Planning in Natural Language Improves LLM Search for Code Generation
No confident code implementation found for this paper. 5 possible matches can be shown below.
No confident code implementation found for this paper. 5 possible matches can be shown below.
No confident code match yet
We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 5 weaker matches are hidden by default — verify before relying on them.
No code implementations found yet.
Know of an implementation? Let us know in the comments below!
How Many Are in This Image A Safety Evaluation Benchmark for Vision LLMs
Policy Evaluation for Variance in Average Reward Reinforcement Learning
Graph Neural Stochastic Diffusion for Estimating Uncertainty in Node Classification
POMDP Planning for Object Search in Partially Unknown Environment
Underestimated Privacy Risks for Minority Populations in Large Language Model Unlearning
Public Opinion Field Effect Fusion in Representation Learning for Trending Topics Diffusion
@article{wang2026planning,
title = {Planning in Natural Language Improves LLM Search for Code Generation},
author = {Evan Z. Wang and Federico Cassano and Catherine Wu and Yunfeng Bai and Will Song and Vaskar Nath and Ziwen Han and Sean M. Hendryx and Summer Yue and Hugh Zhang},
year = {2026},
url = {https://api.semanticscholar.org/CorpusID:032641bb7d4a5dfd10922ed11963f97959370dc3},
journal = {ICLR 2025 2025}
}Shows whether official code is linked for this paper.
[](https://codeofpaper.com/paper/032641bb7d4a5dfd10922ed11963f97959370dc3)