11 citations · 12 across the 4 of their papers we have counts for
4 papers
Is Code Better Than Language for Algorithmic Reasoning
Terry Tong, Yu Feng, Surbhi Goel +1
For tool-augmented language models, comparing natural-language reasoning with code-execution pipelines is difficult because the comparison changes both the intermediate representat…
Fewer Truncations Improve Language Modeling
Hantian Ding, Zijian Wang, Giovanni Paolini +4
In large language model training, input documents are typically concatenated together and then split into sequences of equal length to avoid padding tokens. Despite its efficiency,…
Code Representation Learning At Scale
Dejiao Zhang, Wasi Ahmad, Ming Tan +5
Recent studies have shown that code language models at scale demonstrate significant performance gains on downstream tasks, i.e., code generation. However, most of the existing wor…
CrossCodeEval: A Diverse and Multilingual Benchmark for Cross-File Code Completion
Yangruibo Ding, Zijian Wang, Wasi Uddin Ahmad +8
Code completion models have made significant progress in recent years, yet current popular evaluation datasets, such as HumanEval and MBPP, predominantly focus on code completion t…