27 citations · 50 across the 9 of their papers we have counts for
10 papers
Training Zero-Shot Generalizable End-to-End Task-Oriented Dialog System Without Turn-level Dialog Annotations
Adib Mosharrof, A. B. Siddique
Task-oriented dialogue (TOD) systems enable users to achieve their goals through natural language interactions. Traditionally, these systems have relied on turn-level manually anno…
Zero-Shot Generalizable End-to-End Task-Oriented Dialog System using Context Summarization and Domain Schema
Adib Mosharrof, M. H. Maqbool, A. B. Siddique
Task-oriented dialog systems empower users to accomplish their goals by facilitating intuitive and expressive natural language interactions. State-of-the-art approaches in task-ori…
Toward Open-domain Slot Filling via Self-supervised Co-training
Adib Mosharrof, Moghis Fereidouni, A. B. Siddique
Slot filling is one of the critical tasks in modern conversational systems. The majority of existing literature employs supervised learning methods, which require labeled training…
Personalizing Task-oriented Dialog Systems via Zero-shot Generalizable Reward Function
A. B. Siddique, M. H. Maqbool, Kshitija Taywade +1
Task-oriented dialog systems enable users to accomplish tasks using natural language. State-of-the-art systems respond to users in the same way regardless of their personalities, a…
MobileRec: A Large-Scale Dataset for Mobile Apps Recommendation
M. H. Maqbool, Umar Farooq, Adib Mosharrof +2
Recommender systems have become ubiquitous in our digital lives, from recommending products on e-commerce websites to suggesting movies and music on streaming platforms. Existing r…
Proactive Prioritization of App Issues via Contrastive Learning
Moghis Fereidouni, Adib Mosharrof, Umar Farooq +1
Mobile app stores produce a tremendous amount of data in the form of user reviews, which is a huge source of user requirements and sentiments; such reviews allow app developers to…
Generalized Zero-shot Intent Detection via Commonsense Knowledge
A. B. Siddique, Fuad Jamour, Luxun Xu +1
Identifying user intents from natural language utterances is a crucial step in conversational systems that has been extensively studied as a supervised classification problem. Howe…
Linguistically-Enriched and Context-Aware Zero-shot Slot Filling
A. B. Siddique, Fuad Jamour, Vagelis Hristidis
Slot filling is identifying contiguous spans of words in an utterance that correspond to certain parameters (i.e., slots) of a user request/query. Slot filling is one of the most i…
Unsupervised Paraphrasing via Deep Reinforcement Learning
A. B. Siddique, Samet Oymak, Vagelis Hristidis
Paraphrasing is expressing the meaning of an input sentence in different wording while maintaining fluency (i.e., grammatical and syntactical correctness). Most existing work on pa…
App-Aware Response Synthesis for User Reviews
Umar Farooq, A. B. Siddique, Fuad Jamour +2
Responding to user reviews promptly and satisfactorily improves application ratings, which is key to application popularity and success. The proliferation of such reviews makes it…