9 papers
Triospect: A Three-Dimensional Framework for Robust Statistical AI-Generated Text Detection Against Diverse Attacks
Guangsheng Bao, Lihua Rong, Yanbin Zhao +3
Existing AI-generated text detectors are vulnerable to attacks that manipulate textual characteristics. In this study, we propose a novel Triospect Detection Framework by using add…
Thinking as Compression: Your Reasoning Model is Secretly a Context Compressor
Guoxin Ma, Yibing Liu, Chengzhengxu Li +7
Context compression aims to shorten long context inputs with minimal information loss for LLM inference acceleration. While existing methods have shown promise, they typically rely…
Active Evidence-Seeking and Diagnostic Reasoning in Large Language Models for Clinical Decision Support
Chen Zhan, Xihe Qiu, Xiaoyu Tan +8
Large language models perform well on static medical examinations, yet clinical diagnosis often requires iterative evidence gathering under uncertainty. Building on prior interacti…
AiraXiv: An AI-Driven Open-Access Platform for Human and AI Scientists
Junshu Pan, Panzhong Lu, Yixuan Weng +5
Recent advances in artificial intelligence (AI) have accelerated the growth of both human-authored and AI-generated research outputs, placing increasing strain on traditional acade…
On the Cost and Benefit of Chain of Thought: A Learning-Theoretic Perspective
Yue Zhang, Zhiyi Dong, Tommaso Cesari +1
We develop a learning-theoretic framework for understanding Chain of Thought (CoT). We model CoT as the interaction between an answer map and a chain rule that generates intermedia…
Pre-DPO: Improving Data Utilization in Direct Preference Optimization Using a Guiding Reference Model
Junshu Pan, Wei Shen, Shulin Huang +2
Direct Preference Optimization (DPO) simplifies reinforcement learning from human feedback (RLHF) for large language models (LLMs) by directly optimizing human preferences without…