2 citations · 3 across the 11 of their papers we have counts for
11 papers
CPPO: Contrastive Perception Policy Optimization for VLM Agents
Ahmad Rezaei, Mohsen Gholami, Saeed Ranjbar Alvar +5
We introduce CPPO, a Contrastive Perception Policy Optimization method for finetuning vision--language models (VLMs). Reliable perception is a core requirement for VLM-based agents…
From Segments to Scenes: Temporal Understanding for Agentic Autonomous Driving via Vision-Language Models
Kevin Cannons, Saeed Ranjbar Alvar, Mohammad Asiful Hossain +6
Vision-Language Models (VLMs) are increasingly deployed as the perception and reasoning backbone of autonomous agents acting in the wild, with autonomous driving (AD) being one of…
Spatial Reasoning with Vision-Language Models in Ego-Centric Multi-View Scenes
Mohsen Gholami, Ahmad Rezaei, Zhou Weimin +4
Understanding 3D spatial relationships remains a major limitation of current Vision-Language Models (VLMs). Prior work has addressed this issue by creating spatial question-answeri…
DivPrune: Diversity-based Visual Token Pruning for Large Multimodal Models
Saeed Ranjbar Alvar, Gursimran Singh, Mohammad Akbari +1
Large Multimodal Models (LMMs) have emerged as powerful models capable of understanding various data modalities, including text, images, and videos. LMMs encode both text and visua…
CASP: Compression of Large Multimodal Models Based on Attention Sparsity
Mohsen Gholami, Mohammad Akbari, Kevin Cannons +1
In this work, we propose an extreme compression technique for Large Multimodal Models (LMMs). While previous studies have explored quantization as an efficient post-training compre…
Task-Agnostic Language Model Watermarking via High Entropy Passthrough Layers
Vaden Masrani, Mohammad Akbari, David Ming Xuan Yue +2
In the era of costly pre-training of large language models, ensuring the intellectual property rights of model owners, and insuring that said models are responsibly deployed, is be…
Towards Secure and Usable 3D Assets: A Novel Framework for Automatic Visible Watermarking
Gursimran Singh, Tianxi Hu, Mohammad Akbari +2
3D models, particularly AI-generated ones, have witnessed a recent surge across various industries such as entertainment. Hence, there is an alarming need to protect the intellectu…
LaWa: Using Latent Space for In-Generation Image Watermarking
Ahmad Rezaei, Mohammad Akbari, Saeed Ranjbar Alvar +2
With generative models producing high quality images that are indistinguishable from real ones, there is growing concern regarding the malicious usage of AI-generated images. Imper…
GOLD: Generalized Knowledge Distillation via Out-of-Distribution-Guided Language Data Generation
Mohsen Gholami, Mohammad Akbari, Cindy Hu +3
Knowledge distillation from LLMs is essential for the efficient deployment of language models. Prior works have proposed data generation using LLMs for preparing distilled models.…
AMUSE: Adaptive Multi-Segment Encoding for Dataset Watermarking
Saeed Ranjbar Alvar, Mohammad Akbari, David Ming Xuan Yue +1
Curating high quality datasets that play a key role in the emergence of new AI applications requires considerable time, money, and computational resources. So, effective ownership…
ArchBERT: Bi-Modal Understanding of Neural Architectures and Natural Languages
Mohammad Akbari, Saeed Ranjbar Alvar, Behnam Kamranian +2
Building multi-modal language models has been a trend in the recent years, where additional modalities such as image, video, speech, etc. are jointly learned along with natural lan…