Search Results for author:
Found 7 papers, 3 papers with code
A Large-scale Comprehensive Abusiveness Detection Dataset with Multifaceted Labels from Reddit
As users in online communities suffer from severe side effects of abusive language, many researchers attempted to detect abusive texts from social media, presenting several datasets for such detection.
Universal Gloss-level Representation for Gloss-free Sign Language Translation and Production
Gloss-free methods have emerged to address these limitations, but they often depend on external sign language data or dictionaries, failing to completely eliminate the need for gloss annotations.
Gloss-free Sign Language Translation
Self-Supervised Learning
+4
Ask LLMs Directly, "What shapes your bias?": Measuring Social Bias in Large Language Models
To this end, we propose a novel strategy to intuitively quantify these social perceptions and suggest metrics that can evaluate the social biases within LLMs by aggregating diverse social perceptions.
Autoregressive Sign Language Production: A Gloss-Free Approach with Discrete Representations
Gloss-free Sign Language Production (SLP) offers a direct translation of spoken language sentences into sign language, bypassing the need for gloss intermediaries.
A Simple and Flexible Modeling for Mental Disorder Detection by Learning from Clinical Questionnaires
Our detailed analysis shows that the proposed model is effective at leveraging domain knowledge, transferable to other mental disorders, and providing interpretable detection results.
ELF22: A Context-based Counter Trolling Dataset to Combat Internet Trolls
In particular, we constructed a pair-wise dataset that includes troll comments and counter responses with labeled response strategies, which enables models fine-tuned on our dataset to generate responses by varying counter responses according to the specified strategy.
