Papers

• Selective Self-to-Supervised Fine-Tuning for Generalization in Large Language Models (2025)
  Sonam Gupta et al.
  4.25
• DrugGen 2: A disease-aware language model for enhancing drug discovery (2026)
  Ali Motahharynia et al.
  2.00
• EpiCaR: Knowing What You Don't Know Matters for Better Reasoning in LLMs (2026)
  Jewon Yeom et al.
  1.94
• Learning to Commit: Generating Organic Pull Requests via Online Repository Memory (2026)
  Mo Li et al.
  1.94
• Schema on the Inside: A Two-Phase Fine-Tuning Method for High-Efficiency Text-to-SQL at Scale (2026)
  Chinmay Soni et al.
  1.78
• SERA: Soft-Verified Efficient Repository Agents (2026)
  Ethan Shen et al.
  1.67
• NEFMind: Parameter-Efficient Fine-Tuning of Open-Source LLMs for Telecom APIs Automation (2025)
  Zainab Khan et al.
  1.39
• Technical Report: Full-Stack Fine-Tuning for the Q Programming Language (2025)
  Brendan R. Hogan et al.
  1.28
• Agent Data Protocol: Unifying Datasets for Diverse, Effective Fine-tuning of LLM Agents (2025)
  Yueqi Song et al.
  1.28
• Improving AMR Parsing with Sequence-to-Sequence Pre-training (2020)
  Dongqin Xu et al.
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• LLaMA-Mesh: Unifying 3D Mesh Generation with Language Models (2024)
  Zhengyi Wang et al.
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• AceMath: Advancing Frontier Math Reasoning with Post-Training and Reward Modeling (2024)
  Zihan Liu et al.
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