activity
20242026
most citedA Comparative Analysis of LLM Memorization at Statistical and Internal Levels: Cross-Model Commonalities and Model-Specific Signatures

1 citations · 1 across the 4 of their papers we have counts for

collaborators

6 papers

cs.LG2026

Reward Hacking in the Era of Large Models: Mechanisms, Emergent Misalignment, Challenges

Xiaohua Wang, Muzhao Tian, Yuqi Zeng +20

Reinforcement Learning from Human Feedback (RLHF) and related alignment paradigms have become central to steering large language models (LLMs) and multimodal large language models…

cs.CL20261 cited

A Comparative Analysis of LLM Memorization at Statistical and Internal Levels: Cross-Model Commonalities and Model-Specific Signatures

Bowen Chen, Namgi Han, Yusuke Miyao

Memorization is a fundamental component of intelligence for both humans and LLMs. However, while LLM performance scales rapidly, our understanding of memorization lags. Due to limi…

cs.CL2025

OceanAI: A Conversational Platform for Accurate, Transparent, Near-Real-Time Oceanographic Insights

Bowen Chen, Jayesh Gajbhar, Gregory Dusek +6

Artificial intelligence is transforming the sciences, yet general conversational AI systems often generate unverified "hallucinations" undermining scientific rigor. We present Ocea…

cs.SE2025

Improving Compiler Bug Isolation by Leveraging Large Language Models

Yixian Qi, Jiajun Jiang, Fengjie Li +3

Compilers play a foundational role in building reliable software systems, and bugs within them can lead to catastrophic consequences. The compilation process typically involves hun…

cs.AI2025

TIMER: Temporal Instruction Modeling and Evaluation for Longitudinal Clinical Records

Hejie Cui, Alyssa Unell, Bowen Chen +4

Large language models (LLMs) have emerged as promising tools for assisting in medical tasks, yet processing Electronic Health Records (EHRs) presents unique challenges due to their…

cs.CL2024

A Statistical and Multi-Perspective Revisiting of the Membership Inference Attack in Large Language Models

Bowen Chen, Namgi Han, Yusuke Miyao

The lack of data transparency in Large Language Models (LLMs) has highlighted the importance of Membership Inference Attack (MIA), which differentiates trained (member) and untrain…