1 citations · 1 across the 4 of their papers we have counts for
5 papers
Concise Reasoning in the Lens of Lagrangian Optimization
Chengqian Gao, Haonan Li, Taylor W. Killian +6
Concise reasoning in large language models seeks to generate only essential intermediate steps needed to arrive at a final answer, thereby alleviating issues of overthinking. Most…
Human Texts Are Outliers: Detecting LLM-generated Texts via Out-of-distribution Detection
Cong Zeng, Shengkun Tang, Yuanzhou Chen +6
The rapid advancement of large language models (LLMs) such as ChatGPT, DeepSeek, and Claude has significantly increased the presence of AI-generated text in digital communication.…
Pastiche Novel Generation Creating: Fan Fiction You Love in Your Favorite Author's Style
Xueran Han, Yuhan Liu, Mingzhe Li +5
Great novels create immersive worlds with rich character arcs, well-structured plots, and nuanced writing styles. However, current novel generation methods often rely on brief, sim…
Visual Question Decomposition on Multimodal Large Language Models
Haowei Zhang, Jianzhe Liu, Zhen Han +5
Question decomposition has emerged as an effective strategy for prompting Large Language Models (LLMs) to answer complex questions. However, while existing methods primarily focus…
DALD: Improving Logits-based Detector without Logits from Black-box LLMs
Cong Zeng, Shengkun Tang, Xianjun Yang +7
The advent of Large Language Models (LLMs) has revolutionized text generation, producing outputs that closely mimic human writing. This blurring of lines between machine- and human…