Skip to content
#explainable ai Open access

Gaps Below n in Multiset Resolving Spectra

Oct 2026 · Figshare
Graph Labeling and Dimension Problems

Abstract

A set S of vertices of a connected graph is multiset resolving if every vertex has a distinct multiset of distances to S. We study graphs whose identification spectrum (the set of sizes of multiset resolving sets) contains the order n but skips the sizes just below it, and define the top gap g(G) as n minus the largest size of a proper multiset resolving set. This relates to Problems 2 and 6 of the 2026 survey by Farhan, Klavžar, Kuziak and Yero (arXiv:2607.10311). Main results:- Exactly 17 connected graphs on 10 vertices have top gap 3, and no graph on fewer vertices does; the smallest order with top gap 4 is 11.- Graphs with top gap 3 exist at every order from 10 to 48.- DDI graphs with top gap exactly 5 exist (orders 49 and 51–55), and graphs of order 52 with top gap exactly k for every k from 6 to 10.- The gap-10 graph was verified by three independently written programs, including a clean-room C++ checker that tested all 4,588,649,793 deletion sets of sizes 1 to 9.- Collision, Switch, Blocking, Persistence and Flow Lemmas explain the mechanism; a counting barrier limits switch-based designs.- As by-products, the conjecture dim_m(G) ≤ n − 1 holds for all connected graphs on at most 10 vertices, and dim_m(T) ≤ n − d + 1 holds for all trees on at most 15 vertices. We conjecture that the top gap is unbounded. The supplementary ZIP contains every graph in graph6 format, a plain Python verifier, the C enumeration program with logs, the independent clean-room verifier and its outputs, scripts for all sampling experiments with fixed random seeds, and SHA-256 checksums. Computations and drafting were assisted by the AI systems ChatGPT (OpenAI), Claude (Anthropic) and Grok (xAI), as described in the paper's acknowledgment.

View source

Similar papers

#artificial intelligence Conference Open access Apr 2020

ECCOLA - a Method for Implementing Ethically Aligned AI Systems

The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.

Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson · 64 citations · ⚡6
#computer vision Review Apr 2024

AI-powered Code Review with LLMs: Early Results

The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.

Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al. · 62 citations · ⚡3
#computer vision Open access Mar 2024

LLM-based agents for automating the enhancement of user story quality: An early report

The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.

Zheying Zhang, M. Rayhan, Tomas Herda et al. · 48 citations · ⚡4
#computer vision Review Mar 2024

System for systematic literature review using multiple AI agents: Concept and an empirical evaluation

This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.

Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al. · 44 citations · ⚡2
#computer vision Feb 2024

Can Large Language Models Serve as Data Analysts? A Multi-Agent Assisted Approach for Qualitative Data Analysis

The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.

Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al. · 41 citations
#artificial intelligence Conference Open access Jun 2018

The Key Concepts of Ethics of Artificial Intelligence

It is suggested that the focus on finding keywords is the first step in guiding and providing direction for future research in the AI ethics field.

Ville Vakkuri, P. Abrahamsson · 39 citations · ⚡2

Related blog posts

MIT News · Artificial Intelligence Oct 15, 2026

AI model decodes the language cells use to communicate

A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.