# RONA: Pragmatically Diverse Image Captioning with Coherence Relations

arXiv: https://arxiv.org/abs/2503.10997 · HTML: https://mlsanity.com/paper/2503.10997/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 20 of its 42 references that are in the map.
- First posted on arXiv 14 Mar 2025.

## Builds on (most cited first, 20 of 20)

- [Learning Transferable Visual Models From Natural Language Supervision](https://mlsanity.com/paper/2103.00020/) (2021)
- [BERTScore: Evaluating Text Generation with BERT](https://mlsanity.com/paper/1904.09675/) (2019)
- [CLIPScore: A Reference-free Evaluation Metric for Image Captioning](https://mlsanity.com/paper/2104.08718/) (2021)
- [Microsoft COCO Captions: Data Collection and Evaluation Server](https://mlsanity.com/paper/1504.00325/) (2015)
- [BLEURT: Learning Robust Metrics for Text Generation](https://mlsanity.com/paper/2004.04696/) (2020)
- [Winoground: Probing Vision and Language Models for Visio-Linguistic Compositionality](https://mlsanity.com/paper/2204.03162/) (2022)
- [Towards a Visual Privacy Advisor: Understanding and Predicting Privacy Risks in Images](https://mlsanity.com/paper/1703.10660/) (2017)
- [LION : Empowering Multimodal Large Language Model with Dual-Level Visual Knowledge](https://mlsanity.com/paper/2311.11860/) (2023)
- [A Design Space for Intelligent and Interactive Writing Assistants](https://mlsanity.com/paper/2403.14117/) (2024)
- [Standardizing the Measurement of Text Diversity: A Tool and a Comparative Analysis of Scores](https://mlsanity.com/paper/2403.00553/) (2024)
- [Comprehending and Ordering Semantics for Image Captioning](https://mlsanity.com/paper/2206.06930/) (2022)
- [Clue: Cross-modal Coherence Modeling for Caption Generation](https://mlsanity.com/paper/2005.00908/) (2020)
- [Diverse Image Captioning with Context-Object Split Latent Spaces](https://mlsanity.com/paper/2011.00966/) (2020)
- [CITE: A Corpus of Image-Text Discourse Relations](https://mlsanity.com/paper/1904.06286/) (2019)
- [The Role of Syntactic Planning in Compositional Image Captioning](https://mlsanity.com/paper/2101.11911/) (2021)
- [Understanding Social Media Cross-Modality Discourse in Linguistic Space](https://mlsanity.com/paper/2302.13311/) (2023)
- [ANNA: Abstractive Text-to-Image Synthesis with Filtered News Captions](https://mlsanity.com/paper/2301.02160/) (2023)
- [Learning Descriptive Image Captioning via Semipermeable Maximum Likelihood Estimation](https://mlsanity.com/paper/2306.13460/) (2023)
- [Understanding How Paper Writers Use AI-Generated Captions in Figure Caption Writing](https://mlsanity.com/paper/2501.06317/) (2025)
- [CORDIAL: Can Multimodal Large Language Models Effectively Understand Coherence Relationships?](https://mlsanity.com/paper/2502.11300/) (2025)

## Built on by (most cited first, 3 of 3)

- [IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection](https://mlsanity.com/paper/2505.16258/) (2025)
- [LaMP-Cap: Personalized Figure Caption Generation With Multimodal Figure Profiles](https://mlsanity.com/paper/2506.06561/) (2025)
- [Culture In a Frame: C3B as a Comic-Based Benchmark for Multimodal Culturally Awareness](https://mlsanity.com/paper/2510.00041/) (2025)

## Abstract (arXiv)

Writing Assistants (e.g., Grammarly, Microsoft Copilot) traditionally generate diverse image captions by employing syntactic and semantic variations to describe image components. However, human-written captions prioritize conveying a central message alongside visual descriptions using pragmatic cues. To enhance caption diversity, it is essential to explore alternative ways of communicating these messages in conjunction with visual content. We propose RONA, a novel prompting strategy for Multi-modal Large Language Models (MLLM) that leverages Coherence Relations as a controllable axis for pragmatic variations. We demonstrate that RONA generates captions with better overall diversity and ground-truth alignment, compared to MLLM baselines across multiple domains. Our code is available at: https://github.com/aashish2000/RONA