activity
20242026
most citedMoltNet: Understanding Social Behavior of AI Agents in the Agent-Native MoltBook

1 citations · 1 across the 5 of their papers we have counts for

collaborators

12 papers

cs.CL2026

Beyond Alignment: Value Diversity as a Collective Property in Multicultural Agent Systems

Shaoyang Xu, Jingshen Zhang, Long P. Hoang +2

Multicultural multi-agent systems are increasingly deployed in globally diverse settings, where different agents are grounded in different cultural backgrounds. Existing cultural e…

cs.AI2026

Safety Paradox: How Enhanced Safety Awareness Leaves LLMs Vulnerable to Posterior Attack

Long P. Hoang, Hai V. Le, Shaoyang Xu +2

Large language models (LLMs) are rigorously aligned to refuse harmful requests, a process that inherently cultivates a latent capacity to evaluate and recognize unsafe content. In…

cs.CL2026

Process Rewards with Learned Reliability

Jinyuan Li, Langlin Huang, Chengsong Huang +5

Process Reward Models (PRMs) provide step-level feedback for reasoning, but current PRMs usually output only a single reward score for each step. Downstream methods must therefore…

cs.CL2026

Language of Thought Shapes Output Diversity in Large Language Models

Shaoyang Xu, Wenxuan Zhang

Output diversity is crucial for Large Language Models as it underpins pluralism and creativity. In this work, we reveal that controlling the language used during model thinking-the…

cs.SI20261 cited

MoltNet: Understanding Social Behavior of AI Agents in the Agent-Native MoltBook

Yi Feng, Chen Huang, Zhibo Man +4

Large-scale communities of AI agents are becoming increasingly prevalent, creating new environments for agent-agent social interaction. Prior work has examined multi-agent behavior…

cs.LG2026

Training Data Efficiency in Multimodal Process Reward Models

Jinyuan Li, Chengsong Huang, Langlin Huang +4

Multimodal Process Reward Models (MPRMs) are central to step-level supervision for visual reasoning in MLLMs. Training MPRMs typically requires large-scale Monte Carlo (MC)-annotat…