Graph-to-Sequence

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

2 leaderboard tables shown for this task, 2 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

4 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Most implemented papers archive 2025-07-28

29 shown of 29 papers with code (48 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Neural AMR: Sequence-to-Sequence Models for Parsing and Generation
  26 Apr 2017 5 repositories listed
  Sequence-to-sequence models have shown strong performance across a broad range of applications.
• Graph2Seq: Graph to Sequence Learning with Attention-based Neural Networks
  3 Apr 2018 4 repositories listed Syntology ran 2 of 10 samples · 8 unverified
  Our method first generates the node and graph embeddings using an improved graph-based neural network with a novel aggregation strategy to incorporate edge direction information in the node embeddings.
• A physics-informed neural network for wind turbine main bearing fatigue
  5 May 2020 2 repositories listed
  Unexpected main bearing failure on a wind turbine causes unwanted maintenance and increased operation costs (mainly due to crane, parts, labor, and production loss).
• Physics-informed neural networks for corrosion-fatigue prognosis
  22 Sep 2019 2 repositories listed
  The result is a cumulative damage model where the physics-informed layers are used to model the relatively well understood physics (crack growth through Paris law) and the data-driven layers account for the hard to…
• Structural Neural Encoders for AMR-to-text Generation
  27 Mar 2019 2 repositories listed
  AMR-to-text generation is a problem recently introduced to the NLP community, in which the goal is to generate sentences from Abstract Meaning Representation (AMR) graphs.
• Deep Graph Convolutional Encoders for Structured Data to Text Generation
  23 Oct 2018 2 repositories listed Syntology ran 1 of 3 samples · 2 unverified
  Most previous work on neural text generation from graph-structured data relies on standard sequence-to-sequence methods.
• Graph-to-Sequence Learning using Gated Graph Neural Networks
  26 Jun 2018 2 repositories listed Syntology ran 0 of 4 samples · 4 unverified
  Many NLP applications can be framed as a graph-to-sequence learning problem.
• PDG2Seq: Periodic Dynamic Graph to Sequence Model for Traffic Flow Prediction
  5 Dec 2024 1 repository listed
  To address these findings, this paper proposes a Periodic Dynamic Graph to Sequence Model (PDG2Seq) for traffic flow prediction.
• Ontology-Free General-Domain Knowledge Graph-to-Text Generation Dataset Synthesis using Large Language Model
  11 Sep 2024 1 repository listed Syntology ran 5 of 7 samples · 2 unverified · 7 pointer-only (licence)
  Our method proves to be a scalable and effective solution for generating high-quality G2T data, significantly advancing the field of G2T generation.
• Ask Questions with Double Hints: Visual Question Generation with Answer-awareness and Region-reference
  6 Jul 2024 1 repository listed
  The visual question generation (VQG) task aims to generate human-like questions from an image and potentially other side information (e.
• UAlign: Pushing the Limit of Template-free Retrosynthesis Prediction with Unsupervised SMILES Alignment
  25 Mar 2024 1 repository listed
  Single-step retrosynthesis prediction, a crucial step in the planning process, has witnessed a surge in interest in recent years due to advancements in AI for science.
• Predicting Parking Lot Availability by Graph-to-Sequence Model: A Case Study with SmartSantander
  21 Jun 2022 1 repository listed
  Nowadays, so as to improve services and urban areas livability, multiple smart city initiatives are being carried out throughout the world.
• Permutation invariant graph-to-sequence model for template-free retrosynthesis and reaction prediction
  19 Oct 2021 1 repository listed Syntology ran 0 of 6 samples · 6 unverified
  Synthesis planning and reaction outcome prediction are two fundamental problems in computer-aided organic chemistry for which a variety of data-driven approaches have emerged.
• GPT-too: A language-model-first approach for AMR-to-text generation
  18 May 2020 1 repository listed Syntology ran 2 of 6 samples · 4 unverified
  Meaning Representations (AMRs) are broad-coverage sentence-level semantic graphs.
• ENT-DESC: Entity Description Generation by Exploring Knowledge Graph
  30 Apr 2020 1 repository listed
  Previous works on knowledge-to-text generation take as input a few RDF triples or key-value pairs conveying the knowledge of some entities to generate a natural language description.
• Modeling Global and Local Node Contexts for Text Generation from Knowledge Graphs
  29 Jan 2020 1 repository listed
  Recent graph-to-text models generate text from graph-based data using either global or local aggregation to learn node representations.
• Graph Transformer for Graph-to-Sequence Learning
  18 Nov 2019 1 repository listed Syntology ran 0 of 10 samples · 10 unverified
  The dominant graph-to-sequence transduction models employ graph neural networks for graph representation learning, where the structural information is reflected by the receptive field of neurons.
• Natural Question Generation with Reinforcement Learning Based Graph-to-Sequence Model
  19 Oct 2019 1 repository listed
  Natural question generation (QG) aims to generate questions from a passage and an answer.
• Enhancing AMR-to-Text Generation with Dual Graph Representations
  1 Sep 2019 1 repository listed
  Generating text from graph-based data, such as Abstract Meaning Representation (AMR), is a challenging task due to the inherent difficulty in how to properly encode the structure of a graph with labeled edges.
• Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning
  16 Aug 2019 1 repository listed
  We focus on graph-to-sequence learning, which can be framed as transducing graph structures to sequences for text generation.
• Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation
  14 Aug 2019 1 repository listed Syntology ran 0 of 10 samples · 10 unverified
  Natural question generation (QG) aims to generate questions from a passage and an answer.
• Coherent Comments Generation for Chinese Articles with a Graph-to-Sequence Model
  1 Jul 2019 1 repository listed
  In this paper, we propose to generate comments with a graph-to-sequence model that models the input news as a topic interaction graph.
• Coherent Comment Generation for Chinese Articles with a Graph-to-Sequence Model
  4 Jun 2019 1 repository listed
  In this paper, we propose to generate comments with a graph-to-sequence model that models the input news as a topic interaction graph.
• STG2Seq: Spatial-temporal Graph to Sequence Model for Multi-step Passenger Demand Forecasting
  24 May 2019 1 repository listed
  Multi-step passenger demand forecasting is a crucial task in on-demand vehicle sharing services.
• Step-by-Step: Separating Planning from Realization in Neural Data-to-Text Generation
  6 Apr 2019 1 repository listed Syntology ran 0 of 5 samples · 5 unverified
  We propose to split the generation process into a symbolic text-planning stage that is faithful to the input, followed by a neural generation stage that focuses only on realization.
• Fleet Prognosis with Physics-informed Recurrent Neural Networks
  16 Jan 2019 1 repository listed
  The results demonstrate that our proposed hybrid physics-informed recurrent neural network is able to accurately model fatigue crack growth even when the observed distribution of crack length does not match with the…
• SQL-to-Text Generation with Graph-to-Sequence Model
  14 Sep 2018 1 repository listed Syntology ran 1 of 7 samples · 6 unverified
  Previous work approaches the SQL-to-text generation task using vanilla Seq2Seq models, which may not fully capture the inherent graph-structured information in SQL query.
• Exploiting Rich Syntactic Information for Semantic Parsing with Graph-to-Sequence Model
  23 Aug 2018 1 repository listed Syntology ran 1 of 7 samples · 6 unverified
  Existing neural semantic parsers mainly utilize a sequence encoder, i.
• A Graph-to-Sequence Model for AMR-to-Text Generation
  7 May 2018 1 repository listed
  The problem of AMR-to-text generation is to recover a text representing the same meaning as an input AMR graph.

Syntology lines on 11 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.