3 citations · 9 across the 26 of their papers we have counts for
7 papers · 1 filter
Mint-Agent: Introducing Finance-Native Agentic Foundation Models
Agent Team, Kun Wang, Gavin Zhang +7
Financial agents must do more than recall domain knowledge: they must be both reliable, executing precise operations over grounded evidence, and executive, sustaining long-horizon…
HearSay Benchmark: Do Audio LLMs Leak What They Hear?
Jin Wang, Liang Lin, Kaiwen Luo +8
While Audio Large Language Models (ALLMs) have achieved remarkable progress in understanding and generation, their potential privacy implications remain largely unexplored. This pa…
DiffuGuard: How Intrinsic Safety is Lost and Found in Diffusion Large Language Models
Zherui Li, Zheng Nie, Zhenhong Zhou +7
The rapid advancement of Diffusion Large Language Models (dLLMs) introduces unprecedented vulnerabilities that are fundamentally distinct from Autoregressive LLMs, stemming from th…
Position: LLMs Can be Good Tutors in English Education
Jingheng Ye, Shen Wang, Deqing Zou +8
While recent efforts have begun integrating large language models (LLMs) into English education, they often rely on traditional approaches to learning tasks without fully embracing…
Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning
Yibo Yan, Shen Wang, Jiahao Huo +7
Scientific reasoning, the process through which humans apply logic, evidence, and critical thinking to explore and interpret scientific phenomena, is essential in advancing knowled…
A Survey of Mathematical Reasoning in the Era of Multimodal Large Language Model: Benchmark, Method & Challenges
Yibo Yan, Jiamin Su, Jianxiang He +7
Mathematical reasoning, a core aspect of human cognition, is vital across many domains, from educational problem-solving to scientific advancements. As artificial general intellige…
ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection
Yibo Yan, Shen Wang, Jiahao Huo +13
As the field of Multimodal Large Language Models (MLLMs) continues to evolve, their potential to revolutionize artificial intelligence is particularly promising, especially in addr…