# Metaphor Detection with Effective Context Denoising

arXiv: https://arxiv.org/abs/2302.05611 · HTML: https://mlsanity.com/paper/2302.05611/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 28 references that are in the map.
- First posted on arXiv 11 Feb 2023.

## Builds on (most cited first, 8 of 8)

- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Deep Biaffine Attention for Neural Dependency Parsing](https://mlsanity.com/paper/1611.01734/) (2016)
- [Relational Graph Attention Network for Aspect-based Sentiment Analysis](https://mlsanity.com/paper/2004.12362/) (2020)
- [MelBERT: Metaphor Detection via Contextualized Late Interaction using Metaphorical Identification Theories](https://mlsanity.com/paper/2104.13615/) (2021)
- [Neural Metaphor Detection in Context](https://mlsanity.com/paper/1808.09653/) (2018)
- [Guiding the Growth: Difficulty-Controllable Question Generation through Step-by-Step Rewriting](https://mlsanity.com/paper/2105.11698/) (2021)
- [The Secret of Metaphor on Expressing Stronger Emotion](https://mlsanity.com/paper/2301.13042/) (2023)
- [Nominal Metaphor Generation with Multitask Learning](https://mlsanity.com/paper/2206.05195/) (2022)

## Built on by (most cited first, 13 of 13)

- [Metaphor Detection via Explicit Basic Meanings Modelling](https://mlsanity.com/paper/2305.17268/) (2023)
- [MMTE: Corpus and Metrics for Evaluating Machine Translation Quality of Metaphorical Language](https://mlsanity.com/paper/2406.13698/) (2024)
- [Construction Artifacts in Metaphor Identification Datasets](https://mlsanity.com/paper/2311.00790/) (2023)
- [Meta4XNLI: A Crosslingual Parallel Corpus for Metaphor Detection and Interpretation](https://mlsanity.com/paper/2404.07053/) (2024)
- [Finding Challenging Metaphors that Confuse Pretrained Language Models](https://mlsanity.com/paper/2401.16012/) (2024)
- [Train & Constrain: Phonologically Informed Tongue-Twister Generation from Topics and Paraphrases](https://mlsanity.com/paper/2403.13901/) (2024)
- [Overview of the NLPCC 2024 Shared Task on Chinese Metaphor Generation](https://mlsanity.com/paper/2408.04378/) (2024)
- [Hummus: A Dataset of Humorous Multimodal Metaphor Use](https://mlsanity.com/paper/2504.02983/) (2025)
- [Interpretable Chinese Metaphor Identification via LLM-Assisted MIPVU Rule Script Generation: A Comparative Protocol Study](https://mlsanity.com/paper/2603.10784/) (2026)
- [Exploring Task Performance with Interpretable Models via Sparse Auto-Encoders](https://mlsanity.com/paper/2507.06427/) (2025)
- [Deep Learning-Based Knowledge Injection for Metaphor Detection: A Comprehensive Review](https://mlsanity.com/paper/2308.04306/) (2023)
- [Span Modeling for Idiomaticity and Figurative Language Detection with Span Contrastive Loss](https://mlsanity.com/paper/2603.22799/) (2026)
- [Learning the Cue or Learning the Word? Analyzing Generalization in Metaphor Detection for Verbs](https://mlsanity.com/paper/2604.13713/) (2026)

## Abstract (arXiv)

We propose a novel RoBERTa-based model, RoPPT, which introduces a target-oriented parse tree structure in metaphor detection. Compared to existing models, RoPPT focuses on semantically relevant information and achieves the state-of-the-art on several main metaphor datasets. We also compare our approach against several popular denoising and pruning methods, demonstrating the effectiveness of our approach in context denoising. Our code and dataset can be found at https://github.com/MajiBear000/RoPPT