#fine-tuning
- MinT: Managed Infrastructure for Training and Serving Millions of LLMs Mind Lab research
- Program-as-Weights: Compiling Task Specs into LoRA Adapters for On-Device Inference University of Waterloo / Harvard research
- Compile by Training: turning natural-language specifications into local neural functions research
- Continual Learning Mechanisms Compose for Long-Horizon Memorization Johns Hopkins University research
- Super Weights in LLMs: Why High-Salience Parameters Fail as Fine-Tuning Targets Amazon research
- Super Weights in LLMs and the Failure of Selective Training Amazon Web Services research
- Code2LoRA: Hypernetwork Generates Repo-Specific Adapters for Code LMs with Zero Inference Overhead University of Waterloo research
- Agentic ESOpt: Fine-Tuning Long-Horizon LLM Agents with Minimal GPU Requirements National University of Singapore (Zhi Zheng, Wee Sun Lee et al.) research
- InternLM ships Intern-Decision, an open-weights multimodal decision model family InternLM (Shanghai AI Lab) models-llm
- Verbalizing Activation Differences with Natural Language Autoencoders research