Genetics

Social Genome: Grounded Social Reasoning Abilities of Multimodal Models

Social reasoning abilities are crucial for AI systems to effectively interpret and respond to multimodal human communication and interaction within social contexts. We introduce Social Genome, the first benchmark for fine-grained, grounded social reasoning abilities of multimodal models. Social Genome contains 272 videos of interactions and 1,486 human-annotated reasoning traces related to infer...

Hallucination Detection in Large Language Models with Metamorphic Relations

Large Language Models (LLMs) are prone to hallucinations, e.g., factually incorrect information, in their responses. These hallucinations present challenges for LLM-based applications that demand high factual accuracy. Existing hallucination detection methods primarily depend on external resources, which can suffer from issues such as low availability, incomplete coverage, privacy concerns, high...

Towards Accurate Binary Spiking Neural Networks: Learning with Adaptive Gradient Modulation Mechanism

Binary Spiking Neural Networks (BSNNs) inherit the eventdriven paradigm of SNNs, while also adopting the reduced storage burden of binarization tech...

[Exploration of the Predictive Value of Peripheral Blood-related Indicators for EGFR 
Mutations and Prognosis in Non-small Cell Lung Cancer Using Machine Learning].

BACKGROUND: Epidermal growth factor receptor (EGFR) sensitive mutation is one of the effective targets of targeted therapy for non-small cell lung can...

Optimizing Gene-Based Testing for Antibiotic Resistance Prediction

Antibiotic Resistance (AR) is a critical global health challenge that necessitates the development of cost-effective, efficient, and accurate diagno...

Learning to Discover Regulatory Elements for Gene Expression Prediction

We consider the problem of predicting gene expressions from DNA sequences. A key challenge of this task is to find the regulatory elements that cont...

BOLIMES: Boruta and LIME optiMized fEature Selection for Gene Expression Classification

Gene expression classification is a pivotal yet challenging task in bioinformatics, primarily due to the high dimensionality of genomic data and the...

A linear-time algorithm computing the resident fitness in interacting trajectories

The notion of a system of interacting trajectories was recently introduced by Hermann, Gonz\'alez Casanova, Soares dos Santos, T\'obi\'as and Wakolb...

Be Cautious When Merging Unfamiliar LLMs: A Phishing Model Capable of Stealing Privacy

Model merging is a widespread technology in large language models (LLMs) that integrates multiple task-specific LLMs into a unified one, enabling th...

Do we Really Need Visual Instructions? Towards Visual Instruction-Free Fine-tuning for Large Vision-Language Models

Visual instruction tuning has become the predominant technology in eliciting the multimodal task-solving capabilities of large vision-language model...

HybriDNA: A Hybrid Transformer-Mamba2 Long-Range DNA Language Model

Advances in natural language processing and large language models have sparked growing interest in modeling DNA, often referred to as the "language ...

ControllableGPT: A Ground-Up Designed Controllable GPT for Molecule Optimization

Large Language Models (LLMs) employ three popular training approaches: Masked Language Models (MLM), Causal Language Models (CLM), and Sequence-to-S...

Complex Network Modelling with Power-law Activating Patterns and Its Evolutionary Dynamics

Complex network theory provides a unifying framework for the study of structured dynamic systems. The current literature emphasizes a widely reporte...

Genetic Data Governance in Crisis: Policy Recommendations for Safeguarding Privacy and Preventing Discrimination

Genetic data collection has become ubiquitous today. The ability to meaningfully interpret genetic data has motivated its widespread use, providing ...

Leveraging Machine Learning and Deep Learning Techniques for Improved Pathological Staging of Prostate Cancer

Prostate cancer (Pca) continues to be a leading cause of cancer-related mortality in men, and the limitations in precision of traditional diagnostic...

scMamba: A Pre-Trained Model for Single-Nucleus RNA Sequencing Analysis in Neurodegenerative Disorders

Single-nucleus RNA sequencing (snRNA-seq) has significantly advanced our understanding of the disease etiology of neurodegenerative disorders. Howev...

Orthology and Near-Cographs in the Context of Phylogenetic Networks

Orthologous genes, which arise through speciation, play a key role in comparative genomics and functional inference. In particular, graph-based meth...

Advancing Precision Oncology Through Modeling of Longitudinal and Multimodal Data

Cancer evolves continuously over time through a complex interplay of genetic, epigenetic, microenvironmental, and phenotypic changes. This dynamic b...

CausalGeD: Blending Causality and Diffusion for Spatial Gene Expression Generation

The integration of single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) data is crucial for understanding gene expression in spat...

Whole-Genome Phenotype Prediction with Machine Learning: Open Problems in Bacterial Genomics

How can we identify causal genetic mechanisms that govern bacterial traits? Initial efforts entrusting machine learning models to handle the task of...