Papers with PolyBench

2 papers
Benchmarking for Domain-Specific LLMs: A Case Study on Academia and Beyond (2025.findings-emnlp)

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Challenge: Comp-Comp is an iterative benchmarking framework grounded in the principles of comprehensiveness and compactness.
Approach: They propose a benchmark framework that incorporates the principle of comprehensiveness and compactness.
Outcome: The proposed framework is domain-agnostic and adaptable to a wide range of specialized fields.
HintPilot: LLM-based Compiler Hint Synthesis for Code Optimization (2026.findings-acl)

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Challenge: Existing methods to optimize source code rely on invasive transformations that can introduce semantic errors and miss fine-grained compiler-level optimization opportunities.
Approach: They propose a method that bridges LLM-based reasoning with traditional compilers by synthesizing compiler hints.
Outcome: HintPilot achieves 6.88x speedup over -Ofast while preserving program correctness.

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