World Action Models (WAMs) have emerged as a promising paradigm for generalizable robot control. Despite the growing number of WAM systems, existing works often introduce unified systems that bundle together multiple design choices, such as architecture and training strategy, making it difficult to isolate individual c...
Chao Tang, Haoqing Wang, Zi-Lang Cen et al.· 0 citations
Mixture-of-Experts (MoE) language models suffer from large parameter counts, which create a significant memory bottleneck. Expert pruning is the most direct approach for reducing this parameter count, yet existing methods make pruning decisions for each expert independently, and assume experts'contributions are purely...
Alex M. Tseng, Prannay Kaul, L. Zancato et al.· 0 citations
FaithEyes, a multi-agent self-judging framework that uses a VLM to judge whether each process image helps answer the question and designs a multi-agent framework where the model itself serves as a subagent to judge the tool calls from the main agent, eliminating any dependence on external models at inference.
