6 papers
TSGuard: Automated User-Centric Incident Diagnosis for AI Workloads in the Cloud
Yitao Yang, Yangtao Deng, Yifan Xiong +3
AI workloads incur frequent failures and incidents from the underlying infrastructure. The current incident management workflow follows a provider-centric paradigm, where users rep…
rSIM: Incentivizing Reasoning Capabilities of LLMs via Reinforced Strategy Injection
Sijia Chen, Baochun Li, Di Niu
Large language models (LLMs) are post-trained through reinforcement learning (RL) to evolve into Reasoning Language Models (RLMs), where the hallmark of this advanced reasoning is…
TokenMark: A Modality-Agnostic Watermark for Pre-trained Transformers
Hengyuan Xu, Liyao Xiang, Borui Yang +3
Watermarking is a critical tool for model ownership verification. However, existing watermarking techniques are often designed for specific data modalities and downstream tasks, wi…
Boosting of Thoughts: Trial-and-Error Problem Solving with Large Language Models
Sijia Chen, Baochun Li, Di Niu
The reasoning performance of Large Language Models (LLMs) on a wide range of problems critically relies on chain-of-thought prompting, which involves providing a few chain of thoug…
Calibre: Towards Fair and Accurate Personalized Federated Learning with Self-Supervised Learning
Sijia Chen, Ningxin Su, Baochun Li
In the context of personalized federated learning, existing approaches train a global model to extract transferable representations, based on which any client could train personali…
Toward Adaptive Reasoning in Large Language Models with Thought Rollback
Sijia Chen, Baochun Li
Large language models (LLMs) have been routinely used to solve various tasks using step-by-step reasoning. However, the structure of intermediate reasoning steps, or thoughts, is r…