An Exact Generate - Transform Decomposition of Small-LLM Team Scaling Across Orchestration Architectures
cs.AI
Submitted: 2026-09-28
Updated: 2026-09-28
Sources
- Large Language Monkeys: Scaling Inference Compute with Repeated Sampling
- Evaluating Large Language Models Trained on Code
- Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
- Training Verifiers to Solve Math Word Problems
- Oracle Gap and Signal Fidelity: A Fixed-Pool Diagnostic for Test-Time Collaboration
- Towards a Science of Scaling Agent Systems
- Nine Judges, Two Effective Votes: Correlated Errors Undermine LLM Evaluation Panels
- LLMs Can Generate a Better Answer by Aggregating Their Own Responses
- Single-Agent LLMs Outperform Multi-Agent Systems on Multi-Hop Reasoning Under Equal Thinking Token Budgets
- Recursive Self-Aggregation Unlocks Deep Thinking in Large Language Models
- Understanding Agent Scaling in LLM-Based Multi-Agent Systems via Diversity
- AdaptOrch: Task-Adaptive Multi-Agent Orchestration in the Era of LLM Performance Convergence
Related papers
- MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
- Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
- Agents' Last Exam
- The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
- MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
- Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems