Hung Le

Hung Le has 2 papers in our library, in 2022–2025, most of them on Code & programming languages; often with Silvio Savarese, Akhilesh Deepak Gotmare, Caiming Xiong.

2 papers in our library · 2022–2025

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Fields, topics and concepts

Of its works in our library, with the number of works on each.

The most cited first (OpenAlex and our library).

CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning (2022 · 297 citations)
CodeRL tackles a weakness of code-generating language models. They are usually fine-tuned only to reproduce reference solutions token by token, so they never learn whether a program actually works. As a result they struggle with hard, competition-style problems. The authors treat program synthesis as a reinforcement…
CodeTree: Agent-guided Tree Search for Code Generation with Large Language Models (2025 · 21 citations)
Hard programming tasks have a huge space of possible solutions. Older methods either sample many independent candidates or repeatedly refine one early attempt, which can trap them in a local optimum. CodeTree addresses this by organizing code generation as a tree search run by cooperating LLM agents. A Thinker agent…

7 co-authors with a page, the most papers together first.

Where their works here were published, the most works first, with the editions of those that have a page.

Papers of our library cite their works 191 times (of the 149,439 papers whose bibliographies we read); 38 citing papers with a page here →.

Updated 30 October 2026