Cover Image

A Deep Learning Model for Predicting Transformation Legality

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Tiwari, Avani, Hakimi, Yacine, Baghdadi, Riyadh
Format:	Preprint
Published:	2025
Subjects:	Programming Languages Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Data-driven Analysis of Code Optimizations
by: Hakimi, Yacine, et al.
Published: (2025)

Data-efficient Performance Modeling via Pre-training
by: Liu, Chunting, et al.
Published: (2025)

Automatic Generation of Python Programs Using Context-Free Grammars
by: Yamani, Kamel, et al.
Published: (2024)

LOOPerSet: A Large-Scale Dataset for Data-Driven Polyhedral Compiler Optimization
by: Merouani, Massinissa, et al.
Published: (2025)

Curriculum Learning for Small Code Language Models
by: Naïr, Marwa, et al.
Published: (2024)

Combining Neural Architecture Search and Automatic Code Optimization: A Survey
by: Bachiri, Inas, et al.
Published: (2024)

Agentic Auto-Scheduling: An Experimental Study of LLM-Guided Loop Optimization
by: Merouani, Massinissa, et al.
Published: (2025)

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning
by: Lamouri, Djamel Rassem, et al.
Published: (2025)

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers
by: Merouani, Massinissa, et al.
Published: (2024)

Neural Architecture Search with Mixed Bio-inspired Learning Rules
by: Hamzaoui, Imane, et al.
Published: (2025)

Exploring the Knowledge Mismatch Hypothesis: Hallucination Propensity in Small Models Fine-tuned on Data from Larger Models
by: Wee, Phil, et al.
Published: (2024)

Sign-Symmetry Learning Rules are Robust Fine-Tuners
by: Berriche, Aymene, et al.
Published: (2025)

Dependence-Driven, Scalable Quantum Circuit Mapping with Affine Abstractions
by: Benbetka, Marouane, et al.
Published: (2025)

TocBERT: Medical Document Structure Extraction Using Bidirectional Transformers
by: Saleh, Majd, et al.
Published: (2024)

Transformers for Program Termination
by: Alon, Yoav, et al.
Published: (2026)

QiMeng-Xpiler: Transcompiling Tensor Programs for Deep Learning Systems with a Neural-Symbolic Approach
by: Dong, Shouyang, et al.
Published: (2025)

Verified Lifting of Deep learning Operators
by: Zhan, Qi, et al.
Published: (2024)

Integrating Large Language Models and Reinforcement Learning for Non-Linear Reasoning
by: Alon, Yoav, et al.
Published: (2024)

CompilerDream: Learning a Compiler World Model for General Code Optimization
by: Deng, Chaoyi, et al.
Published: (2024)

DeepCircuitX: A Comprehensive Repository-Level Dataset for RTL Code Understanding, Generation, and PPA Analysis
by: Li, Zeju, et al.
Published: (2025)

Uncertainty Quantification for Neurosymbolic Programs via Compositional Conformal Prediction
by: Ramalingam, Ramya, et al.
Published: (2024)

AutoPyVerifier: Learning Compact Executable Verifiers for Large Language Model Outputs
by: Pezeshkpour, Pouya, et al.
Published: (2026)

FuseFlow: A Fusion-Centric Compilation Framework for Sparse Deep Learning on Streaming Dataflow
by: Lacouture, Rubens, et al.
Published: (2025)

A Comprehensive Guide to Combining R and Python code for Data Science, Machine Learning and Reinforcement Learning
by: Navarro, Alejandro L. García, et al.
Published: (2024)

Understanding How CodeLLMs (Mis)Predict Types with Activation Steering
by: Lucchetti, Francesca, et al.
Published: (2024)

Is Next Token Prediction Sufficient for GPT? Exploration on Code Logic Comprehension
by: Qi, Mengnan, et al.
Published: (2024)

Scorch: A Library for Sparse Deep Learning
by: Yan, Bobby, et al.
Published: (2024)

Learning Minimal Neural Specifications
by: Geng, Chuqin, et al.
Published: (2024)

Agnostics: Learning to Code in Any Programming Language via Reinforcement with a Universal Learning Environment
by: Boruch-Gruszecki, Aleksander, et al.
Published: (2025)

Linguacodus: A Synergistic Framework for Transformative Code Generation in Machine Learning Pipelines
by: Trofimova, Ekaterina, et al.
Published: (2024)

Learning Structure-Aware Representations of Dependent Types
by: Kogkalidis, Konstantinos, et al.
Published: (2024)

Deep R Programming
by: Gagolewski, Marek
Published: (2022)

Deep Learning and Machine Learning -- Python Data Structures and Mathematics Fundamental: From Theory to Practice
by: Chen, Silin, et al.
Published: (2024)

vLLM Hook v0: A Plug-in for Programming Model Internals on vLLM
by: Ko, Ching-Yun, et al.
Published: (2026)

Verifying Computational Graphs in Production-Grade Distributed Machine Learning Frameworks
by: Zulkifli, Kahfi S., et al.
Published: (2025)

Offline Imitation Learning from Multiple Baselines with Applications to Compiler Optimization
by: Marinov, Teodor V., et al.
Published: (2024)

Emergent Stack Representations in Modeling Counter Languages Using Transformers
by: Tiwari, Utkarsh, et al.
Published: (2025)

Enhancing the Code Reasoning Capabilities of LLMs via Consistency-based Reinforcement Learning
by: Qin, Zhanyue, et al.
Published: (2026)

Type-Constrained Code Generation with Language Models
by: Mündler, Niels, et al.
Published: (2025)

Compiler generated feedback for Large Language Models
by: Grubisic, Dejan, et al.
Published: (2024)