Tootfinder

Urban Demons III 👻
城市鬼魂 III 👻
📷 Nikon F4E
🎞️ Rollei RPX 400
If you like my work, buy me a coffee from PayPal #filmphotography

Fascists, cryptobros, young men who play tons of video games and have very little ethical thinking skill and frame everything as a competition to be won, seasoned software engineers, accelerationists, business guys, Business Guy Grifters, hyper-neoliberal technocrats, wannabe software engineers, kids who dream of creating video games, product designers who want to prototype things, capitalist hangers-on and investmentbros who are looking for the next gamble for their money, Chinese tech company employees, third world techies who use these tools to be able to play at the rich countries tech industry table, edgy young men who want to “decensor" everything including open models, tech enthusiasts who want to try every new thing.
And very, _very_ few women. And very, very few experts.

Just made a mistake on page 40 of a #LEGO build that turned out to be wrong, but it didn't interfere with anything until page 242. It was a but janky, but thankfully I didn't need to unbuild everything in between to fix it. Lego puts a huge amount of attention into the design of their instructions, but things like this are pretty hard to catch. I was building quickly and assumed a beam should go on symmetrically when actually it needed to be off-center.

New on #blog: "Money isn’t going to solve the #burnout problem"
"""
The xz-utils backdoor situation brought the problem of FLOSS maintained burnout into the daylight. This in turn lead to numerous discussion on how to solve the problem, and the recurring theme was funding maintenance work.
While I’m definitely not opposed to giving people money for their FLOSS work, if you think that throwing some bucks will actually solve the problem, and especially if you think that you can just throw them once and then forget, I have bad news for you: it won’t. Surely, money is a big part of the problem, but it’s not the only reason people are getting burned out. It’s a systemic problem, and it’s in need of systemic solution, and that’s involves a lot of hard work undo everything that’s happened in the last, say, 20 years.
But let’s start at the beginning and ask the important question: why do people make free software?
"""
#FreeSoftware #OpenSource #AI #NoAI #LLM #NoLLM #Gentoo

