1 citations · 1 across the 2 of their papers we have counts for
4 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-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…
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…
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…