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Found 11 papers, 6 papers with code
EvoCodeBench: An Evolving Code Generation Benchmark with Domain-Specific Evaluations
These evaluations help practitioners select superior LLMs in specific domains and discover the shortcomings of existing LLMs.
Seeker: Enhancing Exception Handling in Code with LLM-based Multi-Agent Approach
In real world software development, improper or missing exception handling can severely impact the robustness and reliability of code.
DECOR: Improving Coherence in L2 English Writing with a Novel Benchmark for Incoherence Detection, Reasoning, and Rewriting
To bridge this gap, we introduce DECOR, a novel benchmark that includes expert annotations for detecting incoherence in L2 English writing, identifying the underlying reasons, and rewriting the incoherent sentences.
VarBench: Robust Language Model Benchmarking Through Dynamic Variable Perturbation
As large language models achieve impressive scores on traditional benchmarks, an increasing number of researchers are becoming concerned about benchmark data leakage during pre-training, commonly known as the data contamination problem.
DevEval: A Manually-Annotated Code Generation Benchmark Aligned with Real-World Code Repositories
Our experiments reveal these LLMs' coding abilities in real-world code repositories.
EvoCodeBench: An Evolving Code Generation Benchmark Aligned with Real-World Code Repositories
Existing benchmarks demonstrate poor alignment with real-world code repositories and are insufficient to evaluate the coding abilities of LLMs.
ProLex: A Benchmark for Language Proficiency-oriented Lexical Substitution
To bridge this gap, we propose a new task, language proficiency-oriented lexical substitution.
DevEval: Evaluating Code Generation in Practical Software Projects
Compared to previous benchmarks, DevEval aligns to practical projects in multiple dimensions, e. g., real program distributions, sufficient dependencies, and enough-scale project contexts.
Multicollinearity Resolution Based on Machine Learning: A Case Study of Carbon Emissions in Sichuan Province
Penalized regression models were then applied for their advantages in overfitting control, high-dimensional data processing, and feature selection - well-suited for the complex energy data.
A High-fidelity, Machine-learning Enhanced Queueing Network Simulation Model for Hospital Ultrasound Operations
To address the issue, we propose a novel two-level routing component to the queueing network model.
Aspect-Based Sentiment Analysis as Fine-Grained Opinion Mining
We show how the general fine-grained opinion mining concepts of opinion target and opinion expression are related to aspect-based sentiment analysis (ABSA) and discuss their benefits for resource creation over popular ABSA annotation schemes.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
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