Search Results for author:
Found 11 papers, 7 papers with code
RESIN-11: Schema-guided Event Prediction for 11 Newsworthy Scenarios
We introduce RESIN-11, a new schema-guided event extraction&prediction framework that can be applied to a large variety of newsworthy scenarios.
Text2Mol: Cross-Modal Molecule Retrieval with Natural Language Queries
Moreover, this can be viewed as an especially challenging cross-lingual retrieval problem by considering the molecules as a language with a very unique grammar.
Ranked #2 on
Cross-Modal Retrieval
on ChEBI-20
$\textit{L+M-24}$: Building a Dataset for Language + Molecules @ ACL 2024
Language-molecule models have emerged as an exciting direction for molecular discovery and understanding.
ChemReasoner: Heuristic Search over a Large Language Model's Knowledge Space using Quantum-Chemical Feedback
The discovery of new catalysts is essential for the design of new and more efficient chemical processes in order to transition to a sustainable future.
Defining a New NLP Playground
The recent explosion of performance of large language models (LLMs) has changed the field of Natural Language Processing (NLP) more abruptly and seismically than any other shift in the field's 80-year history.
Monte Carlo Thought Search: Large Language Model Querying for Complex Scientific Reasoning in Catalyst Design
Discovering novel catalysts requires complex reasoning involving multiple chemical properties and resultant trade-offs, leading to a combinatorial growth in the search space.
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems
Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural sciences.
SynerGPT: In-Context Learning for Personalized Drug Synergy Prediction and Drug Design
We are given a small "personalized dataset" of 10-20 drug synergy relationships in the context of specific cancer cell targets.
Translation between Molecules and Natural Language
We present $\textbf{MolT5}$ $-$ a self-supervised learning framework for pretraining models on a vast amount of unlabeled natural language text and molecule strings.
Ranked #4 on
Text-based de novo Molecule Generation
on ChEBI-20
Semi-supervised New Event Type Induction and Description via Contrastive Loss-Enforced Batch Attention
In contrast, we present a novel approach to semi-supervised new event type induction using a masked contrastive loss, which learns similarities between event mentions by enforcing an attention mechanism over the data minibatch.
Phase-Only Beam Broadening of Contiguous Uniform Subarrayed Arrays Utilizing Three Metaheuristic Global Optimization Techniques
While many methods have been published that address beam broadening of traditional (nonsubarrayed) arrays, there is a knowledge gap in the published literature with respect to efficient and effective beam broadening of contiguous uniform subarrayed arrays.
