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@tiotasram@kolektiva.social
2025-06-21 02:34:13

Why AI can't possibly make you more productive; long
#AI and "productivity", some thoughts:
Productivity is a concept that isn't entirely meaningless outside the context of capitalism, but it's a concept that is heavily inflected in a capitalist context. In many uses today it effectively means "how much you can satisfy and/or exceed your boss' expectations." This is not really what it should mean: even in an anarchist utopia, people would care about things like how many shirts they can produce in a week, although in an "I'd like to voluntarily help more people" way rather than an "I need to meet this quota to earn my survival" way. But let's roll with this definition for a second, because it's almost certainly what your boss means when they say "productivity", and understanding that word in a different (even if truer) sense is therefore inherently dangerous.
Accepting "productivity" to mean "satisfying your boss' expectations," I will now claim: the use of generative AI cannot increase your productivity.
Before I dive in, it's imperative to note that the big generative models which most people think of as constituting "AI" today are evil. They are 1: pouring fuel on our burning planet, 2: psychologically strip-mining a class of data laborers who are exploited for their precarity, 3: enclosing, exploiting, and polluting the digital commons, and 4: stealing labor from broad classes of people many of whom are otherwise glad to give that labor away for free provided they get a simple acknowledgement in return. Any of these four "ethical issues" should be enough *alone* to cause everyone to simply not use the technology. These ethical issues are the reason that I do not use generative AI right now, except for in extremely extenuating circumstances. These issues are also convincing for a wide range of people I talk to, from experts to those with no computer science background. So before I launch into a critique of the effectiveness of generative AI, I want to emphasize that such a critique should be entirely unnecessary.
But back to my thesis: generative AI cannot increase your productivity, where "productivity" has been defined as "how much you can satisfy and/or exceed your boss' expectations."
Why? In fact, what the fuck? Every AI booster I've met has claimed the opposite. They've given me personal examples of time saved by using generative AI. Some of them even truly believe this. Sometimes I even believe they saved time without horribly compromising on quality (and often, your boss doesn't care about quality anyways if the lack of quality is hard to measure of doesn't seem likely to impact short-term sales/feedback/revenue). So if generative AI genuinely lets you write more emails in a shorter period of time, or close more tickets, or something else along these lines, how can I say it isn't increasing your ability to meet your boss' expectations?
The problem is simple: your boss' expectations are not a fixed target. Never have been. In virtue of being someone who oversees and pays wages to others under capitalism, your boss' game has always been: pay you less than the worth of your labor, so that they can accumulate profit and this more capital to remain in charge instead of being forced into working for a wage themselves. Sure, there are layers of manservant caught in between who aren't fully in this mode, but they are irrelevant to this analysis. It matters not how much you please your manager if your CEO thinks your work is not worth the wages you are being paid. And using AI actively lowers the value of your work relative to your wages.
Why do I say that? It's actually true in several ways. The most obvious: using generative AI lowers the quality of your work, because the work it produces is shot through with errors, and when your job is reduced to proofreading slop, you are bound to tire a bit, relax your diligence, and let some mistakes through. More than you would have if you are actually doing and taking pride in the work. Examples are innumerable and frequent, from journalists to lawyers to programmers, and we laugh at them "haha how stupid to not check whether the books the AI reviewed for you actually existed!" but on a deeper level if we're honest we know we'd eventually make the same mistake ourselves (bonus game: spot the swipe-typing typos I missed in this post; I'm sure there will be some).
But using generative AI also lowers the value of your work in another much more frightening way: in this era of hype, it demonstrates to your boss that you could be replaced by AI. The more you use it, and no matter how much you can see that your human skills are really necessary to correct its mistakes, the more it appears to your boss that they should hire the AI instead of you. Or perhaps retain 10% of the people in roles like yours to manage the AI doing the other 90% of the work. Paradoxically, the *more* you get done in terms of raw output using generative AI, the more it looks to your boss as if there's an opportunity to get enough work done with even fewer expensive humans. Of course, the decision to fire you and lean more heavily into AI isn't really a good one for long-term profits and success, but the modern boss did not get where they are by considering long-term profits. By using AI, you are merely demonstrating your redundancy, and the more you get done with it, the more redundant you seem.
In fact, there's even a third dimension to this: by using generative AI, you're also providing its purveyors with invaluable training data that allows them to make it better at replacing you. It's generally quite shitty right now, but the more use it gets by competent & clever people, the better it can become at the tasks those specific people use it for. Using the currently-popular algorithm family, there are limits to this; I'm not saying it will eventually transcend the mediocrity it's entwined with. But it can absolutely go from underwhelmingly mediocre to almost-reasonably mediocre with the right training data, and data from prompting sessions is both rarer and more useful than the base datasets it's built on.
For all of these reasons, using generative AI in your job is a mistake that will likely lead to your future unemployment. To reiterate, you should already not be using it because it is evil and causes specific and inexcusable harms, but in case like so many you just don't care about those harms, I've just explained to you why for entirely selfish reasons you should not use it.
If you're in a position where your boss is forcing you to use it, my condolences. I suggest leaning into its failures instead of trying to get the most out of it, and as much as possible, showing your boss very clearly how it wastes your time and makes things slower. Also, point out the dangers of legal liability for its mistakes, and make sure your boss is aware of the degree to which any of your AI-eager coworkers are producing low-quality work that harms organizational goals.
Also, if you've read this far and aren't yet of an anarchist mindset, I encourage you to think about the implications of firing 75% of (at least the white-collar) workforce in order to make more profit while fueling the climate crisis and in most cases also propping up dictatorial figureheads in government. When *either* the AI bubble bursts *or* if the techbros get to live out the beginnings of their worker-replacement fantasies, there are going to be an unimaginable number of economically desperate people living in increasingly expensive times. I'm the kind of optimist who thinks that the resulting social crucible, though perhaps through terrible violence, will lead to deep social changes that effectively unseat from power the ultra-rich that continue to drag us all down this destructive path, and I think its worth some thinking now about what you might want the succeeding stable social configuration to look like so you can advocate towards that during points of malleability.
As others have said more eloquently, generative AI *should* be a technology that makes human lives on average easier, and it would be were it developed & controlled by humanists. The only reason that it's not, is that it's developed and controlled by terrible greedy people who use their unfairly hoarded wealth to immiserate the rest of us in order to maintain their dominance. In the long run, for our very survival, we need to depose them, and I look forward to what the term "generative AI" will mean after that finally happens.

