activity
20222024
most citedLearning Retrieval Augmentation for Personalized Dialogue Generation

16 citations · 43 across the 13 of their papers we have counts for

collaborators

13 papers

cs.CL202416 cited

Learning Retrieval Augmentation for Personalized Dialogue Generation

Qiushi Huang, Shuai Fu, Xubo Liu +4

Personalized dialogue generation, focusing on generating highly tailored responses by leveraging persona profiles and dialogue context, has gained significant attention in conversa…

cs.CL20241 cited

Selective Prompting Tuning for Personalized Conversations with LLMs

Qiushi Huang, Xubo Liu, Tom Ko +4

In conversational AI, personalizing dialogues with persona profiles and contextual understanding is essential. Despite large language models' (LLMs) improved response coherence, ef…

cs.SD20246 cited

ComposerX: Multi-Agent Symbolic Music Composition with LLMs

Qixin Deng, Qikai Yang, Ruibin Yuan +16

Music composition represents the creative side of humanity, and itself is a complex task that requires abilities to understand and generate information with long dependency and har…

cs.SD2024

T-CLAP: Temporal-Enhanced Contrastive Language-Audio Pretraining

Yi Yuan, Zhuo Chen, Xubo Liu +6

Contrastive language-audio pretraining~(CLAP) has been developed to align the representations of audio and language, achieving remarkable performance in retrieval and classificatio…

cs.CV2023

CM-PIE: Cross-modal perception for interactive-enhanced audio-visual video parsing

Yaru Chen, Ruohao Guo, Xubo Liu +4

Audio-visual video parsing is the task of categorizing a video at the segment level with weak labels, and predicting them as audible or visible events. Recent methods for this task…

cs.SD20231 cited

Synth-AC: Enhancing Audio Captioning with Synthetic Supervision

Feiyang Xiao, Qiaoxi Zhu, Jian Guan +4

Data-driven approaches hold promise for audio captioning. However, the development of audio captioning methods can be biased due to the limited availability and quality of text-aud…