Signals 4 · free daily AI digest

Recurrent GraphNeural NetworkswithSet-BasedAggregation

Paper recorded by Signals 4 on 2026-09-14 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-14 on arXiv · recorded by Signals 4 on 2026-09-15

Category: cs.AI · 人工智能 · first seen 2026-09-15

Abstract

Recurrent GNNs iterate message passing to convergence, and their logical characterizations to date rely on multi-set aggregation, graded (counting) logics, and halting or acceptance conditions that cannot be verified from the network's parameters. We study recurrent GNNs with set-based aggregation and identify sufficient conditions checkable from the weights for networks to compile into formulas a

Read on arXiv →

#65 most recent of 300 cs.AI papers we have recorded · ↑ newer: Vulnerability Localization Benchmark: Measuring Agentic Security Analy · ↓ older: Pilot Early, Commit Late: A Real-Options Model of Enterprise AI Adopti
Cite this page: Recurrent GraphNeural NetworkswithSet-BasedAggregation: the #65 most recent of 300 cs.AI papers we have recorded (as of 2026-09-14). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/recurrent-graphneural-networkswithset-basedaggregation.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
Related: More cs.AI papers · arXiv signals · All papers · Today in AI
Get 4 AI signals a day by email — free.
Subscribe free → See all plans →
Get 4 AI signals a day by email — free
All models · All repos · By company · Daily editions