevalent in recommender systems, where LLMs can be used to generate personalized recommendations. Here, we examine how different LLM-…