37 citations · 41 across the 6 of their papers we have counts for
6 papers
RLMOpt: Adaptive Prompt Optimization via Recursive Language Models
Subhash Bangalore Satheesha, Nirvik Pande, Deepthi Duddempudi +1
Prompt optimizers automate the search for prompts that improve language-model performance, but existing methods rely on a predefined optimization procedure: the algorithm determine…
BMFM-DNA: A SNP-aware DNA foundation model to capture variant effects
Hongyang Li, Sanjoy Dey, Bum Chul Kwon +7
Large language models (LLMs) trained on text demonstrated remarkable results on natural language processing (NLP) tasks. These models have been adapted to decipher the language of…
BMFM-RNA: whole-cell expression decoding improves transcriptomic foundation models
Michael M. Danziger, Bharath Dandala, Viatcheslav Gurev +12
Transcriptomic foundation models pretrained with masked language modeling can achieve low pretraining loss yet produce poor cell representations for downstream tasks. We introduce…
INDUS: Effective and Efficient Language Models for Scientific Applications
Bishwaranjan Bhattacharjee, Aashka Trivedi, Masayasu Muraoka +33
Large language models (LLMs) trained on general domain corpora showed remarkable results on natural language processing (NLP) tasks. However, previous research demonstrated LLMs tr…
WNTRAC: AI Assisted Tracking of Non-pharmaceutical Interventions Implemented Worldwide for COVID-19
Parthasarathy Suryanarayanan, Ching-Huei Tsou, Ananya Poddar +23
The Coronavirus disease 2019 (COVID-19) global pandemic has transformed almost every facet of human society throughout the world. Against an emerging, highly transmissible disease…
Training Models to Extract Treatment Plans from Clinical Notes Using Contents of Sections with Headings
Ananya Poddar, Bharath Dandala, Murthy Devarakonda
Objective: Using natural language processing (NLP) to find sentences that state treatment plans in a clinical note, would automate plan extraction and would further enable their us…