1 citations · 1 across the 9 of their papers we have counts for
9 papers
Learning Through Dialogue: Engagement and Efficacy Matter More Than Explanations
Shaz Furniturewala, Gerard Christopher Yeo, Kokil Jaidka
Large language models (LLMs) are increasingly used as conversational partners for learning, yet the interactional dynamics supporting users' learning and engagement are understudie…
Towards Inclusive Toxic Content Moderation: Addressing Vulnerabilities to Adversarial Attacks in Toxicity Classifiers Tackling LLM-generated Content
Shaz Furniturewala, Arkaitz Zubiaga
The volume of machine-generated content online has grown dramatically due to the widespread use of Large Language Models (LLMs), leading to new challenges for content moderation sy…
Impact of Decoding Methods on Human Alignment of Conversational LLMs
Shaz Furniturewala, Kokil Jaidka, Yashvardhan Sharma
To be included into chatbot systems, Large language models (LLMs) must be aligned with human conversational conventions. However, being trained mainly on web-scraped data gives exi…
Turn-Level Empathy Prediction Using Psychological Indicators
Shaz Furniturewala, Kokil Jaidka
For the WASSA 2024 Empathy and Personality Prediction Shared Task, we propose a novel turn-level empathy detection method that decomposes empathy into six psychological indicators:…
Beyond Text: Leveraging Multi-Task Learning and Cognitive Appraisal Theory for Post-Purchase Intention Analysis
Gerard Christopher Yeo, Shaz Furniturewala, Kokil Jaidka
Supervised machine-learning models for predicting user behavior offer a challenging classification problem with lower average prediction performance scores than other text classifi…
Thinking Fair and Slow: On the Efficacy of Structured Prompts for Debiasing Language Models
Shaz Furniturewala, Surgan Jandial, Abhinav Java +4
Existing debiasing techniques are typically training-based or require access to the model's internals and output distributions, so they are inaccessible to end-users looking to ada…