- Releq: A reinforcement learning approach for deep quantization of neural networks [paper]
- Compiler optimizations for parallel programs [paper]
- Optimization of halide image processing schedules with reinforcement learning [paper]
- Reinforcement learning and adaptive sampling for optimized dnn compilation [paper]
- Poset-rl: Phase ordering for optimizing size and execution time using reinforcement learning [paper]
- Neurovectorizer: End-to-end vectorization with deep reinforcement learning [paper]
- Reinforced genetic algorithm learning for optimizing computation graphs [paper]
- A view on deep reinforcement learning in system optimization [paper]
- Reinforcement learning strategies for compiler optimization in high level synthesis [paper]
- Reinforcement Learning and Adaptive Sampling for Optimized DNN Compilation [paper]
- Chameleon: Adaptive code optimization for expedited deep neural network compilation [paper]
- A reinforcement learning environment for polyhedral optimizations [paper]
- Automating reinforcement learning architecture design for code optimization [paper]
- AutoPhase: Compiler Phase-Ordering for HLS with Deep Reinforcement Learning [paper]
- Static Neural Compiler Optimization via Deep Reinforcement Learning [paper]
- Reinforced genetic algorithm learning for optimizing computation graphs [paper]
- ConfuciuX: Autonomous Hardware Resource Assignment for DNN Accelerators using Reinforcement Learning [paper]
- Bansor: Improving Tensor Program Auto-Scheduling with Bandit Based Reinforcement Learning [paper]
- MLGO: a Machine Learning Guided Compiler Optimizations Framework [paper]
- A Reinforcement Learning Environment for Polyhedral Optimizations [paper]
- Large language models meet nl2code: A survey [paper]
- Solving pbqp-based register allocation using deep reinforcement learning [paper]
- Compilergym: Robust, performant compiler optimization environments for ai research [paper]
- CodeRL: Mastering code generation through pretrained models and deep reinforcement learning [paper]
- Target-independent XLA optimization using Reinforcement Learning [paper]
- Towards intelligent compiler optimization [paper]
- Autophase V2: Towards Function Level Phase Ordering Optimization [paper]
- Profile-Guided Optimization for Function Reordering: A Reinforcement Learning Approach [paper]
- POSET-RL: Phase ordering for Optimizing Size and Execution Time using Reinforcement Learning [paper]
- Optimizing LLVM Pass List using Reinforcement Learning [paper]
- Reinforcement Learning Strategies for Compiler Optimization in High level Synthesis [paper]
- A Motivating Case Study on Code Variant Selection by Reinforcement Learning [paper]
- Compilable Neural Code Generation with Compiler Feedback [paper]
- A survey on language models for code [paper]
- PanGu-Coder2: Boosting Large Language Models for Code with Ranking Feedback [paper]
- Execution-based code generation using deep reinforcement learning [paper]
- Rl4real: Reinforcement learning for register allocation [paper]
- The role of Reinforcement Learning in software testing [paper]
- CodeT5+: Open Code Large Language Models for Code Understanding and Generation [paper]
- Learning Compiler Pass Orders using Coreset and Normalized Value Prediction [paper]
- RLTF: Reinforcement Learning from Unit Test Feedback [paper]
- Automatic Unit Test Data Generation and Actor-Critic Reinforcement Learning for Code Synthesis [paper]
- A survey of neural code intelligence: Paradigms, advances and beyond [paper]
- A Survey on Large Language Models for Code Generation [paper]
- SEED: Customize Large Language Models with Sample-Efficient Adaptation for Code Generation [paper]
- Unlock the Correlation between Supervised Fine-Tuning and Reinforcement Learning in Training Code Large Language Models [paper]
- Improving domain-specific neural code generation with few-shot meta-learning [paper]
- A Reinforcement Learning Environment for Automatic Code Optimization in the MLIR Compiler [paper]
- B-Coder: Value-Based Deep Reinforcement Learning for Program Synthesis [paper]
- Continual Multi-Objective Reinforcement Learning via Reward Model Rehearsal [paper]
- StepCoder: Improve Code Generation with Reinforcement Learning from Compiler Feedback [paper]
- Performance-Aligned LLMs for Generating Fast Code [paper]
- Measuring memorization in RLHF for code completion [paper]
- Applying RLAIF for Code Generation with API-usage in Lightweight LLMs [paper]
- Compiler Generated Feedback for Large Language Models [paper]
- Iterative Refinement of Project-Level Code Context for Precise Code Generation with Compiler Feedback [paper]
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