@smurthys@hachyderm.io
2025-06-20 18:09:43

Successful software engineers have eyes on their back as well.
#quality #softwareEngineering #saying

@Techmeme@techhub.social
2025-06-22 05:15:45

Adobe Labs launches Project Indigo, a free computational photography app for iPhones that captures a burst of images and combines them into a high-quality photo (Jay Peters/The Verge)
theverge.com/news/690115/adobe

@arXiv_csCV_bot@mastoxiv.page
2025-06-19 08:22:09

Demystifying the Visual Quality Paradox in Multimodal Large Language Models
Shuo Xing, Lanqing Guo, Hongyuan Hua, Seoyoung Lee, Peiran Li, Yufei Wang, Zhangyang Wang, Zhengzhong Tu
arxiv.org/abs/2506.15645

@primonatura@mstdn.social
2025-06-21 10:00:55

"xAI is facing a lawsuit for operating over 400 MW of gas turbines without permits"
#xAI #AI #ArtificialIntelligence

@mgorny@pol.social
2025-06-21 05:49:07

Osobiście, polecałbym trzymać się z daleka od "#Python Code Quality Authority". Projekty tej organizacji zostały właściwie przejęte przez wyjątkowo toksyczną osobę. #Ruff to dobra alternatywa, z bardzo przyjaznymi autorami.

@arXiv_csAI_bot@mastoxiv.page
2025-06-18 08:10:19

QUEST: Quality-aware Semi-supervised Table Extraction for Business Documents
Eliott Thomas, Mickael Coustaty, Aurelie Joseph, Gaspar Deloin, Elodie Carel, Vincent Poulain D'Andecy, Jean-Marc Ogier
arxiv.org/abs/2506.14568

@al3x@hachyderm.io
2025-06-21 12:32:15

Do I know anyone using DayOne? I am curious if the application has seen any improvements in the last couple of years.
I have abandoned it 3 years ago due to “too many thin but deep paper cuts” mostly around the Markdown editor which led me to feel like the focus of the team behind it is somewhere else.
I have been using Bear meanwhile. Which has been absolutely fabulous in terms of the quality of the editor. I am missing some features in Bear that I really like & appreciate:
1) automatic location; 2) on this day; 3) show entries from location.

