Papers

• From Resource Flow to Executable Tests: Petri-Net-Guided LLM Test Generation for Concurrent Stateful Rust APIs (2026)
  Kaiwen Zhang et al.
  4.39
• Self-Execution Simulation Improves Coding Models (2026)
  Gallil Maimon et al.
  1.83
• Competitive Programming with Large Reasoning Models (2025)
  OpenAI et al.
  1.28
• Selective Self-to-Supervised Fine-Tuning for Generalization in Large Language Models (2025)
  Sonam Gupta et al.
  1.28
• Building A Proof-Oriented Programmer That Is 64% Better Than GPT-4o Under Data Scarsity (2025)
  Dylan Zhang et al.
  1.28
• CodeARC: Benchmarking Reasoning Capabilities of LLM Agents for Inductive Program Synthesis (2025)
  Anjiang Wei et al.
  1.28
• DINGO: Constrained Inference for Diffusion LLMs (2025)
  Tarun Suresh et al.
  1.28
• SR-Scientist: Scientific Equation Discovery With Agentic AI (2025)
  Shijie Xia et al.
  1.28
• Scaling Laws for Code: Every Programming Language Matters (2025)
  Jian Yang et al.
  1.28
• SymbolicAI: A framework for logic-based approaches combining generative models and solvers (2024)
  Marius-Constantin Dinu et al.
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• FaceChain-SuDe: Building Derived Class to Inherit Category Attributes for One-shot Subject-Driven Generation (2024)
  Pengchong Qiao et al.
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• Automated Design of Agentic Systems (2024)
  Shengran Hu et al.
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• CodeMMLU: A Multi-Task Benchmark for Assessing Code Understanding Capabilities of CodeLLMs (2024)
  Dung Nguyen Manh et al.
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