# A Recurrent Neural Model with Attention for the Recognition of Chinese Implicit Discourse Relations

arXiv: https://arxiv.org/abs/1704.08092 · HTML: https://mlsanity.com/paper/1704.08092/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Apr 2017.

## Built on by (most cited first, 2 of 2)

- [A Survey of Implicit Discourse Relation Recognition](https://mlsanity.com/paper/2203.02982/) (2022)
- [Fine-Grained Evaluation for Implicit Discourse Relation Recognition](https://mlsanity.com/paper/2503.05326/) (2025)

## Abstract (arXiv)

We introduce an attention-based Bi-LSTM for Chinese implicit discourse relations and demonstrate that modeling argument pairs as a joint sequence can outperform word order-agnostic approaches. Our model benefits from a partial sampling scheme and is conceptually simple, yet achieves state-of-the-art performance on the Chinese Discourse Treebank. We also visualize its attention activity to illustrate the model's ability to selectively focus on the relevant parts of an input sequence.