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@heiseonline@social.heise.de
2026-05-10 09:19:00

KI-Bots als Täter-Software: Wenn Algorithmen Kindesmissbrauch simulieren
Auf Plattformen wie Chub AI werden Sprachmodelle trainiert, sexualisierte Gewalt gegen Kinder darzustellen und Nutzer in Missbrauchsszenarien zu verwickeln.

@hex@kolektiva.social
2026-05-02 07:23:18

"It places page cache pages in a writable scatterlist, separated from the legitimate write region by nothing more than an offset boundary. The design assumes every AEAD algorithm will confine its writes to the intended destination, but nothing in the API enforces this, and nothing documents it as a requirement.
Unfortunately, one AEAD algorithm breaks this silent invariant."
"No other standard AEAD algorithm in the kernel [uses memory that doesn't belong to it as a scratch pad]. GCM, CCM, and regular authenc all confine their writes to the legitimate output area. authencesn alone writes past the boundary."
I'm actually amazed that there's only one bug here. Somehow almost everyone just managed to do the right thing, despite no mechanism enforcing it and no documentation describing it. That's just amazing. It's a testament to the skill of those developers, despite an incredibly bad design.
#copyfail

A newly expanded policy from the Trump administration could require travelers from five World Cup-qualified countries to front a bond of up to $15,000 in order to enter the United States for the tournament.
Visa bonds operate like security deposits:
a one-time payment meant to be refunded after a traveler exits the US under the terms of their visa.
The amounts generally run between $5,000 and $15,000, and are required for passport holders from certain countries to enter the…

@kuba@toot.kuba-orlik.name
2026-04-24 07:56:37

> The Commission copied and pasted an amendment suggested by Microsoft and the lobby group Digital Europe. The aim: To prevent NGOs from obtaining information on energy-hungry data centers in the face of growing resistance
algorithmwatch.org/en/copy-pas

@ocrampal@mastodon.social
2026-02-21 17:19:08

Society has lost its direction. We are now driving blind, and the reason is reductionism. We’ve become so obsessed with breaking the world into tiny parts that we’ve forgotten how the whole thing actually hangs together.
ocrampal.com/too-narrow-to-be-

@arXiv_csPF_bot@mastoxiv.page
2026-04-01 08:01:42

Closed-Loop Integrated Sensing, Communication, and Control for Efficient Drone Flight
Jingli Li, Yiyan Ma, Bo Ai, Wei Chen, Weijie Yuan, Qingqing Cheng, Tongyang Xu, Guoyu Ma, Mi Yang, Yunlong Lu, Wenwei Yue, Christos Masouros, Zhangdui Zhong
arxiv.org/abs/2603.29220 arxiv.org/pdf/2603.29220 arxiv.org/html/2603.29220
arXiv:2603.29220v1 Announce Type: new
Abstract: Low-altitude wireless networks (LAWN) require drones to follow specific trajectories controlled by ground base stations (GBSs). However, given complex low-altitude channel conditions and limited spectrum and power resources, sensing errors and wireless link unreliability cannot be ignored, leading to trajectory deviations that threaten flight safety. To address this issue, this paper proposes an integrated sensing-communication-control (ISCC) closed-loop trajectory tracking approach, aiming to reveal the coupling mechanisms among communication, sensing, and control during drone flight. In detail, we incorporate sensing errors in trajectory state estimation, packet losses in control command transmission, and finite blocklength transmission effects into the closed-loop dynamics. First, through theoretical analysis, we identify the dominant role of the time-frequency resources allocated to control in ensuring system stability and derive a lower bound on the resources required to guarantee stable operation. Second, to minimize tracking error, we formulate a time-frequency resource allocation optimization problem for the sensing, communication, and control components, subject to constraints on communication rate and closed-loop stability. Accordingly, a solution algorithm based on successive convex approximation is proposed. Third, simulation results indicate that once stability is ensured, system performance is primarily determined by sensing accuracy, with the trajectory tracking error exhibiting an approximately linear dependence on the position error bound. Finally, it is shown that the proposed ISCC scheme avoids trajectory divergence under FBL transmission compared with ISCC designs ignoring control packet loss, and could achieve decimeter-level average tracking accuracy, reducing the error to only 17.37% of that observed in the baseline global navigation satellite system scheme.
toXiv_bot_toot

@relcfp@mastodon.social
2026-03-03 07:43:17

ALGORITHM OR ALLY? AI, GLOBAL ENGLISH, AND THE FUTURE OF LANGUAGE LEARNING call-for-papers.sas.upenn.edu/

