3 papers
cs.LG2026
KForge: LLM-Driven Cross-Platform Kernel Generation for AI Accelerators
Taras Sereda, Burak Bartan, Ankita Nayak +3
Production inference increasingly targets a heterogeneous mix of accelerators. Agentic pipelines interleave reasoning, tool calls, and multi-agent coordination, each with distinct…
cs.LG2025
KForge: Program Synthesis for Diverse AI Hardware Accelerators
Taras Sereda, Tom St. John, Burak Bartan +3
GPU kernels are critical for ML performance but difficult to optimize across diverse accelerators. We present KForge, a platform-agnostic framework built on two collaborative LLM-b…
eess.AS2024
Transcribe, Align and Segment: Creating speech datasets for low-resource languages
Taras Sereda
In this work, we showcase a cost-effective method for generating training data for speech processing tasks. First, we transcribe unlabeled speech using a state-of-the-art Automatic…