Copertina

AnCoder: Anchored Code Generation via Discrete Diffusion Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Xue, Anton, Rout, Litu, Caramanis, Constantine, Shakkottai, Sanjay
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning Programming Languages
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Anchored Diffusion Language Model
di: Rout, Litu, et al.
Pubblicazione: (2025)

Entropy Aware Reward Guidance for Diffusion Language Model Alignment
di: Tejaswi, Atula, et al.
Pubblicazione: (2026)

Test-Time Anchoring for Discrete Diffusion Posterior Sampling
di: Rout, Litu, et al.
Pubblicazione: (2025)

RB-Modulation: Training-Free Personalization of Diffusion Models using Stochastic Optimal Control
di: Rout, Litu, et al.
Pubblicazione: (2024)

Semantic Image Inversion and Editing using Rectified Stochastic Differential Equations
di: Rout, Litu, et al.
Pubblicazione: (2024)

Efficient Approximate Posterior Sampling with Annealed Langevin Monte Carlo
di: Parulekar, Advait, et al.
Pubblicazione: (2025)

Asymptotically-Optimal Gaussian Bandits with Side Observations
di: Atsidakou, Alexia, et al.
Pubblicazione: (2025)

Constrained Posterior Sampling: Time Series Generation with Hard Constraints
di: Narasimhan, Sai Shankar, et al.
Pubblicazione: (2024)

MonoCoder: Domain-Specific Code Language Model for HPC Codes and Tasks
di: Kadosh, Tal, et al.
Pubblicazione: (2023)

Constrained Decoding for Fill-in-the-Middle Code Language Models via Efficient Left and Right Quotienting of Context-Sensitive Grammars
di: Melcer, Daniel, et al.
Pubblicazione: (2024)

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

MaxSketch: Robust Distinct Counting in Streams via Random Projections
di: Tsikouras, Nikos, et al.
Pubblicazione: (2026)

Self-Infilling Code Generation
di: Zheng, Lin, et al.
Pubblicazione: (2023)

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

ANCORA: Learning to Question via Manifold-Anchored Self-Play for Verifiable Reasoning
di: Yang, Chengcao
Pubblicazione: (2026)

Correctness-Guaranteed Code Generation via Constrained Decoding
di: Li, Lingxiao, et al.
Pubblicazione: (2025)

Optimization Can Learn Johnson Lindenstrauss Embeddings
di: Tsikouras, Nikos, et al.
Pubblicazione: (2024)

On Mitigating Affinity Bias through Bandits with Evolving Biased Feedback
di: Faw, Matthew, et al.
Pubblicazione: (2025)

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

BioCoder: A Benchmark for Bioinformatics Code Generation with Large Language Models
di: Tang, Xiangru, et al.
Pubblicazione: (2023)

More Than a Score: Probing the Impact of Prompt Specificity on LLM Code Generation
di: Zi, Yangtian, et al.
Pubblicazione: (2025)

SIMCOPILOT: Evaluating Large Language Models for Copilot-Style Code Generation
di: Jiang, Mingchao, et al.
Pubblicazione: (2025)

Malicious and Unintentional Disclosure Risks in Large Language Models for Code Generation
di: Rabin, Rafiqul, et al.
Pubblicazione: (2025)

Constrained Code Generation with Discrete Diffusion
di: Shao, Lize, et al.
Pubblicazione: (2026)

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

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

ReflexiCoder: Teaching Large Language Models to Self-Reflect on Generated Code and Self-Correct It via Reinforcement Learning
di: Jiang, Juyong, et al.
Pubblicazione: (2026)

KnowCoder-X: Boosting Multilingual Information Extraction via Code
di: Zuo, Yuxin, et al.
Pubblicazione: (2024)

Top Leaderboard Ranking = Top Coding Proficiency, Always? EvoEval: Evolving Coding Benchmarks via LLM
di: Xia, Chunqiu Steven, et al.
Pubblicazione: (2024)

RTL++: Graph-enhanced LLM for RTL Code Generation
di: Akyash, Mohammad, et al.
Pubblicazione: (2025)

Neural Models for Source Code Synthesis and Completion
di: Niyogi, Mitodru
Pubblicazione: (2024)

Code Simulation Challenges for Large Language Models
di: La Malfa, Emanuele, et al.
Pubblicazione: (2024)

SecCoder: Towards Generalizable and Robust Secure Code Generation
di: Zhang, Boyu, et al.
Pubblicazione: (2024)

In-Context Learning with Transformers: Softmax Attention Adapts to Function Lipschitzness
di: Collins, Liam, et al.
Pubblicazione: (2024)

Grounding Data Science Code Generation with Input-Output Specifications
di: Wen, Yeming, et al.
Pubblicazione: (2024)

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

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

QiMeng-SALV: Signal-Aware Learning for Verilog Code Generation
di: Zhang, Yang, et al.
Pubblicazione: (2025)

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

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