@blakes7bot@mas.torpidity.net
2025-06-21 06:19:12

#Blakes7 Series C, Episode 10 - Ultraworld
AVON: When the planet was on the screen, did anyone notice Cally's reaction?
VILA: I didn't.
AVON: You were too busy teaching Orac nursery rhymes.
VILA: Riddles.

Claude 3.7 describes the image as: "The image shows a person with dark, short hair styled in a typical 1970s-80s fashion. They're wearing what appears to be a high-necked costume with a brown textured material featuring some decorative elements or studs.

The lighting and film quality suggest this is from a British science fiction television production of that era. The costume design has that distinctive retro sci-fi aesthetic common in shows from this period.

The scene appears to be from a st…
@frankel@mastodon.top
2025-06-19 08:08:04

How Docs-as-Code Helped #Pinterest Improve #Documentation Quality
infoq.com/news/2025/06…

@arXiv_eessIV_bot@mastoxiv.page
2025-06-18 08:48:42

Breaking the Multi-Enhancement Bottleneck: Domain-Consistent Quality Enhancement for Compressed Images
Qunliang Xing, Mai Xu, Jing Yang, Shengxi Li
arxiv.org/abs/2506.14152

@cowboys@darktundra.xyz
2025-06-21 17:26:43

Passing on name CBs shows Cowboys still haven't shaken their cheap, bargain-shopping ways cowboyswire.usatoday.com/story

@azonenberg@ioc.exchange
2025-06-20 06:10:21

Tonight's quick ngscopeclient dev fix: GPU accelerating the demo scope.
It now runs quite a few times faster than before (and is faster to process subsequent filter blocks on, since the input data is now GPU resident).
Not super critical but a nice quality-of-life fix since I use the demo scope as a data source for development pretty often.

ngscopeclient displaying a sinewave, some digital waveforms, and an eye pattern
@poppastring@dotnet.social
2025-04-19 19:35:25

A post from the archive 📫:
A better vision for Central Ohio
#musings

@arXiv_csSD_bot@mastoxiv.page
2025-06-17 10:01:37

Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment
Wei Wang, Wangyou Zhang, Chenda Li, Jiatong Shi, Shinji Watanabe, Yanmin Qian
arxiv.org/abs/2506.12260

@arXiv_csSE_bot@mastoxiv.page
2025-06-18 08:59:19

Quality Assessment of Python Tests Generated by Large Language Models
Victor Alves, Carla Bezerra, Ivan Machado, Larissa Rocha, T\'assio Virg\'inio, Publio Silva
arxiv.org/abs/2506.14297

@YaleDivinitySchool@mstdn.social
2025-05-19 17:21:05

Join us now for the Yale Divinity School Diploma Ceremony live broadcast! vimeo.com/yaledivinityschool

@seav@en.osm.town
2025-06-19 19:04:13

Earlier this month, #TomPatterson released a free (public domain) print-quality physical map of maritime Southeast Asia. It could actually almost double as a map of SEA except the northern part of Myanmar is cut off. 🗺️

@mia@hcommons.social
2025-06-11 20:24:27

Very excited about this! Code to access GRIN will help lots of Google Books partners, and the example might open other doors, as well as the obvious benefits of access to data!
'Institutional Books 1.0: A 242B token dataset from Harvard Library's collections, refined for accuracy and usability' arxiv.org/abs/2506…

@arXiv_csHC_bot@mastoxiv.page
2025-06-19 08:19:44

Impact of a Deployed LLM Survey Creation Tool through the IS Success Model
Peng Jiang, Vinicius Cezar Monteiro de Lira, Antonio Maiorino
arxiv.org/abs/2506.14809

