17 papers
Self-Evolving Multi-Agent Systems via Textual Backpropagation
Xiaowen Ma, Yunpu Ma, Chenyang Lin +6
Leveraging multiple Large Language Models (LLMs) has proven effective for addressing complex, high-dimensional tasks, but current approaches often rely on static, manually engineer…
EchoRL: Reinforcement Learning via Rollout Echoing
Jinhe Bi, Aniri, Minglai Yang +9
Reinforcement Learning with Verifiable Rewards is an effective route for post-training to strengthen the reasoning capability of large language models. However, as training proceed…
PRISM: Self-Pruning Intrinsic Selection Method for Training-Free Multimodal Data Selection
Jinhe Bi, Aniri, Zengjie Jin +11
Visual instruction tuning adapts pre-trained Multimodal Large Language Models (MLLMs) to follow human instructions for real-world applications. However, the rapid growth of these d…
Routing-Free Mixture-of-Experts
Yilun Liu, Jinru Han, Sikuan Yan +2
Standard Mixture-of-Experts (MoE) models rely on centralized routing mechanisms that introduce rigid inductive biases. We propose Routing-Free MoE which eliminates any hard-coded c…
Quantum Architecture Search with Unsupervised Representation Learning
Yize Sun, Zixin Wu, Volker Tresp +1
Unsupervised representation learning presents new opportunities for advancing Quantum Architecture Search (QAS) on Noisy Intermediate-Scale Quantum (NISQ) devices. QAS is designed…
Bayes or Heisenberg: Who(se) Rules?
Volker Tresp, Hang Li, Federico Harjes +1
Although quantum systems are generally described by quantum state vectors, we show that in certain cases their measurement processes can be reformulated as probabilistic equations…