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Graph Theory coverage.

Every story in the WeSearch catalog tagged with #graph-theory, chronological, with view counts. Subscribe to the per-tag RSS feed to follow this topic in your reader of choice.

7 stories tagged with #graph-theory, in publish-time order across the WeSearch catalog. Tag pages update as new stories ingest.

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#ai4#ml4#mathematics1#discrete-mathematics1#language-models1#reinforcement-learning1#education1#evaluation1
ARXIV CS.AI

GTBench: A Curriculum-Grounded Benchmark for Evaluating LLMs as Mathematical Research Assistants in Graph Theory

Large language models (LLMs) are increasingly used as self-study assistants in technical disciplines, yet their reliability as mathematical reasoning assistants remains poorly unde…

8 views ·
#artificial intelligence#education
AMAZON NEWS

AWS used random graph theory to build more efficient data centers

How a Slack shout-out, a dusted-off academic theory, and a spaghetti monster led an AWS team to crack an elusive code—and deliver greater reliability and performance for customers.…

13 views ·
ARXIV CS.AI

Fuzzy, Neutrosophic, and Uncertain Graph Theory: Properties and Applications

This book presents a comprehensive and systematic survey of graph theory under uncertainty, with particular emphasis on the unifying role of the uncertain graph framework. It revie…

22 views ·
#artificial intelligence#machine learning
ARXIV CS.AI

Clustering as Reasoning: A $k$-Means Interpretation of Chain-of-Thought Graph Learning

Chain-of-Thought (CoT) prompting has shown promise in enhancing the reasoning capabilities of large language models (LLMs) on text-attributed graphs (TAGs). This work reframes CoT-…

11 views ·
#artificial intelligence#machine learning
ARXIV CS.AI

Graph Alignment Topology as an Inductive Bias for Grounding Detection

Large Language Models (LLMs) are optimized to produce distributionally plausible continuations rather than to explicitly verify whether generated propositions are entailed by sourc…

10 views ·
#artificial intelligence#language models
ARXIV CS.AI

Reinforcement Learning for Microcanonical Graph Ensemble with Assortativity Constraints

How network structure determines function is a fundamental question, and it can be investigated by graph ensembles with precisely controlled structural properties. Canonical approa…

11 views ·
#machine learning#reinforcement learning
WOLFRAM

Self-Complementary Graphs

A self-complementary graph is a graph which is isomorphic to its graph complement. The numbers of simple self-complementary graphs on n=1, 2, ... nodes are 1, 0, 0, 1, 2, 0, 0, 10,…

13 views ·
#mathematics#discrete mathematics