Abstract Automated Essay Scoring (AES) aims to score essays written in response to
specific prompts. Many AES models have been proposed, but most of them are either …

In Emotion Recognition in Conversations (ERC), the emotions of target utterances are
closely dependent on their context. Therefore, existing works train the model to generate the …

Achieving precise semantic control over the latent spaces of Variational AutoEncoders
(VAEs) holds significant value for downstream tasks in NLP as the underlying generative …

In the wake of responsible AI, interpretability methods, which attempt to provide an
explanation for the predictions of neural models have seen rapid progress. In this work, we …

Exploring the realms of counterfactuals, this paper introduces a versatile approach in text
generation using structural causal models (SCM), broadening the scope beyond traditional …

Disentangled latent spaces usually have better semantic separability and geometrical
properties, which leads to better interpretability and more controllable data generation …

With the rapid development of the internet in the past decade, it has become increasingly
important to extract valuable information from vast resources efficiently, which is crucial for …

Abstract Speculation and Negation Identification focuses on the extraction of speculative
and negative cues and scopes. Previous work relied on complete syntactic trees or simply …

With the rapid development of the internet in the past decade, it has become increasingly
important to extract valuable information from vast resources efficiently, which is crucial for …

Dataset bias, ie, the over-reliance on dataset-specific literal heuristics, is getting increasing
attention for its detrimental effect on the generalization ability of NLU models. Existing works …