9 citations · 9 across the 4 of their papers we have counts for
4 papers
Effective and Efficient Conversation Retrieval for Dialogue State Tracking with Implicit Text Summaries
Seanie Lee, Jianpeng Cheng, Joris Driesen +2
Few-shot dialogue state tracking (DST) with Large Language Models (LLM) relies on an effective and efficient conversation retriever to find similar in-context examples for prompt l…
LUCID: LLM-Generated Utterances for Complex and Interesting Dialogues
Joe Stacey, Jianpeng Cheng, John Torr +5
Spurred by recent advances in Large Language Models (LLMs), virtual assistants are poised to take a leap forward in terms of their dialogue capabilities. Yet a major bottleneck to…
Fine-grained Late-interaction Multi-modal Retrieval for Retrieval Augmented Visual Question Answering
Weizhe Lin, Jinghong Chen, Jingbiao Mei +2
Knowledge-based Visual Question Answering (KB-VQA) requires VQA systems to utilize knowledge from external knowledge bases to answer visually-grounded questions. Retrieval-Augmente…
Grounding Description-Driven Dialogue State Trackers with Knowledge-Seeking Turns
Alexandru Coca, Bo-Hsiang Tseng, Jinghong Chen +4
Schema-guided dialogue state trackers can generalise to new domains without further training, yet they are sensitive to the writing style of the schemata. Augmenting the training s…