4 papers
Memorization, Emergence, and Explaining Reversal Failures: A Controlled Study of Relational Semantics in LLMs
Yihua Zhu, Qianying Liu, Jiaxin Wang +5
Autoregressive LLMs perform well on relational tasks that require linking entities via relational words (e.g., father/son, friend), but it is unclear whether they learn the logical…
Rollout-Training Co-Design for Efficient LLM-Based Multi-Agent Reinforcement Learning
Zhida Jiang, Zhaolong Xing, Jiawei Lu +13
Despite algorithm-level innovations for multi-agent reinforcement learning (MARL), the underlying networked infrastructure for large-scale MARL training remains underexplored. Exis…
Kimi K2: Open Agentic Intelligence
Kimi Team, Yifan Bai, Yiping Bao +195
We introduce Kimi K2, a Mixture-of-Experts (MoE) large language model with 32 billion activated parameters and 1 trillion total parameters. We propose the MuonClip optimizer, which…
Logic-of-Thought: Injecting Logic into Contexts for Full Reasoning in Large Language Models
Tongxuan Liu, Wenjiang Xu, Weizhe Huang +5
Large Language Models (LLMs) have demonstrated remarkable capabilities across various tasks but their performance in complex logical reasoning tasks remains unsatisfactory. Althoug…