Replaced article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new
[4/5]:
- Retrieving Climate Change Disinformation by Narrative
Upravitelev, Solopova, Jakob, Sahitaj, M\"oller, Schmitt
https://arxiv.org/abs/2603.22015 https://mastoxiv.page/@arXiv_csCL_bot/116283633674519408
- PaperVoyager : Building Interactive Web with Visual Language Models
Dasen Dai, Biao Wu, Meng Fang, Wenhao Wang
https://arxiv.org/abs/2603.22999 https://mastoxiv.page/@arXiv_csCL_bot/116289015432093128
- Continual Robot Skill and Task Learning via Dialogue
Weiwei Gu, Suresh Kondepudi, Anmol Gupta, Lixiao Huang, Nakul Gopalan
https://arxiv.org/abs/2409.03166 https://mastoxiv.page/@arXiv_csRO_bot/113089412115632702
- Shifting Perspectives: Steering Vectors for Robust Bias Mitigation in LLMs
Zara Siddique, Irtaza Khalid, Liam D. Turner, Luis Espinosa-Anke
https://arxiv.org/abs/2503.05371 https://mastoxiv.page/@arXiv_csLG_bot/114136994263573386
- SkillFlow: Scalable and Efficient Agent Skill Retrieval System
Fangzhou Li, Pagkratios Tagkopoulos, Ilias Tagkopoulos
https://arxiv.org/abs/2504.06188 https://mastoxiv.page/@arXiv_csAI_bot/114306773220502860
- Large Language Models for Computer-Aided Design: A Survey
Licheng Zhang, Bach Le, Naveed Akhtar, Siew-Kei Lam, Tuan Ngo
https://arxiv.org/abs/2505.08137 https://mastoxiv.page/@arXiv_csLG_bot/114504972217393639
- Structured Agent Distillation for Large Language Model
Liu, Kong, Dong, Yang, Li, Tang, Yuan, Niu, Zhang, Zhao, Lin, Huang, Wang
https://arxiv.org/abs/2505.13820 https://mastoxiv.page/@arXiv_csLG_bot/114544636506163783
- VLM-3R: Vision-Language Models Augmented with Instruction-Aligned 3D Reconstruction
Fan, Zhang, Li, Zhang, Chen, Hu, Wang, Qu, Zhou, Wang, Yan, Xu, Theiss, Chen, Li, Tu, Wang, Ranjan
https://arxiv.org/abs/2505.20279 https://mastoxiv.page/@arXiv_csCV_bot/114578817567171199
- Learning to Diagnose Privately: DP-Powered LLMs for Radiology Report Classification
Bhattacharjee, Tian, Rubin, Lo, Merchant, Hanson, Gounley, Tandon
https://arxiv.org/abs/2506.04450 https://mastoxiv.page/@arXiv_csCR_bot/114635189706505648
- L-MARS: Legal Multi-Agent Workflow with Orchestrated Reasoning and Agentic Search
Ziqi Wang, Boqin Yuan
https://arxiv.org/abs/2509.00761 https://mastoxiv.page/@arXiv_csAI_bot/115140304787881576
- Your Models Have Thought Enough: Training Large Reasoning Models to Stop Overthinking
Han, Huang, Liao, Jiang, Lu, Zhao, Wang, Zhou, Jiang, Liang, Zhou, Sun, Yu, Xiao
https://arxiv.org/abs/2509.23392 https://mastoxiv.page/@arXiv_csAI_bot/115293169353788311
- Person-Centric Annotations of LAION-400M: Auditing Bias and Its Transfer to Models
Leander Girrbach, Stephan Alaniz, Genevieve Smith, Trevor Darrell, Zeynep Akata
https://arxiv.org/abs/2510.03721 https://mastoxiv.page/@arXiv_csCV_bot/115332690912652473
- Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models
Zhang, Hu, Upasani, Ma, Hong, Kamanuru, Rainton, Wu, Ji, Li, Thakker, Zou, Olukotun
https://arxiv.org/abs/2510.04618 https://mastoxiv.page/@arXiv_csLG_bot/115332999596603375
- Mitigating Premature Exploitation in Particle-based Monte Carlo for Inference-Time Scaling
Giannone, Xu, Nayak, Awhad, Sudalairaj, Xu, Srivastava
https://arxiv.org/abs/2510.05825 https://mastoxiv.page/@arXiv_csLG_bot/115338159696513898
- Complete asymptotic type-token relationship for growing complex systems with inverse power-law co...
Pablo Rosillo-Rodes, Laurent H\'ebert-Dufresne, Peter Sheridan Dodds
https://arxiv.org/abs/2511.02069 https://mastoxiv.page/@arXiv_physicssocph_bot/115496283627867809
- ViPRA: Video Prediction for Robot Actions
Sandeep Routray, Hengkai Pan, Unnat Jain, Shikhar Bahl, Deepak Pathak
https://arxiv.org/abs/2511.07732 https://mastoxiv.page/@arXiv_csRO_bot/115535941444003568
- AISAC: An Integrated multi-agent System for Transparent, Retrieval-Grounded Scientific Assistance
Chandrachur Bhattacharya, Sibendu Som
https://arxiv.org/abs/2511.14043
- VideoARM: Agentic Reasoning over Hierarchical Memory for Long-Form Video Understanding
Yufei Yin, Qianke Meng, Minghao Chen, Jiajun Ding, Zhenwei Shao, Zhou Yu
https://arxiv.org/abs/2512.12360 https://mastoxiv.page/@arXiv_csCV_bot/115729238732682644
- RadImageNet-VQA: A Large-Scale CT and MRI Dataset for Radiologic Visual Question Answering
L\'eo Butsanets, Charles Corbi\`ere, Julien Khlaut, Pierre Manceron, Corentin Dancette
https://arxiv.org/abs/2512.17396 https://mastoxiv.page/@arXiv_csCV_bot/115762705911757243
- Measuring all the noises of LLM Evals
Sida Wang
https://arxiv.org/abs/2512.21326 https://mastoxiv.page/@arXiv_csLG_bot/115779597137785637
toXiv_bot_toot