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20242026
most citedA Comprehensive Survey on Long Context Language Modeling

1 citations · 1 across the 9 of their papers we have counts for

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cs.SE2025

CodeIF: Benchmarking the Instruction-Following Capabilities of Large Language Models for Code Generation

Kaiwen Yan, Hongcheng Guo, Xuanqing Shi +3

With the rapid advancement of Large Language Models (LLMs), the demand for robust instruction-following capabilities in code generation tasks has grown significantly. Code generati…

cs.SE2025

Turning the Tide: Repository-based Code Reflection

Wei Zhang, Jian Yang, Jiaxi Yang +5

Code large language models (LLMs) enhance programming by understanding and generating code across languages, offering intelligent feedback, bug detection, and code updates through…

cs.SE2025

Lemur: Log Parsing with Entropy Sampling and Chain-of-Thought Merging

Wei Zhang, Xiangyuan Guan, Lu Yunhong +5

Logs produced by extensive software systems are integral to monitoring system behaviors. Advanced log analysis facilitates the detection, alerting, and diagnosis of system faults.…

cs.SE2024

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback

Wei Zhang, Yi Zhang, Li Zhu +5

Large Language Models (LLMs) have made significant strides in Natural Language Processing and coding, yet they struggle with robustness and accuracy in complex function calls. To t…

cs.SE2024

In-Context Code-Text Learning for Bimodal Software Engineering

Xunzhu Tang, Liran Wang, Yonghui Liu +6

Bimodal software analysis initially appeared to be within reach with the advent of large language models. Unfortunately, the complex interplay of natural language text and code in…

cs.SE2024

ECLIPSE: Semantic Entropy-LCS for Cross-Lingual Industrial Log Parsing

Wei Zhang, Xianfu Cheng, Yi Zhang +8

Log parsing, a vital task for interpreting the vast and complex data produced within software architectures faces significant challenges in the transition from academic benchmarks…