10 citations · 13 across the 7 of their papers we have counts for
7 papers
Synthetic Hallucinations, Real Gains: Hard Negatives from Frontier Models for FIM Hallucination Mitigation
Mahdi Erfanian, Nelson Daniel Troncoso, Aashna Garg +4
Small open-source code models that power IDE autocomplete still emit hallucinated Fill-in-the-Middle (FIM) completions: syntactically natural calls to methods, parameters, variable…
Delulu: A Verified Multi-Lingual Benchmark for Code Hallucination Detection in Fill-in-the-Middle Tasks
Mahdi Erfanian, Nelson Daniel Troncoso, Aashna Garg +4
Large Language Models for code generation frequently produce hallucinations in Fill-in-the-Middle (FIM) tasks -- plausible but incorrect completions such as invented API methods, i…
DevBench: A Realistic, Developer-Informed Benchmark for Code Generation Models
Adarsh Kumarappan, Pareesa Ameneh Golnari, Wen Wen +5
DevBench is a telemetry-driven benchmark designed to evaluate Large Language Models (LLMs) on realistic code completion tasks. It includes 1,800 evaluation instances across six pro…
LoRA-Enhanced Distillation on Guided Diffusion Models
Pareesa Ameneh Golnari
Diffusion models, such as Stable Diffusion (SD), offer the ability to generate high-resolution images with diverse features, but they come at a significant computational and memory…
RenAIssance: A Survey into AI Text-to-Image Generation in the Era of Large Model
Fengxiang Bie, Yibo Yang, Zhongzhu Zhou +10
Text-to-image generation (TTI) refers to the usage of models that could process text input and generate high fidelity images based on text descriptions. Text-to-image generation us…
Selective Guidance: Are All the Denoising Steps of Guided Diffusion Important?
Pareesa Ameneh Golnari, Zhewei Yao, Yuxiong He
This study examines the impact of optimizing the Stable Diffusion (SD) guided inference pipeline. We propose optimizing certain denoising steps by limiting the noise computation to…
Sparse Matrix to Matrix Multiplication: A Representation and Architecture for Acceleration (long version)
Pareesa Ameneh Golnari, Sharad Malik
Accelerators for sparse matrix multiplication are important components in emerging systems. In this paper, we study the main challenges of accelerating Sparse Matrix Multiplication…