10 citations · 10 across the 6 of their papers we have counts for
6 papers
REPREC: Representation Driven Parameter-Efficient Recommendation System
Harshini Kavuru, Dwipam Katariya, Giri Iyengar +3
Large language models (LLMs) have been applied to sequential recommendation by incorporating collaborative signals through input conditioning or model adaptation. However, existing…
Trust The Typical
Debargha Ganguly, Sreehari Sankar, Biyao Zhang +8
Current approaches to LLM safety fundamentally rely on a brittle cat-and-mouse game of identifying and blocking known threats via guardrails. We argue for a fresh approach: robust…
Eye-Tracking, Mouse Tracking, Stimulus Tracking,and Decision-Making Datasets in Digital Pathology
Veronica Thai, Rui Li, Meng Ling +7
Interpretation of giga-pixel whole-slide images (WSIs) is an important but difficult task for pathologists. Their diagnostic accuracy is estimated to average around 70%. Adding a s…
Improving Compound Activity Classification via Deep Transfer and Representation Learning
Vishal Dey, Raghu Machiraju, Xia Ning
Recent advances in molecular machine learning, especially deep neural networks such as Graph Neural Networks (GNNs) for predicting structure activity relationships (SAR) have shown…
An Annotated Corpus for Machine Reading of Instructions in Wet Lab Protocols
Chaitanya Kulkarni, Wei Xu, Alan Ritter +1
We describe an effort to annotate a corpus of natural language instructions consisting of 622 wet lab protocols to facilitate automatic or semi-automatic conversion of protocols in…
iGPSe: A Visual Analytic System for Integrative Genomic Based Cancer Patient Stratification
Hao Ding, Chao Wang, Kun Huang +1
Background: Cancers are highly heterogeneous with different subtypes. These subtypes often possess different genetic variants, present different pathological phenotypes, and most i…