11 citations · 16 across the 7 of their papers we have counts for
7 papers
DeepVRegulome: DNABERT-based deep-learning framework for predicting the functional impact of short genomic variants on the human regulome
Pratik Dutta, Matthew Obusan, Rekha Sathian +8
Whole-genome sequencing (WGS) has revealed numerous non-coding short variants whose functional impacts remain poorly understood. Despite recent advances in deep-learning genomic ap…
Genome-Factory: A Library for Tuning, Deploying, and Interpreting Genomic Foundation Models
Weimin Wu, Xuefeng Song, Yibo Wen +5
We introduce Genome-Factory, the first integrated Python library for tuning, deploying, and interpreting genomic foundation models. Our core contribution is to simplify and unify t…
Fast and Low-Cost Genomic Foundation Models via Outlier Removal
Haozheng Luo, Chenghao Qiu, Maojiang Su +5
To address the challenge of scarce computational resources in genomic modeling, we introduce GERM, a genomic foundation model with strong compression performance and fast adaptabil…
USE: Dynamic User Modeling with Stateful Sequence Models
Zhihan Zhou, Qixiang Fang, Leonardo Neves +5
User embeddings play a crucial role in user engagement forecasting and personalized services. Recent advances in sequence modeling have sparked interest in learning user embeddings…
DNABERT-S: Pioneering Species Differentiation with Species-Aware DNA Embeddings
Zhihan Zhou, Weimin Wu, Harrison Ho +5
We introduce DNABERT-S, a tailored genome model that develops species-aware embeddings to naturally cluster and segregate DNA sequences of different species in the embedding space.…
General-Purpose User Modeling with Behavioral Logs: A Snapchat Case Study
Qixiang Fang, Zhihan Zhou, Francesco Barbieri +6
Learning general-purpose user representations based on user behavioral logs is an increasingly popular user modeling approach. It benefits from easily available, privacy-friendly y…
MorphPiece : A Linguistic Tokenizer for Large Language Models
Haris Jabbar
Tokenization is a critical part of modern NLP pipelines. However, contemporary tokenizers for Large Language Models are based on statistical analysis of text corpora, without much…