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cs.LG2026
When Parallelism Pays Off: Cohesion-Aware Task Partitioning for Multi-Agent Coding
Xu Yang, Lunyiu Nie, Ethan Chandra +3
Multi-agent Large Language Model (LLM) systems offer a way to decompose complex tasks, such as coding, through parallelization and context isolation. However, adding agents in prac…
cs.LG2025
Loong: Synthesize Long Chain-of-Thoughts at Scale through Verifiers
Xingyue Huang, Rishabh, Gregor Franke +43
Recent advances in Large Language Models (LLMs) have shown that their reasoning capabilities can be significantly improved through Reinforcement Learning with Verifiable Reward (RL…