Tootfinder

An RDMA-First Object Storage System with SmartNIC Offload
Yu Zhu, Aditya Dhakal, Pedro Bruel, Gourav Rattihalli, Yunming Xiao, Johann Lombardi, Dejan Milojicic
https://arxiv.org/abs/2509.13997

An RDMA-First Object Storage System with SmartNIC Offload
AI training and inference impose sustained, fine-grain I/O that stresses host-mediated, TCP-based storage paths. Motivated by kernel-bypass networking and user-space storage stacks, we revisit POSIX-compatible object storage for GPU-centric pipelines. We present ROS2, an RDMA-first object storage system design that offloads the DAOS client to an NVIDIA BlueField-3 SmartNIC while leaving the DAOS I/O engine unchanged on the storage server. ROS2 separates a lightweight control plane (gRPC for nam…

SWE-Debate: Competitive Multi-Agent Debate for Software Issue Resolution
Han Li, Yuling Shi, Shaoxin Lin, Xiaodong Gu, Heng Lian, Xin Wang, Yantao Jia, Tao Huang, Qianxiang Wang
https://arxiv.org/abs/2507.23348

SWE-Debate: Competitive Multi-Agent Debate for Software Issue Resolution
Issue resolution has made remarkable progress thanks to the advanced reasoning capabilities of large language models (LLMs). Recently, agent-based frameworks such as SWE-agent have further advanced this progress by enabling autonomous, tool-using agents to tackle complex software engineering tasks. While existing agent-based issue resolution approaches are primarily based on agents' independent explorations, they often get stuck in local solutions and fail to identify issue patterns that span a…

Inverse Elastica: A Theoretical Framework for Inverse Design of Morphing Slender Structures
JiaHao Li, Weicheng Huang, YinBo Zhu, Luxia Yu, Xiaohao Sun, Mingchao Liu, HengAn Wu
https://arxiv.org/abs/2508.19673

Inverse Elastica: A Theoretical Framework for Inverse Design of Morphing Slender Structures
Inverse design of morphing slender structures with programmable curvature has significant applications in various engineering fields. Most existing studies formulate it as an optimization problem, which requires repeatedly solving the forward equations to identify optimal designs. Such methods, however, are computationally intensive and often susceptible to local minima issues. In contrast, solving the inverse problem theoretically, which can bypass the need for optimizations, is highly efficie…