Skip to main content
Angestrom home
SearchPapersModelsLive AIIntelligence
Search⌕⌘K
EnterprisePricingSign in

Stay Ahead in the AI Revolution

Weekly digest — EPI pulse, top intelligence, fresh lineage. Free, no account.

Follow Angestrom
Global source network
Synced every 5 minutes

Continuous sync from primary AI sources — indexed, enriched, and queryable in real time.

arXivHugging FaceGitHubOpenAIAnthropicDeepMindReutersBBC TechHacker NewsReddit MLVerified feedsFunding
ANGESTROM

The Intelligence Layer of Humanity. Everything AI. All in One Place.

Angestrom connects every piece of the AI ecosystem — data, models, research, companies, tools, and people.

info@angestrom.comwww.angestrom.comLucknow, Uttar Pradesh, India

Product

  • AI Search
  • AI Models
  • Research Papers
  • Companies
  • News & Events
  • GitHub Explorer
  • APIs & Tools
  • Datasets
  • Benchmarks
  • Model lifecycle
  • Funding graph
  • Contributors
  • AI Agents

Resources

  • Weekly digest
  • Documentation
  • Tutorials
  • Guides
  • News
  • Help / Start
  • Community

Company

  • About
  • Contact
  • Privacy Policy
  • Terms of Service
  • Acceptable Use

Enterprise

  • Pricing
  • Workspace
  • Contact Sales

Developer

  • Developer Hub
  • API docs
  • GitHub

Learn

  • Learning Academy
  • Roadmaps
  • Glossary
  • AI for Beginners

Popular Topics

Loading topics…
View All Topics →
© 2026 Angestrom Intelligence Private Limited. All rights reserved.
English
Theme
Angestrom home
SearchPapersModelsLive AIIntelligence
Search⌕⌘K
EnterprisePricingSign in
  1. Home
  2. /Repositories
  3. /KennispuntTwente/tidyprompt
Read original ↗
repoGitHubTrust 82 · PrimaryPublished 4d agoLive · 4d ago

KennispuntTwente/tidyprompt

R package to easily construct prompts and associated logic for interacting with large language models (‘LLMs’)

Lineage graph

Paper → model → repo connections mined from source citations (Tier-1 exact match).

Implements

paperJoint Learning of Experiential Rules and Policies for Large Language Model AgentspaperWhen the Database Fails: Prompting LLM Dialogue Agents for Safe Recovery in Task-Oriented DialoguepaperTheory of Mind and Persuasion Beyond Conversation: Assessing the Capacity of LLMs to Induce Belief States via Planning and Action

Covers

newsIEEE Rolls Out Large Language Models Virtual Training CoursenewsClinical drug report generation using multi-phase prompt large language models - Nature

Related across the graph

newsClinical drug report generation using multi-phase prompt large language models - NaturepaperJoint Learning of Experiential Rules and Policies for Large Language Model AgentsnewsIEEE Rolls Out Large Language Models Virtual Training CoursepaperTheory of Mind and Persuasion Beyond Conversation: Assessing the Capacity of LLMs to Induce Belief States via Planning and ActionpaperWhen the Database Fails: Prompting LLM Dialogue Agents for Safe Recovery in Task-Oriented Dialogue
Knowledge path·NClinical drug report generation using multi-phase prompt large language models - Nature→PJoint Learning of Experiential Rules and Policies for Large Language Model Agents→NIEEE Rolls Out Large Language Models Virtual Training Course→RKennispuntTwente/tidyprompt

Topics

llmr-package

Explore

Search similar →Knowledge graph →All repos →Full intelligence feed →
Graph trust82Primary
Graph score31