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2,897 papers
GATK-SV A structural variation discovery pipeline for Illumina short-read whole-genome sequencing (WGS) data. Table of Contents Requirements Citation Acknowledgements Quickstart Pipeline Overview Cohort mode Single-sample mode gCNV model Generating a reference panel Module Descriptions GatherSampleEvidence - Raw caller...
GATK-SV A structural variation discovery pipeline for Illumina short-read whole-genome sequencing (WGS) data. Table of Contents Requirements Citation Acknowledgements Quickstart Pipeline Overview Cohort mode Single-sample mode gCNV model Generating a reference panel Module Descriptions GatherSampleEvidence - Raw caller...
Retrieval-Augmented Generation (RAG) has emerged as a principled solution to the knowledge limitations of large language models (LLMs). We design and implement a complete RAG pipeline built on LangChain, ChromaDB with HNSW indexing, BAAI/bge-small-en-v1.5 embeddings, and LLaMA 3.3 70B deployed on Groq LPU infrastructur...
Code accompanying the manuscript "Standard Group Relative Reinforcement Learning Is Unstable on Small Masked-Diffusion Language Models: A Controlled Study and Five Rejected Explanations," submitted to Scientific Reports. Includes the reinforcement learning driver, the supervised fine-tuning and evaluation scripts writt...
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The emergence of Large Language Models (LLMs) presents a dual challenge in the fight against disinformation. These powerful tools, capable of generating human-like text at scale, can be weaponised to produce sophisticated disinformation, yet they also hold promise for enhancing mitigation strategies. This paper investi...
Replication package for the paper "When Retrieval Helps and When It Hurts: A Pre-Registered Cross-Lingual RAG Benchmark for Small Language Models in Greek and Georgian" (submitted to Baltic Journal of Modern Computing, 2026). Contains: all pipeline scripts (01–11), the final question dataset (230 K-12 science questions...
ABSTRACT Modeling of longitudinal cohort data typically involves complex temporal dependencies between multiple variables. There, the transformer architecture, which has been highly successful in language and vision applications, allows us to account for the fact that the most recently observed time points in an indivi...
Current LLMs can match or exceed dermatologists in completeness of guideline-based systemic psoriasis recommendations, particularly in low-risk contexts, however, they remain more prone to critical safety errors in complex, high-stakes scenarios.
Findings are best viewed as preliminary evidence of high concordance under controlled conditions and should use transparent model reporting, repeated runs, consensus reference standards, and clinically representative multimodal cases before expert-level performance is inferred.
Intent-based networking decouples desired outcomes from device-level configuration, but most systems still map intents to parameters of an algorithm selected in advance. Large language models (LLMs) create an opportunity to automate algorithm design, yet unrestricted generated code is unsuitable for transport-network c...
This work applies MRT to power outage report generation for the Outage Data Initiative Nationwide (ODIN), transforming heterogeneous reports into standardized XML compliant with CIM IEC 61968-3.
Direct Relational Set-Risk Pruning is introduced, which formulates agent-history compression as risk-constrained selection over deletion sets and shows that decision-conditioned relations, retained-context information, pair interactions, and abstention each contribute to reliable pruning.
Earth AI
A Blog post by Ai2 on Hugging Face
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