mlsanityData to 7 Oct 2026

DangerMaps: Personalized Safety Advice for Travel in Urban Environments using a Retrieval-Augmented Language Model

arXiv 2503.14103 ↗First posted 18 Mar 2025cs.HCcited by 1

On the map: Retrieval-augmented generation → RAG for recommendation

Abstract (arXiv)

Planning a trip into a potentially unsafe area is a difficult task. We conducted a formative study on travelers' information needs, finding that most of them turn to search engines for trip planning. Search engines, however, fail to provide easily interpretable results adapted to the context and personal information needs of a traveler. Large language models (LLMs) create new possibilities for providing personalized travel safety advice. To explore this idea, we developed DangerMaps, a mapping system that assists its users in researching the safety of an urban travel destination, whether it is pre-travel or on-location. DangerMaps plots safety ratings onto a map and provides explanations on demand. This late breaking work specifically emphasizes the challenges of designing real-world applications with large language models. We provide a detailed description of our approach to prompt design and highlight future areas of research.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in RAG for recommendation, one of 15 directions in Retrieval-augmented generation. Builds on 23 of its 57 references that are in the map. First posted on arXiv 18 Mar 2025.

Builds on

23 of 57 references.

References · 23

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  3. 2017A Unified Approach to Interpreting Model Predictionscited by 6,488
  4. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,601
  5. 2022Large Language Models are Zero-Shot Reasonerscited by 4,323
  6. 2023Self-Refine: Iterative Refinement with Self-Feedbackcited by 3,317
  7. 2023Sparks of Artificial General Intelligence: Early experiments with GPT-4cited by 2,579
  8. 2021Calibrate Before Use: Improving Few-Shot Performance of Language Modelscited by 1,371
  9. 2021Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivitycited by 1,122
  10. 2022Large Language Models Are Human-Level Prompt Engineerscited by 1,020
  11. 2022Ignore Previous Prompt: Attack Techniques For Language Modelscited by 760
  12. 2023In-Context Retrieval-Augmented Language Modelscited by 694
11 more
  1. 2020It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learnerscited by 668
  2. 2021Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigmcited by 599
  3. 2022Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Taskcited by 417
  4. 2023How Language Model Hallucinations Can Snowballcited by 310
  5. 2022Can language models learn from explanations in context?cited by 248
  6. 2023In-Context Impersonation Reveals Large Language Models' Strengths and Biasescited by 154
  7. 2022Conversing with Copilot: Exploring Prompt Engineering for Solving CS1 Problems Using Natural Languagecited by 81
  8. 2023Prompting AI Art: An Investigation into the Creative Skill of Prompt Engineeringcited by 40
  9. 2024Don't Do RAG: When Cache-Augmented Generation is All You Need for Knowledge Taskscited by 38
  10. 2023Synergi: A Mixed-Initiative System for Scholarly Synthesis and Sensemakingcited by 25
  11. 2023A Case Study in Engineering a Conversational Programming Assistant's Personacited by 6

Built on by

Cited by year

Citing papers per year: 2025: 1.

1 paper.

  1. 2025A Survey of Context Engineering for Large Language Modelscited by 120

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  2. 2026Urban Risk-Aware Navigation via VQA-Based Event Maps for People with Low Vision
  3. 2024Robust Planning with LLM-Modulo Framework: Case Study in Travel Planning
  4. 2026When Helpers Become Hazards: A Benchmark for Analyzing Multimodal LLM-Powered Safety in Daily Life
  5. 2025Personalized Safety in LLMs: A Benchmark and A Planning-Based Agent Approach
  6. 2025Large Language Models and Their Applications in Roadway Safety and Mobility Enhancement: A Comprehensive Review
  7. 2025Evaluating Retrieval Augmented Generative Models for Document Queries in Transportation Safety
  8. 2025LLMAP: LLM-Assisted Multi-Objective Route Planning with User Preferences