activity
20182024
most citedComplexCodeEval: A Benchmark for Evaluating Large Code Models on More Complex Code

8 citations · 15 across the 4 of their papers we have counts for

collaborators

5 papers

cs.SE2024

A Systematic Evaluation of Large Code Models in API Suggestion: When, Which, and How

Chaozheng Wang, Shuzheng Gao, Cuiyun Gao +4

API suggestion is a critical task in modern software development, assisting programmers by predicting and recommending third-party APIs based on the current context. Recent advance…

cs.SE20248 cited

ComplexCodeEval: A Benchmark for Evaluating Large Code Models on More Complex Code

Jia Feng, Jiachen Liu, Cuiyun Gao +4

In recent years, the application of large language models (LLMs) to code-related tasks has gained significant attention. However, existing evaluation benchmarks often focus on limi…

cs.LG20215 cited

Label-Aware Distribution Calibration for Long-tailed Classification

Chaozheng Wang, Shuzheng Gao, Cuiyun Gao +4

Real-world data usually present long-tailed distributions. Training on imbalanced data tends to render neural networks perform well on head classes while much worse on tail classes…

cs.SE20212 cited

Enriching Query Semantics for Code Search with Reinforcement Learning

Chaozheng Wang, Zhenghao Nong, Cuiyun Gao +4

Code search is a common practice for developers during software implementation. The challenges of accurate code search mainly lie in the knowledge gap between source code and natur…

cs.RO2018

Adapting Everyday Manipulation Skills to Varied Scenarios

Pawel Gajewski, Paulo Ferreira, Georg Bartels +5

We address the problem of executing tool-using manipulation skills in scenarios where the objects to be used may vary. We assume that point clouds of the tool and target object can…