# SocAoG: Incremental Graph Parsing for Social Relation Inference in Dialogues

arXiv: https://arxiv.org/abs/2106.01006 · HTML: https://mlsanity.com/paper/2106.01006/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- Builds on 22 of its 46 references that are in the map.
- First posted on arXiv 2 Jun 2021.

## Builds on (most cited first, 22 of 22)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Human-centric Indoor Scene Synthesis Using Stochastic Grammar](https://mlsanity.com/paper/1808.08473/) (2018)
- [Dialogue-Based Relation Extraction](https://mlsanity.com/paper/2004.08056/) (2020)
- [MovieGraphs: Towards Understanding Human-Centric Situations from Videos](https://mlsanity.com/paper/1712.06761/) (2017)
- [Structured Prediction Energy Networks](https://mlsanity.com/paper/1511.06350/) (2015)
- [Few-shot Relation Extraction via Bayesian Meta-learning on Relation Graphs](https://mlsanity.com/paper/2007.02387/) (2020)
- [Fine-tuning Pre-Trained Transformer Language Models to Distantly Supervised Relation Extraction](https://mlsanity.com/paper/1906.08646/) (2019)
- [GDPNet: Refining Latent Multi-View Graph for Relation Extraction](https://mlsanity.com/paper/2012.06780/) (2020)
- [Frowning Frodo, Wincing Leia, and a Seriously Great Friendship: Learning to Classify Emotional Relationships of Fictional Characters](https://mlsanity.com/paper/1903.12453/) (2019)
- [Learning Interactions and Relationships between Movie Characters](https://mlsanity.com/paper/2003.13158/) (2020)
- [Learning Social Affordance for Human-Robot Interaction](https://mlsanity.com/paper/1604.03692/) (2016)
- [Structured Attention for Unsupervised Dialogue Structure Induction](https://mlsanity.com/paper/2009.08552/) (2020)
- [Inferring Interpersonal Relations in Narrative Summaries](https://mlsanity.com/paper/1512.00112/) (2015)
- [A Survey of Deep Learning Methods for Relation Extraction](https://mlsanity.com/paper/1705.03645/) (2017)
- [An Embarrassingly Simple Model for Dialogue Relation Extraction](https://mlsanity.com/paper/2012.13873/) (2020)
- [Improved Relation Extraction with Feature-Rich Compositional Embedding Models](https://mlsanity.com/paper/1505.02419/) (2015)
- [Dialogue Relation Extraction with Document-level Heterogeneous Graph Attention Networks](https://mlsanity.com/paper/2009.05092/) (2020)
- [High-order Semantic Role Labeling](https://mlsanity.com/paper/2010.04641/) (2020)
- [Relation of the Relations: A New Paradigm of the Relation Extraction Problem](https://mlsanity.com/paper/2006.03719/) (2020)
- [Deep Bidirectional Transformers for Relation Extraction without Supervision](https://mlsanity.com/paper/1911.00313/) (2019)
- [Vertical-Horizontal Structured Attention for Generating Music with Chords](https://mlsanity.com/paper/2011.09078/) (2020)

## Built on by (most cited first, 9 of 9)

- [Visual Chain of Thought: Bridging Logical Gaps with Multimodal Infillings](https://mlsanity.com/paper/2305.02317/) (2023)
- [Multimodal Procedural Planning via Dual Text-Image Prompting](https://mlsanity.com/paper/2305.01795/) (2023)
- [ValueNet: A New Dataset for Human Value Driven Dialogue System](https://mlsanity.com/paper/2112.06346/) (2021)
- [A Comprehensive Survey on Relation Extraction: Recent Advances and New Frontiers](https://mlsanity.com/paper/2306.02051/) (2023)
- [SPRING: Situated Conversation Agent Pretrained with Multimodal Questions from Incremental Layout Graph](https://mlsanity.com/paper/2301.01949/) (2023)
- [D-REX: Dialogue Relation Extraction with Explanations](https://mlsanity.com/paper/2109.05126/) (2021)
- [Generic Dependency Modeling for Multi-Party Conversation](https://mlsanity.com/paper/2302.10680/) (2023)
- [DialogRE^C+: An Extension of DialogRE to Investigate How Much Coreference Helps Relation Extraction in Dialogs](https://mlsanity.com/paper/2308.04498/) (2023)
- [Value-Spectrum: Quantifying Preferences of Vision-Language Models via Value Decomposition in Social Media Contexts](https://mlsanity.com/paper/2411.11479/) (2024)

## Abstract (arXiv)

Inferring social relations from dialogues is vital for building emotionally intelligent robots to interpret human language better and act accordingly. We model the social network as an And-or Graph, named SocAoG, for the consistency of relations among a group and leveraging attributes as inference cues. Moreover, we formulate a sequential structure prediction task, and propose an α-β-γ strategy to incrementally parse SocAoG for the dynamic inference upon any incoming utterance: (i) an α process predicting attributes and relations conditioned on the semantics of dialogues, (ii) a β process updating the social relations based on related attributes, and (iii) a γ process updating individual's attributes based on interpersonal social relations. Empirical results on DialogRE and MovieGraph show that our model infers social relations more accurately than the state-of-the-art methods. Moreover, the ablation study shows the three processes complement each other, and the case study demonstrates the dynamic relational inference.