1 citations · 1 across the 5 of their papers we have counts for
5 papers
Enhancing User Engagement in Socially-Driven Dialogue through Interactive LLM Alignments
Jiashuo Wang, Kaitao Song, Chunpu Xu +5
Enhancing user engagement through interactions plays an essential role in socially-driven dialogues. While prior works have optimized models to reason over relevant knowledge or pl…
Next-User Retrieval: Enhancing Cold-Start Recommendations via Generative Next-User Modeling
Yu-Ting Lan, Yang Huo, Yi Shen +2
The item cold-start problem is critical for online recommendation systems, as the success of this phase determines whether high-quality new items can transition to popular ones, re…
Listen, Analyze, and Adapt to Learn New Attacks: An Exemplar-Free Class Incremental Learning Method for Audio Deepfake Source Tracing
Yang Xiao, Rohan Kumar Das
As deepfake speech becomes common and hard to detect, it is vital to trace its source. Recent work on audio deepfake source tracing (ST) aims to find the origins of synthetic or ma…
NGENT: Next-Generation AI Agents Must Integrate Multi-Domain Abilities to Achieve Artificial General Intelligence
Zhicong Li, Hangyu Mao, Jiangjin Yin +4
This paper argues that the next generation of AI agent (NGENT) should integrate across-domain abilities to advance toward Artificial General Intelligence (AGI). Although current AI…
Buffer is All You Need: Defending Federated Learning against Backdoor Attacks under Non-iids via Buffering
Xingyu Lyu, Ning Wang, Yang Xiao +4
Federated Learning (FL) is a popular paradigm enabling clients to jointly train a global model without sharing raw data. However, FL is known to be vulnerable towards backdoor atta…