Papers with GG

2 papers
Guided by Gut: Efficient Test-Time Scaling with Reinforced Intrinsic Confidence (2026.acl-long)

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Challenge: Guided by Gut (GG) is an efficient self-guided TTS framework for Large Language Models (LLMs) that performs step-by-step reasoning at a low cost without any reward models or verifiers.
Approach: They propose a self-guided TTS framework that enables LLMs to perform step-by-step reasoning at a low cost without any reward models or verifiers.
Outcome: Empirical evaluations show that GG performs better than TTS with PRMs while reducing GPU memory usage by up to 10.
Guaranteed Guess: A Language Modeling Approach for CISC-to-RISC Transpilation with Testing Guarantees (2025.findings-emnlp)

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Challenge: ISA-centric transpilation pipelines are used to translate low-level programs between ISAs . GG provides high code coverage across unit tests and better energy efficiency .
Approach: They propose a ISA-centric transpilation pipeline that embeds large language models into software testing frameworks to ensure accuracy.
Outcome: The proposed method achieves high code coverage across unit tests and functional/semantic correctness of 99% on HumanEval and 49% on BringupBench programs.

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