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A Survey on Recent Advances in Conversational Data Generation
Heydar Soudani, Roxana Petcu, Evangelos Kanoulas +1
Recent advancements in conversational systems have significantly enhanced human-machine interactions across various domains. However, training these systems is challenging due to t…
Self-seeding and Multi-intent Self-instructing LLMs for Generating Intent-aware Information-Seeking dialogs
Arian Askari, Roxana Petcu, Chuan Meng +4
Identifying user intents in information-seeking dialogs is crucial for a system to meet user's information needs. Intent prediction (IP) is challenging and demands sufficient dialo…
Fine Tuning vs. Retrieval Augmented Generation for Less Popular Knowledge
Heydar Soudani, Evangelos Kanoulas, Faegheh Hasibi
Language Models (LMs) memorize a vast amount of factual knowledge, exhibiting strong performance across diverse tasks and domains. However, it has been observed that the performanc…
Learning to Ask: Conversational Product Search via Representation Learning
Jie Zou, Jimmy Xiangji Huang, Zhaochun Ren +1
Online shopping platforms, such as Amazon and AliExpress, are increasingly prevalent in society, helping customers purchase products conveniently. With recent progress in natural l…
QFMTS: Generating Query-Focused Summaries over Multi-Table Inputs
Weijia Zhang, Vaishali Pal, Jia-Hong Huang +2
Table summarization is a crucial task aimed at condensing information from tabular data into concise and comprehensible textual summaries. However, existing approaches often fall s…
Leveraging Graph Structures to Detect Hallucinations in Large Language Models
Noa Nonkes, Sergei Agaronian, Evangelos Kanoulas +1
Large language models are extensively applied across a wide range of tasks, such as customer support, content creation, educational tutoring, and providing financial guidance. Howe…