Papers Workflow Discovery
“Workflow Discovery” 태그가 달린 논문 4편 · 필터 해제
AutoSynth: Automated Workflow Optimization for High-Quality Synthetic Dataset Generation via Monte Carlo Tree Search
Supervised fine-tuning (SFT) of large language models (LLMs) for specialized tasks requires high-quality datasets, but manual curation is prohibitively expensive. Synthetic data generation offers scalability, but its eff…
Synthetic Data GenerationPrompt EngineeringWorkflow DiscoveryOpus: A Quantitative Framework for Workflow Evaluation
This paper introduces the Opus Workflow Evaluation Framework, a probabilistic-normative formulation for quantifying Workflow quality and efficiency. It integrates notions of correctness, reliability, and cost into a cohe…
Reinforcement LearningWorkflow DiscoveryLeveraging Explicit Procedural Instructions for Data-Efficient Action Prediction
Task-oriented dialogues often require agents to enact complex, multi-step procedures in order to meet user requests. While large language models have found success automating these dialogues in constrained environments, …
Language ModelingLanguage ModellingLarge Language ModelMasked Language Modeling+3Workflow Discovery from Dialogues in the Low Data Regime
Text-based dialogues are now widely used to solve real-world problems. In cases where solution strategies are already known, they can sometimes be codified into workflows and used to guide humans or artificial agents thr…
Workflow Discovery