#compiler-feedback News & Analysis

4 articles tagged with #compiler-feedback. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

4 articles

AIBullisharXiv – CS AI · Jun 117/10

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TAHOE: Text-to-SQL with Automated Hint Optimization from Experience

Researchers introduce Tahoe, a system that optimizes LLM-based Text-to-SQL conversion through dynamic prompt engineering rather than model retraining. By consolidating debugging traces into reusable hints and modeling conflicting user intents as strategies, Tahoe increases query pass rates from 62% to 79% on Spider 2.0-Snow benchmarks while maintaining compatibility across weaker model backbones.

🧠 GPT-5

AIBullisharXiv – CS AI · Jun 57/10

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Beyond Code Pairs: Dialogue-Based Data Generation for LLM Code Translation

Researchers have developed an automated pipeline using dual-LLM agents to generate high-quality training data for code translation tasks, particularly in low-resource languages like Fortran and CUDA. The approach produces verified translations with unit tests and multi-turn dialogue datasets, enabling a 7B model to outperform larger proprietary systems with over 56% improvement in functional correctness on C++-to-CUDA translation.

AIBullisharXiv – CS AI · May 17/10

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SpatialGrammar: A Domain-Specific Language for LLM-Based 3D Indoor Scene Generation

Researchers introduce SpatialGrammar, a domain-specific language designed to improve LLM-based 3D indoor scene generation by representing layouts as bird's-eye-view grid placements with compiler validation. The approach, paired with SG-Agent (an iterative refinement system) and SG-Mini (a 104M-parameter model), significantly reduces spatial errors and collision issues that plague existing natural language-to-3D scene generation methods.

AINeutralarXiv – CS AI · May 296/10

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Grammar-Aware Literate Generative Mathematical Programming with Compiler-in-the-Loop

Researchers introduce SyntAGM, an AI system that generates mathematical optimization models in readable algebraic language rather than general-purpose code. The system uses a compiler-in-the-loop approach with iterative feedback to improve model accuracy, achieving better cost-quality trade-offs than existing language model baselines.