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Found 7 papers, 4 papers with code
DrugAgent: Automating AI-aided Drug Discovery Programming through LLM Multi-Agent Collaboration
Recent advancements in Large Language Models (LLMs) have opened new avenues for accelerating drug discovery processes.
FlexMol: A Flexible Toolkit for Benchmarking Molecular Relational Learning
Molecular relational learning (MRL) is crucial for understanding the interaction behaviors between molecular pairs, a critical aspect of drug discovery and development.
Multilingual Contrastive Decoding via Language-Agnostic Layers Skipping
Decoding by contrasting layers (DoLa), is designed to improve the generation quality of large language models (LLMs) by contrasting the prediction probabilities between an early exit output (amateur logits) and the final output (expert logits).
Large Language Models Are Cross-Lingual Knowledge-Free Reasoners
However, the relationship between capabilities in different languages is less explored.
NovoBench: Benchmarking Deep Learning-based De Novo Peptide Sequencing Methods in Proteomics
In this work, we present the first unified benchmark NovoBench for \emph{de novo} peptide sequencing, which comprises diverse mass spectrum data, integrated models, and comprehensive evaluation metrics.
AdaNovo: Adaptive \emph{De Novo} Peptide Sequencing with Conditional Mutual Information
Moreover, AdaNovo excels in identifying amino acids with PTMs and exhibits robustness against data noise.
kNN-BOX: A Unified Framework for Nearest Neighbor Generation
Augmenting the base neural model with a token-level symbolic datastore is a novel generation paradigm and has achieved promising results in machine translation (MT).
