12 citations · 15 across the 6 of their papers we have counts for
7 papers
Test-Time Scaling of Diffusion Models via Noise Trajectory Search
Vignav Ramesh, Morteza Mardani
The iterative and stochastic nature of diffusion models enables test-time scaling, whereby spending additional compute during denoising generates higher-fidelity samples. Increasin…
Communicating Activations Between Language Model Agents
Vignav Ramesh, Kenneth Li
Communication between multiple language model (LM) agents has been shown to scale up the reasoning ability of LMs. While natural language has been the dominant medium for inter-LM…
Improving Radiology Report Generation Systems by Removing Hallucinated References to Non-existent Priors
Vignav Ramesh, Nathan Andrew Chi, Pranav Rajpurkar
Current deep learning models trained to generate radiology reports from chest radiographs are capable of producing clinically accurate, clear, and actionable text that can advance…
Contrastive learning-based pretraining improves representation and transferability of diabetic retinopathy classification models
Minhaj Nur Alam, Rikiya Yamashita, Vignav Ramesh +6
Self supervised contrastive learning based pretraining allows development of robust and generalized deep learning models with small, labeled datasets, reducing the burden of label…
Unsupervised Tokenization Learning
Anton Kolonin, Vignav Ramesh
In the presented study, we discover that the so-called "transition freedom" metric appears superior for unsupervised tokenization purposes in comparison to statistical metrics such…
End-to-end Malaria Diagnosis and 3D Cell Rendering with Deep Learning
Vignav Ramesh
Malaria is a parasitic infection that poses a significant burden on global health. It kills one child every 30 seconds and over one million people annually. If diagnosed in a timel…
Natural Language Generation Using Link Grammar for General Conversational Intelligence
Vignav Ramesh, Anton Kolonin
Many current artificial general intelligence (AGI) and natural language processing (NLP) architectures do not possess general conversational intelligence--that is, they either do n…