collaborators

5 papers

cs.SE2026

Spec Kit Agents: Context-Grounded Agentic Workflows

Pardis Taghavi, Santosh Bhavani

Spec-driven development (SDD) with AI coding agents provides a structured workflow, but agents often remain "context blind" in large, evolving repositories, leading to hallucinated…

cs.CV2026

Training a Student Expert via Semi-Supervised Foundation Model Distillation

Pardis Taghavi, Tian Liu, Renjie Li +2

Foundation models deliver strong perception but are often too computationally heavy to deploy, and adapting them typically requires costly annotations. We introduce a semi-supervis…

cs.CV2026

The Pulse of Motion: Measuring Physical Frame Rate from Visual Dynamics

Xiangbo Gao, Mingyang Wu, Siyuan Yang +4

While recent generative video models have achieved remarkable visual realism and are being explored as world models, true physical simulation requires mastering both space and time…

cs.RO2026

NaviDriveVLM: Decoupling High-Level Reasoning and Motion Planning for Autonomous Driving

Ximeng Tao, Pardis Taghavi, Dimitar Filev +2

Vision-language models (VLMs) have emerged as a promising direction for end-to-end autonomous driving (AD) by jointly modeling visual observations, driving context, and language-ba…

cs.CV2025

CAST: Contrastive Adaptation and Distillation for Semi-Supervised Instance Segmentation

Pardis Taghavi, Tian Liu, Renjie Li +2

Instance segmentation demands costly per-pixel annotations and computationally expensive models. We introduce CAST, a semi-supervised knowledge distillation (SSKD) framework that c…