7 papers
Assessing the Impact of Code Changes on the Fault Localizability of Large Language Models
Sabaat Haroon, Ahmad Faraz Khan, Ahmad Humayun +5
Generative Large Language Models (LLMs) are increasingly used in non-generative software maintenance tasks, such as fault localization (FL). Success in FL depends on a models abili…
BinaryShield: Cross-Service Threat Intelligence in LLM Services using Privacy-Preserving Fingerprints
Waris Gill, Natalie Isak, Matthew Dressman
The widespread deployment of LLMs across enterprise services has created a critical security blind spot. Organizations operate multiple LLM services handling billions of queries da…
ProToken: Token-Level Attribution for Federated Large Language Models
Waris Gill, Ahmad Humayun, Ali Anwar +1
Federated Learning (FL) enables collaborative training of Large Language Models (LLMs) across distributed data sources while preserving privacy. However, when federated LLMs are de…
Are the Majority of Public Computational Notebooks Pathologically Non-Executable?
Tien Nguyen, Waris Gill, Muhammad Ali Gulzar
Computational notebooks are the de facto platforms for exploratory data science, offering an interactive programming environment where users can create, modify, and execute code ce…
Advancing Semantic Caching for LLMs with Domain-Specific Embeddings and Synthetic Data
Waris Gill, Justin Cechmanek, Tyler Hutcherson +5
This report investigates enhancing semantic caching effectiveness by employing specialized, fine-tuned embedding models. Semantic caching relies on embedding similarity rather than…
MeanCache: User-Centric Semantic Caching for LLM Web Services
Waris Gill, Mohamed Elidrisi, Pallavi Kalapatapu +3
Large Language Models (LLMs) like ChatGPT and Llama have revolutionized natural language processing and search engine dynamics. However, these models incur exceptionally high compu…