演讲人: Souradeep Sasmal [University of Electronic Science and Technology of China]时间: 15:00-17:00, Sep 8, 2025 (Mon)地点: RM S327, MMW Building (#腾讯会议:435-802-209)内容:The prevailing consensus is that the sequential sharing of nonlocality in a Bell experiment requires generalised unsharp measurements, since a sharp measurement inevitably destroys the entanglement of the shared state...
演讲人: Sergey Samsonov [HSE University] 时间: 11:00-12:00, Aug 25, 2025 (Mon)地点:11:00-12:00, Aug 25, 2025 (Mon)内容:GFlowNets are a family of generative models that learn to sample objects from a given probability distribution, potentially known only up to a normalizing constant. The key concept behind GFlowNets is the use of two stochastic policies: a forward policy, which incrementally...
演讲人: 程韵 [普林斯顿大学] 时间: 11:00-12:00, Aug 13, 2025 (Wed)地点:RM 1-222, FIT Building (//meeting.tencent.com/dm/hpLuprdKjM45 #腾讯会议:567-960-508)内容:While Vision Language Models (VLMs) are impressive in tasks such as visual question answering (VQA) and image captioning, their ability to apply multi-step reasoning to images has lagged, giving rise to perceptions of modality ...
演讲人: 朱星宇 [普林斯顿大学]时间: 11:00-12:00, Aug 11, 2025 (Mon)地点:RM 1-222, FIT Building (//meeting.tencent.com/dm/O15OBOE6VLfC #腾讯会议:490-402-711)内容:We formalize a new concept for LLMs, context-enhanced learning. It involves standard gradient-based learning on text except that the context is enhanced with additional data on which no auto-regressive gradients are computed. ...
演讲人: Chi Jin [Princeton University]时间: 11:00-12:00, Jul 30, 2025 (Wed)地点:RM 1-222, FIT Building (//meeting.tencent.com/dm/wIj1OMGZx499)内容:This talk introduces Goedel-Prover-V2, an open-source model that establishes a new state-of-the-art for automated theorem proving in Lean. //blog.goedel-prover.com/个人简介:Chi Jin is an Assistant Professor of Electrical and Computer ...
演讲人: Renfei Zhou [CMU]时间: 11:00-12:00, Jul 25, 2025 (Fri)地点:RM 1-222, FIT Building (//meeting.tencent.com/dm/1suGQN3X1y5V (#腾讯会议:939-634-954))内容:Fast matrix multiplication is one of the most fundamental problems in computer science. We present new algorithms that improve the time complexity of matrix multiplication to $n^{2.371339}$, surpassing the previous bound of $n...