Structurally Speaking: Motif-Oriented Graph Captioning through Bidirectional Graph-Text Translation
Updated 49 min ago · first seen 11 Sept 2026
paper_01M294FQB47K8ANN0YZVYZTNJH
- Published
- 11 Sept 2026
- T1 · 50 min ago
- arXiv
- 2609.10923
- T1 · 50 min ago
- Category
- cs.CL
- T1 · 50 min ago
Abstract
Graph captions should help readers understand graph structure, rather than simply translate adjacency matrices into long textual edge lists. A useful graph caption abstracts connectivity into recognizable motifs, such as hubs, paths, cycles, cliques, and bridges, because these motifs provide compact structural units that are easier to read, compare, and recover. In this paper, we study motif-oriented graph captioning as a bidirectional graph-text translation task, where captions must both preserve enough topology for graph recovery and express the graph through concise motif-level descriptions. We show that direct prompting of GPT-5.1 often produces graph-recoverable captions by enumerating node-to-node connections, but these captions are verbose and can contain inconsistent motif interpretations. To address this gap, we introduce Structurally Speaking, a lightweight structured prompting protocol that guides translation between explicit connectivity and motif-level abstraction. Experiments on a synthetic motif-based dataset show that structured prompting produces shorter and more motif-consistent captions while maintaining comparable graph recovery. These results suggest that explicit topology-to-motif reasoning guidance can make LLM-generated graph captions more interpretable without model fine-tuning.
Authors 3
Hsiao-Ying Lu, Dongyu Liu, Kwan-Liu Ma
Specification
- Official page
Source:arXiv (Atom API + RSS)T1observed 50 min agohigh
- Arxiv announce type
- new
Source:arXiv (Atom API + RSS)T1observed 50 min agohigh
- arXiv id
- 2609.10923
Source:arXiv (Atom API + RSS)T1observed 50 min agohigh
- Categories
- cs.CL, cs.LG
Source:arXiv (Atom API + RSS)T1observed 50 min agohigh
Source:arXiv (Atom API + RSS)T1observed 50 min agohigh
- Primary category
- cs.CL
Source:arXiv (Atom API + RSS)T1observed 50 min agohigh
- Published
- 11 Sept 2026
Source:arXiv (Atom API + RSS)T1observed 50 min agohigh
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Provenance
Attributed facts
9
Source tiers
T19
Freshest observation
50 min ago
Conflicts
None
No models linked to this paper yet.
- Authors
- Hsiao-Ying Lu, Dongyu Liu, Kwan-Liu Ma
As of
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Claim history · Official page
Official pageofficial_url1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| https://arxiv.org/abs/2609.10923 | → current | current | arXiv (Atom API + RSS)T1 | high | deterministic |
Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →
- Property changedPaperStructurally Speaking: Motif-Oriented Graph Captioning through Bidirectional Graph-Text Translation
Structurally Speaking: Motif-Oriented Graph Captioning through Bidirectional Graph-Text Translation: arxiv announce type changed from cross to new
Arxiv announce typecross→newarxiv - New paperPaperStructurally Speaking: Motif-Oriented Graph Captioning through Bidirectional Graph-Text Translation
New paper: Structurally Speaking: Motif-Oriented Graph Captioning through Bidirectional Graph-Text Translation
arxiv
| Source | Document | Type | Tier | Last observed | Snapshots |
|---|---|---|---|---|---|
| arXiv (Atom API + RSS) | rss.arxiv.org/rss/cs.CL | feed | T1· Official | 49 min ago | 1 |
| arXiv (Atom API + RSS) | rss.arxiv.org/rss/cs.LG | feed | T1· Official | 50 min ago | 1 |
Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.