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https://sammlung.belvedere.at/objects/52614/elfriede-jelinek-9-juni-1970-lesung-und-diskussionsrunde

Elfriede Jelinek, 9. Juni 1970, Lesung und Diskussionsrunde

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Jalen Ngonda:
🎵 Just as Long as Were Together
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https://jalenngonda.bandcamp.com/track/just-as-long-as-were-together
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Did Trump miss a chance at his dream Nobel by not arresting and jailing the war criminal Putin?

ToxiFrench: Benchmarking and Enhancing Language Models via CoT Fine-Tuning for French Toxicity Detection
Axel Delaval, Shujian Yang, Haicheng Wang, Han Qiu, Jialiang Lu
https://arxiv.org/abs/2508.11281

ToxiFrench: Benchmarking and Enhancing Language Models via CoT Fine-Tuning for French Toxicity Detection
Detecting toxic content using language models is crucial yet challenging. While substantial progress has been made in English, toxicity detection in French remains underdeveloped, primarily due to the lack of culturally relevant, large-scale datasets. In this work, we introduce TOXIFRENCH, a new public benchmark of 53,622 French online comments, constructed via a semi-automated annotation pipeline that reduces manual labeling to only 10% through high-confidence LLM-based pre-annotation and huma…

Track Any Motions under Any Disturbances
Zhikai Zhang, Jun Guo, Chao Chen, Jilong Wang, Chenghuai Lin, Yunrui Lian, Han Xue, Zhenrong Wang, Maoqi Liu, Huaping Liu, He Wang, Li Yi
https://arxiv.org/abs/2509.13833

Track Any Motions under Any Disturbances
A foundational humanoid motion tracker is expected to be able to track diverse, highly dynamic, and contact-rich motions. More importantly, it needs to operate stably in real-world scenarios against various dynamics disturbances, including terrains, external forces, and physical property changes for general practical use. To achieve this goal, we propose Any2Track (Track Any motions under Any disturbances), a two-stage RL framework to track various motions under multiple disturbances in the rea…

Nucleation-free independent graphs with implied nonedges
Jialong Cheng, Meera Sitharam, Ileana Streinu, William Sims
https://arxiv.org/abs/2508.12417 https://

Nucleation-free independent graphs with implied nonedges
We give inductive constructions of independent graphs that contain implied nonedges but do not contain any non-trivial rigid subgraphs, or \emph{nucleations}: some of the constructions and proofs apply to 3-dimensional abstract rigidity matroids with their respective definitions of nucleations and implied nonedges. The first motivation for the inductive constructions of this paper, which generate an especially intractable class of flexible circuits, is to illuminate further obstacles to settlin…

Why is this a case that the Japanese Railway thinks about in their ticket prices?

Indoor Fluid Antenna Systems Enabled by Layout-Specific Modeling and Group Relative Policy Optimization
Tong Zhang, Qianren Li, Shuai Wang, Wanli Ni, Jiliang Zhang, Rui Wang, Kai-Kit Wong, Chan-Byoung Chae
https://arxiv.org/abs/2509.15006

Indoor Fluid Antenna Systems Enabled by Layout-Specific Modeling and Group Relative Policy Optimization
The fluid antenna system (FAS) revolutionizes wireless communications by employing position-flexible antennas that dynamically optimize channel conditions and mitigate multipath fading. This innovation is particularly valuable in indoor environments, where signal propagation is severely degraded due to structural obstructions and complex multipath reflections. In this paper, we study the channel modeling and joint optimization of antenna positioning, beamforming, and power allocation for indoor…

Approximate Factor Model with S-vine Copula Structure
Jialing Han, Yu-Ning Li
https://arxiv.org/abs/2508.11619 https://arxiv.org/pdf/2508.11619

Approximate Factor Model with S-vine Copula Structure
We propose a novel framework for approximate factor models that integrates an S-vine copula structure to capture complex dependencies among common factors. Our estimation procedure proceeds in two steps: first, we apply principal component analysis (PCA) to extract the factors; second, we employ maximum likelihood estimation that combines kernel density estimation for the margins with an S-vine copula to model the dependence structure. Jointly fitting the S-vine copula with the margins yields a…

Replaced article(s) found for cs.DC. https://arxiv.org/list/cs.DC/new
[1/1]:
- Temporal-Aware GPU Resource Allocation for Distributed LLM Inference via Reinforcement Learning
Chengze Du, Zhiwei Yu, Heng Xu, Haojie Wang, Bo liu, Jialong Li