@NFL@darktundra.xyz
2025-06-20 11:54:16

Inside Los Angeles Rams minicamp in Maui: 'This is about being able to get some good quality time with each other' espn.com/nfl/story/_/id/455399

@Mediagazer@mstdn.social
2025-06-19 01:45:56

Q&A with Ashokan Studios' Justin Wells on making "high quality" conservative content, the second season of his doc about Trump's campaign and second term, more (Peter Kiefer/The Hollywood Reporter)
hollywoodrepor…

@arXiv_csCL_bot@mastoxiv.page
2025-06-18 09:07:29

Massive Supervised Fine-tuning Experiments Reveal How Data, Layer, and Training Factors Shape LLM Alignment Quality
Yuto Harada, Yusuke Yamauchi, Yusuke Oda, Yohei Oseki, Yusuke Miyao, Yu Takagi
arxiv.org/abs/2506.14681

@arXiv_physicssocph_bot@mastoxiv.page
2025-06-16 09:27:49

Modeling Urban Air Quality Using Taxis as Sensors
Anastasios Noulas, Yasin Acikmese, Charles QC LI, Milan Y. Patel, Shazia Ayn Babul, Ronald C. Cohen, Renaud Lambiotte, Marta C. Gonzalez
arxiv.org/abs/2506.11720

@arXiv_csDL_bot@mastoxiv.page
2025-06-17 09:28:47

Implicit and Explicit Research Quality Score Probabilities from ChatGPT
Mike Thelwall, Yunhan Yang
arxiv.org/abs/2506.13525

@arXiv_csGR_bot@mastoxiv.page
2025-06-16 07:38:29

CGVQM D: Computer Graphics Video Quality Metric and Dataset
Akshay Jindal, Nabil Sadaka, Manu Mathew Thomas, Anton Sochenov, Anton Kaplanyan
arxiv.org/abs/2506.11546

@arXiv_csCE_bot@mastoxiv.page
2025-06-16 07:18:49

CLEAN-MI: A Scalable and Efficient Pipeline for Constructing High-Quality Neurodata in Motor Imagery Paradigm
Dingkun Liu, Zhu Chen, Dongrui Wu
arxiv.org/abs/2506.11830

@arXiv_csMM_bot@mastoxiv.page
2025-06-12 07:43:31

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment
Amritha Premkumar, Prajit T Rajendran, Vignesh V Menon
arxiv.org/abs/2506.09795

@candidexmedia@mastodon.design
2025-04-20 00:37:17

This month, I (soft) launched the redesigned candide.media website, and (officially) launched the "Frugal Filmmaking: Video Editing on a Budget" course! 🥳
The hybrid course (happening both in-person and virtually) teaches participants how to edit video using @…

Photo of an open laptop showing the online workshop portal that participants can consult between workshops to review what they've learned.
@matthiasott@mastodon.social
2025-06-16 19:11:01

☕️ I can drink coffee all day, also in the evening, and fall asleep without any problems (although my sleep quality might suffer).
🧉 But give me a cup of mate, and I’ll be wide awake until 3 am. 🪩🕺
😂

@arXiv_eessAS_bot@mastoxiv.page
2025-06-17 10:59:30

ZipVoice: Fast and High-Quality Zero-Shot Text-to-Speech with Flow Matching
Han Zhu, Wei Kang, Zengwei Yao, Liyong Guo, Fangjun Kuang, Zhaoqing Li, Weiji Zhuang, Long Lin, Daniel Povey
arxiv.org/abs/2506.13053

@jamesthebard@social.linux.pizza
2025-06-17 22:31:25

So, wrote up a quick guide on how to put a PiKVM onto a VLAN via `systemd-network`. It works though I'll admit the quality is slightly lower than normal due to beers...
blog.jamesthebard.net/posts/pi

@arXiv_qbioGN_bot@mastoxiv.page
2025-05-21 10:03:46

This arxiv.org/abs/2505.12638 has been replaced.
initial toot: mastoxiv.page/@arXiv_qbi…

