11 citations · 12 across the 12 of their papers we have counts for
6 papers · 1 filter
Generative Representation Learning for Scalable Latent Tokenization
Alan Baade, Kyle Sargent, Vincent Sitzmann +4
We introduce an approach for self-supervised representation learning designed to be used as a tokenizer for generative modeling. Our objective supervises a representation loss by f…
Real-Time Source-Free Object Detection
Sairam VCR, Varun Gopal, Poornima Jain +2
Real-world detectors for autonomous driving, surveillance, and robotics must handle domain-shifts under strict latency and memory constraints, yet existing source-free object detec…
Pixels Don't Lie (But Your Detector Might): Bootstrapping MLLM-as-a-Judge for Trustworthy Deepfake Detection and Reasoning Supervision
Kartik Kuckreja, Parul Gupta, Muhammad Haris Khan +1
Deepfake detection models often generate natural-language explanations, yet their reasoning is frequently ungrounded in visual evidence, limiting reliability. Existing evaluations…
Towards Calibrating Prompt Tuning of Vision-Language Models
Ashshak Sharifdeen, Fahad Shamshad, Muhammad Akhtar Munir +6
Prompt tuning of large-scale vision-language models such as CLIP enables efficient task adaptation without updating model weights. However, it often leads to poor confidence calibr…
OpenEarthAgent: A Unified Framework for Tool-Augmented Geospatial Agents
Akashah Shabbir, Muhammad Umer Sheikh, Muhammad Akhtar Munir +8
Recent progress in multimodal reasoning has enabled agents that interpret imagery, connect it with language, and execute structured analytical tasks. Extending these capabilities t…
DAMASHA: Detecting AI in Mixed Adversarial Texts via Segmentation with Human-interpretable Attribution
L. D. M. S. Sai Teja, N. Siva Gopala Krishna, Ufaq Khan +2
In the age of advanced large language models (LLMs), the boundaries between human and AI-generated text are becoming increasingly blurred. We address the challenge of segmenting mi…