MFTCoder: Boosting Code LLMs with Multitask Fine-Tuning
Paper
• 2311.02303 • Published
• 12
codefuse-papers
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CodeFuse-13B: A Pretrained Multi-lingual Code Large Language Model
Paper • 2310.06266 • Published • 2 -
CoBa: Convergence Balancer for Multitask Finetuning of Large Language Models
Paper • 2410.06741 • Published • 3 -
Every Sample Matters: Leveraging Mixture-of-Experts and High-Quality Data for Efficient and Accurate Code LLM
Paper • 2503.17793 • Published • 24 -
Code Graph Model (CGM): A Graph-Integrated Large Language Model for Repository-Level Software Engineering Tasks
Paper • 2505.16901 • Published • 48 -
Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code
Paper • 2311.07989 • Published • 26 -
Prompting Frameworks for Large Language Models: A Survey
Paper • 2311.12785 • Published -
LLMDFA: Analyzing Dataflow in Code with Large Language Models
Paper • 2402.10754 • Published • 1 -
GALLa: Graph Aligned Large Language Models for Improved Source Code Understanding
Paper • 2409.04183 • Published • 3 -
Rodimus*: Breaking the Accuracy-Efficiency Trade-Off with Efficient Attentions
Paper • 2410.06577 • Published • 14 -
CodeFuse-CR-Bench: A Comprehensiveness-aware Benchmark for End-to-End Code Review Evaluation in Python Projects
Paper • 2509.14856 • Published • 2 -
D2LLM: Decomposed and Distilled Large Language Models for Semantic Search
Paper • 2406.17262 • Published • 5 -
E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning
Paper • 2409.06679 • Published • 4 -
F2LLM Technical Report: Matching SOTA Embedding Performance with 6 Million Open-Source Data
Paper • 2510.02294 • Published • 46 -
C2LLM Technical Report: A New Frontier in Code Retrieval via Adaptive Cross-Attention Pooling
Paper • 2512.21332 • Published • 16