1 citations · 1 across the 11 of their papers we have counts for
4 papers · 1 filter
The Prompt is Mightier than the Example
Shengzhe Xu, Nikhil Muralidhar, Naren Ramakrishnan
Numerous recent prompt optimization approaches like chain-of-thought, have been demonstrated to significantly improve the quality of content generated by large language models (LLM…
Optimizing Product Provenance Verification using Data Valuation Methods
Raquib Bin Yousuf, Hoang Anh Just, Shengzhe Xu +8
Determining and verifying product provenance remains a critical challenge in global supply chains, particularly as geopolitical conflicts and shifting borders create new incentives…
Why LLMs Are Bad at Synthetic Table Generation (and what to do about it)
Shengzhe Xu, Cho-Ting Lee, Mandar Sharma +3
Synthetic data generation is integral to ML pipelines, e.g., to augment training data, replace sensitive information, and even to power advanced platforms like DeepSeek. While LLMs…
STAN: Synthetic Network Traffic Generation with Generative Neural Models
Shengzhe Xu, Manish Marwah, Martin Arlitt +1
Deep learning models have achieved great success in recent years but progress in some domains like cybersecurity is stymied due to a paucity of realistic datasets. Organizations ar…