13 citations · 25 across the 13 of their papers we have counts for
15 papers
AutoNovo: Agentic Program Search Discovers Transferable Nucleic Acid Design Algorithms
Joel Shor, Subhashini Venugopalan
In-silico optimization of nucleic acids relies on predictive oracles that imperfectly capture biological function, so sequences optimized against one model may exploit model-specif…
Idea Search: Guiding Tree Search with Ideas to Explore Diverse Scientific Methods
Xuefei Julie Wang, Hao Cui, Michael P. Brenner +1
Tree Search-based test-time scaling of LLMs is a powerful tool for automated scientific coding. However, pure Tree Search sometimes struggles with systematic exploration, becoming…
MAgSeg: Segmentation of Agricultural Landscapes in High-Resolution Satellite Imagery using Multimodal Large Language Models
Piyush Tiwary, Utkarsh Ahuja, Depanshu Sani +5
Agricultural landscape segmentation in the Global South is challenging as it is characterized by fragmented plots, high intra-class variance, and a scarcity of labeled training dat…
WAXAL: A Large-Scale Multilingual African Language Speech Corpus
Abdoulaye Diack, Perry Nelson, Kwaku Agbesi +40
The advancement of speech technology has predominantly favored high-resource languages, creating a significant digital divide for speakers of most Sub-Saharan African languages. To…
Expert Evaluation of LLM World Models: A High- Superconductivity Case Study
Haoyu Guo, Maria Tikhanovskaya, Paul Raccuglia +20
Large Language Models (LLMs) show great promise as a powerful tool for scientific literature exploration. However, their effectiveness in providing scientifically accurate and comp…
An AI system to help scientists write expert-level empirical software
Eser Aygün, Anastasiya Belyaeva, Gheorghe Comanici +39
The cycle of scientific discovery is frequently bottlenecked by the slow, manual creation of software to support computational experiments\cite{hannay2009how}. To address this, we…
FEABench: Evaluating Language Models on Multiphysics Reasoning Ability
Nayantara Mudur, Hao Cui, Subhashini Venugopalan +3
Building precise simulations of the real world and invoking numerical solvers to answer quantitative problems is an essential requirement in engineering and science. We present FEA…
Towards AI-assisted Academic Writing
Daniel J. Liebling, Malcolm Kane, Madeleine Grunde-Mclaughlin +3
We present components of an AI-assisted academic writing system including citation recommendation and introduction writing. The system recommends citations by considering the user'…
CURIE: Evaluating LLMs On Multitask Scientific Long Context Understanding and Reasoning
Hao Cui, Zahra Shamsi, Gowoon Cheon +31
Scientific problem-solving involves synthesizing information while applying expert knowledge. We introduce CURIE, a scientific long-Context Understanding,Reasoning and Information…
Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning
Chirag Nagpal, Subhashini Venugopalan, Jimmy Tobin +3
We introduce a large language model (LLM) capable of processing speech inputs and show that tuning it further with reinforcement learning on human preference (RLHF) enables it to a…
Towards a Single ASR Model That Generalizes to Disordered Speech
Jimmy Tobin, Katrin Tomanek, Subhashini Venugopalan
This study investigates the impact of integrating a dataset of disordered speech recordings (1,000 hours) into the fine-tuning of a near state-of-the-art ASR baseline system.…
Quantum Many-Body Physics Calculations with Large Language Models
Haining Pan, Nayantara Mudur, Will Taranto +5
Large language models (LLMs) have demonstrated an unprecedented ability to perform complex tasks in multiple domains, including mathematical and scientific reasoning. We demonstrat…
Using Large Language Models to Accelerate Communication for Users with Severe Motor Impairments
Shanqing Cai, Subhashini Venugopalan, Katie Seaver +13
Finding ways to accelerate text input for individuals with profound motor impairments has been a long-standing area of research. Closing the speed gap for augmentative and alternat…
Accurate Prediction of Experimental Band Gaps from Large Language Model-Based Data Extraction
Samuel J. Yang, Shutong Li, Subhashini Venugopalan +5
Machine learning is transforming materials discovery by providing rapid predictions of material properties, which enables large-scale screening for target materials. However, such…
Speech Intelligibility Classifiers from 550k Disordered Speech Samples
Subhashini Venugopalan, Jimmy Tobin, Samuel J. Yang +7
We developed dysarthric speech intelligibility classifiers on 551,176 disordered speech samples contributed by a diverse set of 468 speakers, with a range of self-reported speaking…