10 citations · 11 across the 7 of their papers we have counts for
7 papers
Universal Transformers for Circuit Computations: Perfect Length Generalization in Tiny Transformers
Takuya Ito, Ruchir Puri, Murray Campbell +1
Learning generalizable algorithmic computations remains a challenge for neural networks, as reflected in persistent failures on compositional and length generalization benchmarks.…
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…
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…
Customizing a Large Language Model for VHDL Design of High-Performance Microprocessors
Nicolas Dupuis, Ravi Nair, Shyam Ramji +7
The use of Large Language Models (LLMs) in hardware design has taken off in recent years, principally through its incorporation in tools that increase chip designer productivity. T…
Qiskit HumanEval: An Evaluation Benchmark For Quantum Code Generative Models
Sanjay Vishwakarma, Francis Harkins, Siddharth Golecha +7
Quantum programs are typically developed using quantum Software Development Kits (SDKs). The rapid advancement of quantum computing necessitates new tools to streamline this develo…
Qiskit Code Assistant: Training LLMs for generating Quantum Computing Code
Nicolas Dupuis, Luca Buratti, Sanjay Vishwakarma +5
Code Large Language Models (Code LLMs) have emerged as powerful tools, revolutionizing the software development landscape by automating the coding process and reducing time and eff…
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…