Feed m Birds with One Scone: Accelerating Multi-task Gradient Balancing via Bi-level Optimization
Feed m Birds with One Scone: Accelerating Multi-task Gradient Balancing via Bi-level Optimization explores MARIGOLD accelerates multi-task learning by efficiently balancing gradients using bi-level optimization, showing superior performance on public and industrial datasets.. Commercial viability score: 7/10 in Multi-Task Learning.
BUILDER'S SANDBOX
Build This Paper
Use an AI coding agent to implement this research.
OpenAI CodexAI Agent
Lightweight coding agent in your terminal.
Claude CodeAI Agent
Agentic coding tool for terminal workflows.
AntiGravity IDEScaffolding
AI agent mindset installer and workflow scaffolder.
CursorIDE
AI-first code editor built on VS Code.
VS CodeIDE
Free, open-source editor by Microsoft.
Recommended Stack
Startup Essentials
Estimated $9K - $13K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
Related Papers
- Builds On ThisMulti-Task GRPO: Reliable LLM Reasoning Across TasksViability: 4.0
- Builds On ThisDisentangling Task Conflicts in Multi-Task LoRA via Orthogonal Gradient ProjectionViability: 5.0
- Builds On ThisBD-Merging: Bias-Aware Dynamic Model Merging with Evidence-Guided Contrastive LearningViability: 5.0
- Builds On ThisA Unified Hierarchical Multi-Task Multi-Fidelity Framework for Data-Efficient Surrogate Modeling in ManufacturingViability: 6.0
- Builds On ThisMulti-Task Genetic Algorithm with Multi-Granularity Encoding for Protein-Nucleotide Binding Site Prediction