1 citations · 1 across the 8 of their papers we have counts for
8 papers
HiRoute: Hierarchical Routed Prompt Tuning for Safety Alignment of Large Language Models
Fangzhou Chen, Shiji Zhao, Mengyang Wang +4
Large language models (LLMs) remain vulnerable to harmful requests and jailbreak attacks. Parameter-efficient safety alignment methods based on prompt tuning typically rely on a si…
MemGUI-Agent: An End-to-End Long-Horizon Mobile GUI Agent with Proactive Context Management
Guangyi Liu, Gao Wu, Congxiao Liu +7
MLLM-based mobile GUI agents have made substantial progress on short-horizon tasks, yet remain unreliable on long-horizon tasks that require retaining intermediate facts across man…
MobileForge: Annotation-Free Adaptation for Mobile GUI Agents with Hierarchical Feedback-Guided Policy Optimization
Guangyi Liu, Pengxiang Zhao, Gao Wu +9
MLLM-based mobile GUI agents have made substantial progress in UI understanding and action execution, but adapting them to real target apps remains costly because mobile apps are n…
Improving Safety Alignment via Balanced Direct Preference Optimization
Shiji Zhao, Mengyang Wang, Shukun Xiong +7
With the rapid development and widespread application of Large Language Models (LLMs), their potential safety risks have attracted widespread attention. Reinforcement Learning from…
Balancing Information Perception with Yin-Yang: Agent-Based Information Neutrality Model for Recommendation Systems
Mengyan Wang, Yuxuan Hu, Shiqing Wu +3
While preference-based recommendation algorithms effectively enhance user engagement by recommending personalized content, they often result in the creation of ``filter bubbles''.…
BHEISR: Nudging from Bias to Balance -- Promoting Belief Harmony by Eliminating Ideological Segregation in Knowledge-based Recommendations
Mengyan Wang, Yuxuan Hu, Zihan Yuan +4
In the realm of personalized recommendation systems, the increasing concern is the amplification of belief imbalance and user biases, a phenomenon primarily attributed to the filte…
DOR: A Novel Dual-Observation-Based Approach for News Recommendation Systems
Mengyan Wang, Weihua Li, Jingli Shi +2
Online social media platforms offer access to a vast amount of information, but sifting through the abundance of news can be overwhelming and tiring for readers. personalised recom…
Scientific Paper Recommendation: A Survey
Xiaomei Bai, Mengyang Wang, Ivan Lee +3
Globally, recommendation services have become important due to the fact that they support e-commerce applications and different research communities. Recommender systems have a lar…