8 citations · 10 across the 5 of their papers we have counts for
6 papers
TorchTPU - A Hybrid Eager/Compiled Architecture for Native PyTorch Execution on TPU
Claudio Basile, Michael Voznesensky, Gunhyun Park +50
TorchTPU is an open-source collaboration between Google and Meta that introduces a native and principled PyTorch backend for Google TPUs. It enables seamless out-of-the-box model e…
State-of-the-art Small Language Coder Model: Mify-Coder
Abhinav Parmar, Abhisek Panigrahi, Abhishek Kumar Dwivedi +93
We present Mify-Coder, a 2.5B-parameter code model trained on 4.2T tokens using a compute-optimal strategy built on the Mify-2.5B foundation model. Mify-Coder achieves comparable a…
PLUTO-4: Frontier Pathology Foundation Models
Harshith Padigela, Shima Nofallah, Atchuth Naveen Chilaparasetti +11
Foundation models trained on large-scale pathology image corpora have demonstrated strong transfer capabilities across diverse histopathology tasks. Building on this progress, we i…
ML-Dev-Bench: Comparative Analysis of AI Agents on ML development workflows
Harshith Padigela, Chintan Shah, Dinkar Juyal
In this report, we present ML-Dev-Bench, a benchmark aimed at testing agentic capabilities on applied Machine Learning development tasks. While existing benchmarks focus on isolate…
Learning biologically relevant features in a pathology foundation model using sparse autoencoders
Nhat Minh Le, Ciyue Shen, Neel Patel +13
Pathology plays an important role in disease diagnosis, treatment decision-making and drug development. Previous works on interpretability for machine learning models on pathology…
PLUTO: Pathology-Universal Transformer
Dinkar Juyal, Harshith Padigela, Chintan Shah +30
Pathology is the study of microscopic inspection of tissue, and a pathology diagnosis is often the medical gold standard to diagnose disease. Pathology images provide a unique chal…