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cs.AI2026
Agent Factories for High Level Synthesis: How Far Can General-Purpose Coding Agents Go in Hardware Optimization?
Abhishek Bhandwaldar, Mihir Choudhury, Ruchir Puri +1
We present an empirical study of how far general-purpose coding agents -- without hardware-specific training -- can optimize hardware designs from high-level algorithmic specificat…
cs.AI2026
Think Locally, Explain Globally: Graph-Guided LLM Investigations via Local Reasoning and Belief Propagation
Saurabh Jha, Rohan Arora, Bhavya +7
LLM agents excel when environments are mostly static and the needed information fits in a model's context window, but they often fail in open-ended investigations where explanation…
cs.AI2024
Granite Code Models: A Family of Open Foundation Models for Code Intelligence
Mayank Mishra, Matt Stallone, Gaoyuan Zhang +43
Large Language Models (LLMs) trained on code are revolutionizing the software development process. Increasingly, code LLMs are being integrated into software development environmen…