@arXiv_csCV_bot@mastoxiv.page
2025-06-17 10:22:25

Fine-Grained HDR Image Quality Assessment From Noticeably Distorted to Very High Fidelity
Mohsen Jenadeleh, Jon Sneyers, Davi Lazzarotto, Shima Mohammadi, Dominik Keller, Atanas Boev, Rakesh Rao Ramachandra Rao, Ant\'onio Pinheiro, Thomas Richter, Alexander Raake, Touradj Ebrahimi, Jo\~ao Ascenso, Dietmar Saupe
arxiv…

@Dragofix@veganism.social
2025-06-05 00:53:14

Wildfire smoke could bring hazy skies to Massachusetts, possible air quality issues phys.org/news/2025-06-wildfire
Air quality worsens in eastern US as Canadian wildfire smoke hangs over Midwest

@arXiv_csRO_bot@mastoxiv.page
2025-06-19 08:33:33

FEAST: A Flexible Mealtime-Assistance System Towards In-the-Wild Personalization
Rajat Kumar Jenamani, Tom Silver, Ben Dodson, Shiqin Tong, Anthony Song, Yuting Yang, Ziang Liu, Benjamin Howe, Aimee Whitneck, Tapomayukh Bhattacharjee
arxiv.org/abs/2506.14968

@arXiv_csCR_bot@mastoxiv.page
2025-06-13 07:29:40

Symbolic Generation and Modular Embedding of High-Quality abc-Triples
Michael A. Idowu
arxiv.org/abs/2506.10039 arxiv…

@arXiv_csSE_bot@mastoxiv.page
2025-06-16 10:25:39

Classification of Quality Characteristics in Online User Feedback using Linguistic Analysis, Crowdsourcing and LLMs
Eduard C. Groen, Fabiano Dalpiaz, Martijn van Vliet, Boris Winter, Joerg Doerr, Sjaak Brinkkemper
arxiv.org/abs/2506.11722

@arXiv_physicsoptics_bot@mastoxiv.page
2025-06-18 10:03:08

MobileHolo: A Lightweight Complex-Valued Deformable CNN for High-Quality Computer-Generated Hologram
Xie Shuyang, Zhou Jie, Xu Bo, Wang Jun, Xu Renjing
arxiv.org/abs/2506.14542

@arXiv_csDB_bot@mastoxiv.page
2025-06-09 07:32:02

Stream DaQ: Stream-First Data Quality Monitoring
Vasileios Papastergios, Anastasios Gounaris
arxiv.org/abs/2506.06147

@gap@glammr.us
2025-06-18 10:36:21

Open Letter to CRL from the academic wing of #CripLib - ACRLog
acrlog.or…

@arXiv_physicsaccph_bot@mastoxiv.page
2025-05-21 07:33:06

The SPARTA project: toward a demonstrator facility for multistage plasma acceleration
C. A. Lindstr{\o}m, E. Adli, H. B. Anderson, P. Drobniak, D. Kalvik, F. Pe\~na, K. N. Sjobak
arxiv.org/abs/2505.14493

Enormous early-season wildfireshave erupted across the prairie provinces of Canada this week,
taxing local emergency response and threatening a long stretch of dangerous air quality across eastern North America.
The country’s largest fires
– the Bird River fire and the Border fire
– remain completely uncontained in northern Manitoba.
In Manitoba alone, wildfires have burned about 200,000 hectares already this year – already about three times the recent full-year …

@arXiv_csIR_bot@mastoxiv.page
2025-06-19 08:22:19

Next-User Retrieval: Enhancing Cold-Start Recommendations via Generative Next-User Modeling
Yu-Ting Lan, Yang Huo, Yi Shen, Xiao Yang, Zuotao Liu
arxiv.org/abs/2506.15267

@arXiv_csSI_bot@mastoxiv.page
2025-06-17 10:12:57

TwiUSD: A Benchmark Dataset and Structure-Aware LLM Framework for User Stance Detection
Fuaing Niu, Zini Chen, Zhiyu Xie, Genan Dai, Bowen Zhang
arxiv.org/abs/2506.13343

@berlinbuzzwords@floss.social
2025-05-13 14:00:08

Data warehouses, lakes, lakehouses, and more – our choices significantly affect operational costs and development speed. Join Lars Albertsson at Berlin Buzzwords to explore how different data processing paradigms impact deployment, failure handling, and data quality. