15 papers
Probing Multimodal Large Language Models on Cognitive Biases in Chinese Short-Video Misinformation
Jen-tse Huang, Chang Chen, Shiyang Lai +3
Short-video platforms have become major channels for misinformation, where deceptive claims frequently leverage visual experiments and social cues. While Multimodal Large Language…
Human Cognitive Benchmarks Reveal Foundational Visual Gaps in MLLMs
Jen-Tse Huang, Dasen Dai, Jen-Yuan Huang +7
Humans develop perception through a bottom-up hierarchy: from basic primitives and Gestalt principles to high-level semantics. In contrast, current Multimodal Large Language Models…
A Survey on the Safety and Security Threats of Computer-Using Agents: JARVIS or Ultron?
Ada Chen, Yongjiang Wu, Junyuan Zhang +6
Recently, AI-driven interactions with computing devices have advanced from basic prototype tools to sophisticated, LLM-based systems that emulate human-like operations in graphical…
Curing Miracle Steps in LLM Mathematical Reasoning with Rubric Rewards
Youliang Yuan, Qiuyang Mang, Jingbang Chen +7
In this paper, we observe that current models are susceptible to reward hacking, leading to a substantial overestimation of a model's reasoning ability. This is evidenced by a high…
The PIMMUR Principles: Ensuring Validity in Collective Behavior of LLM Societies
Jiaxu Zhou, Jen-tse Huang, Xuhui Zhou +5
Large language models (LLMs) are increasingly deployed to simulate human collective behaviors, yet the methodological rigor of these "AI societies" remains under-explored. Through…
On the Failure of Latent State Persistence in Large Language Models
Jen-tse Huang, Kaiser Sun, Wenxuan Wang +1
While Large Language Models (LLMs) excel in reasoning, whether they can sustain persistent latent states remains under-explored. The capacity to maintain and manipulate unexpressed…