@arXiv_csCL_bot@mastoxiv.page
2026-03-31 10:40:54

Crosslisted article(s) found for cs.CL. arxiv.org/list/cs.CL/new
[1/2]:
- Bridge-RAG: An Abstract Bridge Tree Based Retrieval Augmented Generation Algorithm With Cuckoo Fi...
Li, Liu, Zong, Tao, Dai, Ren, Liu, Jiang, Yang
arxiv.org/abs/2603.26668 mastoxiv.page/@arXiv_csIR_bot/
- SRAG: RAG with Structured Data Improves Vector Retrieval
Shalin Shah, Srikanth Ryali, Ramasubbu Venkatesh
arxiv.org/abs/2603.26670 mastoxiv.page/@arXiv_csIR_bot/
- LITTA: Late-Interaction and Test-Time Alignment for Visually-Grounded Multimodal Retrieval
Seonok Kim
arxiv.org/abs/2603.26683 mastoxiv.page/@arXiv_csIR_bot/
- Agentic AI for Human Resources: LLM-Driven Candidate Assessment
Yuksel, Anees, Elneima, Hewavitharana, Al-Badrashiny, Sawaf
arxiv.org/abs/2603.26710 mastoxiv.page/@arXiv_csIR_bot/
- SEAR: Schema-Based Evaluation and Routing for LLM Gateways
Zecheng Zhang, Han Zheng, Yue Xu
arxiv.org/abs/2603.26728 mastoxiv.page/@arXiv_csDB_bot/
- SleepVLM: Explainable and Rule-Grounded Sleep Staging via a Vision-Language Model
Guifeng Deng, Pan Wang, Jiquan Wang, Shuying Rao, Junyi Xie, Wanjun Guo, Tao Li, Haiteng Jiang
arxiv.org/abs/2603.26738 mastoxiv.page/@arXiv_csCV_bot/
- Aesthetic Assessment of Chinese Handwritings Based on Vision Language Models
Chen Zheng, Yuxuan Lai, Haoyang Lu, Wentao Ma, Jitao Yang, Jian Wang
arxiv.org/abs/2603.26768 mastoxiv.page/@arXiv_csCV_bot/
- Learning to Select Visual In-Context Demonstrations
Eugene Lee, Yu-Chi Lin, Jiajie Diao
arxiv.org/abs/2603.26775 mastoxiv.page/@arXiv_csLG_bot/
- CRISP: Characterizing Relative Impact of Scholarly Publications
Hannah Collison, Benjamin Van Durme, Daniel Khashabi
arxiv.org/abs/2603.26791 mastoxiv.page/@arXiv_csDL_bot/
- GroupRAG: Cognitively Inspired Group-Aware Retrieval and Reasoning via Knowledge-Driven Problem S...
Xinyi Duan, Yuanrong Tang, Jiangtao Gong
arxiv.org/abs/2603.26807 mastoxiv.page/@arXiv_csIR_bot/
- In your own words: computationally identifying interpretable themes in free-text survey data
Jenny S Wang, Aliya Saperstein, Emma Pierson
arxiv.org/abs/2603.26930 mastoxiv.page/@arXiv_csCY_bot/
- Multilingual Stutter Event Detection for English, German, and Mandarin Speech
Felix Haas, Sebastian P. Bayerl
arxiv.org/abs/2603.26939 mastoxiv.page/@arXiv_csSD_bot/
- FormalProofBench: Can Models Write Graduate Level Math Proofs That Are Formally Verified?
Ravi, Ying, Nesterov, Krishnan, Uskuplu, Xia, Aswedige, Nashold
arxiv.org/abs/2603.26996 mastoxiv.page/@arXiv_csAI_bot/
- PHONOS: PHOnetic Neutralization for Online Streaming Applications
Waris Quamer, Mu-Ruei Tseng, Ghady Nasrallah, Ricardo Gutierrez-Osuna
arxiv.org/abs/2603.27001 mastoxiv.page/@arXiv_eessAS_bo
- ChartNet: A Million-Scale, High-Quality Multimodal Dataset for Robust Chart Understanding
Jovana Kondic, et al.
arxiv.org/abs/2603.27064 mastoxiv.page/@arXiv_csCV_bot/
- daVinci-LLM:Towards the Science of Pretraining
Qin, Liu, Mi, Xie, Huang, Si, Lu, Feng, Wu, Liu, Luo, Hou, Guo, Qiao, Liu
arxiv.org/abs/2603.27164 mastoxiv.page/@arXiv_csAI_bot/
- LightMover: Generative Light Movement with Color and Intensity Controls
Zhou, Wang, Kim, Shu, Yu, Hold-Geoffroy, Chaturvedi, Wu, Lin, Cohen
arxiv.org/abs/2603.27209 mastoxiv.page/@arXiv_csCV_bot/
- Self-evolving AI agents for protein discovery and directed evolution
Tan, Zhang, Li, Yu, Zhong, Zhou, Dong, Hong
arxiv.org/abs/2603.27303 mastoxiv.page/@arXiv_csAI_bot/
- Inference-Time Structural Reasoning for Compositional Vision-Language Understanding
Amartya Bhattacharya
arxiv.org/abs/2603.27349 mastoxiv.page/@arXiv_csCV_bot/
- LLM Readiness Harness: Evaluation, Observability, and CI Gates for LLM/RAG Applications
Alexandre Cristov\~ao Maiorano
arxiv.org/abs/2603.27355 mastoxiv.page/@arXiv_csAI_bot/
- Heterogeneous Debate Engine: Identity-Grounded Cognitive Architecture for Resilient LLM-Based Eth...
Jakub Mas{\l}owski, Jaros{\l}aw A. Chudziak
arxiv.org/abs/2603.27404 mastoxiv.page/@arXiv_csAI_bot/
toXiv_bot_toot

@relcfp@mastodon.social
2026-03-02 06:20:30

ALGORITHM OR ALLY? AI, GLOBAL ENGLISH, AND THE FUTURE OF LANGUAGE LEARNING call-for-papers.sas.upenn.edu/

@relcfp@mastodon.social
2026-03-02 07:28:18

ALGORITHM OR ALLY? AI, GLOBAL ENGLISH, AND THE FUTURE OF LANGUAGE LEARNING call-for-papers.sas.upenn.edu/