时 间:15:00-17:00, Sep 9, 2026 (Wed)地 点:MMW-727会议室 (腾讯会议: 422-776-136)内容:In the context of irreversible dynamics, the meaning of the reverse of a physical evolution can be quite ambiguous. It is a standard choice to define the reverse process using Bayes' theorem, but, in general, this is not optimal with respect to the relative entropy of recovery. In this work we explore wh...
时 间:10:00-12:00, Sep 8, 2026 (Tue)地 点:RM 1-202, FIT Building内容:AI 应用已经从单一、单体的基础模型(FM)转向复合型智能体系统。然而,今天的技术栈仍然是碎片化的:即便协议(如 MCP、A2A)缓解了工具/智能体连接问题,每个框架仍内嵌了一个隐式运行时,用于处理状态、记忆、预算和护栏,这使得行为不可移植,治理也变得脆弱。这与操作系统出现之前的计算环境如出一辙,那时每个程序都要重新实现基本服务。本...
时 间:11:00-12:00, Aug 13, 2026 (Thu)地 点:RM S527, MMW Building内容:Detecting quantum resources, especially in mixed quantum states, is a highly challenging task. Starting from the widely-used concept of resource witnesses, we propose a framework that systematically generate analytical and experimentally accessible criteria based on a single witness and a group of free unitaries.Our co...
时 间:11:00-12:00, Aug 21, 2026 (Fri)地 点:腾讯会议:188-585-149(会议链接:https://meeting.tencent.com/dm/ueSfCeE8ENCB)内容:Duality transformations reveal unexpected equivalences between seemingly distinct models. We introduce a concept of global duality, in which a duality operator intertwines two one-dimensional local Hamiltonians via generalised exchange relations, in contrast to lo...
时 间:10:00-11:00, Aug 7, 2026 (Fri)地 点:https://meeting.tencent.com/dm/z9BkdA8pj32P (https://meeting.tencent.com/dm/z9BkdA8pj32P)内容:Driven by next-token prediction, NLP shifted from task-specific models into powerful generalist foundation models. What, then, is the equivalent catalyst needed to achieve a general-purpose model in computer vision?In this talk, we contend that large-sca...
时 间:11:00-12:00, Aug 6, 2026 (Thu)地 点:https://meeting.tencent.com/dm/RB08CDbR31ou (https://meeting.tencent.com/dm/RB08CDbR31ou)内容:Robots operating in real-world environments must handle open-ended tasks, novel objects, and instructions from non-expert users. However, current systems often fail to generalize beyond their training data because they lack commonsense knowledge about th...