6 citations · 9 across the 10 of their papers we have counts for
10 papers
SARLO-80: Worldwide Slant SAR Language Optic Dataset 80cm
Solène Debuysère, Nicolas Trouvé, Nathan Letheule +2
Multimodal foundation models have advanced rapidly thanks to large optical benchmarks, but comparable resources for synthetic aperture radar (SAR) remain limited. Existing SAR--opt…
Building Reliable Long-Form Generation via Hallucination Rejection Sampling
Lin Li, Georgia Channing, Suhaas M Bhat +2
Large language models (LLMs) have achieved remarkable progress in open-ended text generation, yet they remain prone to hallucinating incorrect or unsupported content, which undermi…
Contrastive Image-Metadata Pre-Training for Materials Transmission Electron Microscopy
Georgia Channing, Debora Keller, Marta D. Rossell +3
The transmission electron microscope facilitates the highest-resolution imaging of any instrument ever created, and its limiting factor is no longer spatial resolution but dose eff…
LeMat-GenBench: A Unified Evaluation Framework for Crystal Generative Models
Siddharth Betala, Samuel P. Gleason, Ali Ramlaoui +12
Generative machine learning (ML) models hold great promise for accelerating materials discovery through the inverse design of inorganic crystals, enabling an unprecedented explorat…
LeMat-Synth: a multi-modal toolbox to curate broad synthesis procedure databases from scientific literature
Magdalena Lederbauer, Siddharth Betala, Valerie Gentzke +22
Wide access to advanced experimental methods in materials science has given rise to an abundance of procedural knowledge, which is scattered across decades of scientific literature…
AI for Scientific Discovery is a Social Problem
Georgia Channing, Avijit Ghosh
Artificial intelligence (AI) is being increasingly applied to scientific research, but its benefits remain unevenly distributed across different communities and disciplines. While…
Fact-Checking with Contextual Narratives: Leveraging Retrieval-Augmented LLMs for Social Media Analysis
Arka Ujjal Dey, Muhammad Junaid Awan, Georgia Channing +2
We propose CRAVE (Cluster-based Retrieval Augmented Verification with Explanation); a novel framework that integrates retrieval-augmented Large Language Models (LLMs) with clusteri…
PSyDUCK: Training-Free Steganography for Latent Diffusion
Aqib Mahfuz, Georgia Channing, Mark van der Wilk +3
Recent advances in generative AI have opened promising avenues for steganography, which can securely protect sensitive information for individuals operating in hostile environments…
Toward Robust Real-World Audio Deepfake Detection: Closing the Explainability Gap
Georgia Channing, Juil Sock, Ronald Clark +2
The rapid proliferation of AI-manipulated or generated audio deepfakes poses serious challenges to media integrity and election security. Current AI-driven detection solutions lack…
MAD-Sherlock: Multi-Agent Debate for Visual Misinformation Detection
Kumud Lakara, Georgia Channing, Christian Rupprecht +4
One of the most challenging forms of misinformation involves pairing images with misleading text to create false narratives. Existing AI-driven detection systems often require doma…