Imagen de Portada

Transformers for Program Termination

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Alon, Yoav, David, Cristina
Formato:	Preprint
Publicado:	2026
Materias:	Programming Languages Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

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

Synthetic Programming Elicitation for Text-to-Code in Very Low-Resource Programming and Formal Languages
por: Mora, Federico, et al.
Publicado: (2024)

RefineStat: Efficient Exploration for Probabilistic Program Synthesis
por: Kanda, Madhav, et al.
Publicado: (2025)

Guided Sketch-Based Program Induction by Search Gradients
por: Amin, Ahmad Ayaz
Publicado: (2024)

Data-driven Verification of Procedural Programs with Integer Arrays
por: Bouajjani, Ahmed, et al.
Publicado: (2025)

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

PolyBlocks: A Compiler Infrastructure for AI Chips and Programming Frameworks
por: Bondhugula, Uday, et al.
Publicado: (2026)

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

ExeDec: Execution Decomposition for Compositional Generalization in Neural Program Synthesis
por: Shi, Kensen, et al.
Publicado: (2023)

Technical Report: Full-Stack Fine-Tuning for the Q Programming Language
por: Hogan, Brendan R., et al.
Publicado: (2025)

A Deep Learning Model for Predicting Transformation Legality
por: Tiwari, Avani, et al.
Publicado: (2025)

Beyond Bayesian Model Averaging over Paths in Probabilistic Programs with Stochastic Support
por: Reichelt, Tim, et al.
Publicado: (2023)

Knowledge Transfer from High-Resource to Low-Resource Programming Languages for Code LLMs
por: Cassano, Federico, et al.
Publicado: (2023)

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

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

Emergent Representations of Program Semantics in Language Models Trained on Programs
por: Jin, Charles, et al.
Publicado: (2023)

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

AIOS Compiler: LLM as Interpreter for Natural Language Programming and Flow Programming of AI Agents
por: Xu, Shuyuan, et al.
Publicado: (2024)

Gradient-Based Program Repair: Fixing Bugs in Continuous Program Spaces
por: Silva, André, et al.
Publicado: (2025)

Program Synthesis using Inductive Logic Programming for the Abstraction and Reasoning Corpus
por: Rocha, Filipe Marinho, et al.
Publicado: (2024)

The Elements of Differentiable Programming
por: Blondel, Mathieu, et al.
Publicado: (2024)

Deep R Programming
por: Gagolewski, Marek
Publicado: (2022)

APPL: A Prompt Programming Language for Harmonious Integration of Programs and Large Language Model Prompts
por: Dong, Honghua, et al.
Publicado: (2024)

EnCompass: Enhancing Agent Programming with Search Over Program Execution Paths
por: Li, Zhening, et al.
Publicado: (2025)

Flex Attention: A Programming Model for Generating Optimized Attention Kernels
por: Dong, Juechu, et al.
Publicado: (2024)

Prism: Symbolic Superoptimization of Tensor Programs
por: Wu, Mengdi, et al.
Publicado: (2026)

Probabilistic Programming with Programmable Variational Inference
por: Becker, McCoy R., et al.
Publicado: (2024)

Exploiting Code Symmetries for Learning Program Semantics
por: Pei, Kexin, et al.
Publicado: (2023)

Quokka: Accelerating Program Verification with LLMs via Invariant Synthesis
por: Wei, Anjiang, et al.
Publicado: (2025)

Allo: A Programming Model for Composable Accelerator Design
por: Chen, Hongzheng, et al.
Publicado: (2024)

Program Semantic Inequivalence Game with Large Language Models
por: Miceli-Barone, Antonio Valerio, et al.
Publicado: (2025)

Generating Pragmatic Examples to Train Neural Program Synthesizers
por: Vaduguru, Saujas, et al.
Publicado: (2023)

Mirage: A Multi-Level Superoptimizer for Tensor Programs
por: Wu, Mengdi, et al.
Publicado: (2024)

Assured Automatic Programming via Large Language Models
por: Mirchev, Martin, et al.
Publicado: (2024)

Teaching LLMs Program Semantics via Symbolic Execution Traces
por: Bayer, Jonas, et al.
Publicado: (2026)

Dato: A Task-Based Programming Model for Dataflow Accelerators
por: Fang, Shihan, et al.
Publicado: (2025)

Streaming Tensor Programs: A Streaming Abstraction for Dynamic Parallelism
por: Sohn, Gina, et al.
Publicado: (2025)

CodeARC: Benchmarking Reasoning Capabilities of LLM Agents for Inductive Program Synthesis
por: Wei, Anjiang, et al.
Publicado: (2025)

Hexcute: A Compiler Framework for Automating Layout Synthesis in GPU Programs
por: Zhang, Xiao, et al.
Publicado: (2025)

Bridging the Knowledge Void: Inference-time Acquisition of Unfamiliar Programming Languages for Coding Tasks
por: Shen, Chen, et al.
Publicado: (2026)