4 papers
LLM Ghostbusters: Surgical Package Hallucination Suppression via Adaptive Unlearning
Joseph Spracklen, Pedram Aghazadeh, Farinaz Koushanfar +1
Hallucinations remain an unsolved problem for LLMs, and package hallucinations are a particularly dangerous instance of this phenomenon. Package hallucinations occur during code ge…
Beyond Perplexity: A Lightweight Benchmark for Knowledge Retention in Supervised Fine-Tuning
Soheil Zibakhsh Shabgahi, Pedram Aghazadeh, Farinaz Koushanfar
Supervised Fine-Tuning (SFT) is a standard approach for injecting domain knowledge into Large Language Models (LLMs). However, relying on validation perplexity to monitor training…
ForTIFAI: Fending Off Recursive Training Induced Failure for AI Model Collapse
Soheil Zibakhsh Shabgahi, Pedram Aghazadeh, Azalia Mirhoseini +1
The increasing reliance on generative AI models is rapidly increasing the volume of synthetic data, with some projections suggesting that most available new data for training could…
SwapTransformer: highway overtaking tactical planner model via imitation learning on OSHA dataset
Alireza Shamsoshoara, Safin B Salih, Pedram Aghazadeh
This paper investigates the high-level decision-making problem in highway scenarios regarding lane changing and over-taking other slower vehicles. In particular, this paper aims to…