2 citations · 3 across the 4 of their papers we have counts for
4 papers
VeriCoder: Enhancing LLM-Based RTL Code Generation through Functional Correctness Validation
Anjiang Wei, Huanmi Tan, Tarun Suresh +5
Recent advances in Large Language Models (LLMs) have sparked growing interest in applying them to Electronic Design Automation (EDA) tasks, particularly Register Transfer Level (RT…
CodeARC: Benchmarking Reasoning Capabilities of LLM Agents for Inductive Program Synthesis
Anjiang Wei, Tarun Suresh, Jiannan Cao +6
Inductive program synthesis, or programming by example, requires synthesizing functions from input-output examples that generalize to unseen inputs. While large language model agen…
EquiBench: Benchmarking Large Language Models' Reasoning about Program Semantics via Equivalence Checking
Anjiang Wei, Jiannan Cao, Ran Li +8
As large language models (LLMs) become integral to code-related tasks, a central question emerges: Do LLMs truly understand program semantics? We introduce EquiBench, a new benchma…
Improving Parallel Program Performance with LLM Optimizers via Agent-System Interfaces
Anjiang Wei, Allen Nie, Thiago S. F. X. Teixeira +4
Modern scientific discovery increasingly relies on high-performance computing for complex modeling and simulation. A key challenge in improving parallel program performance is effi…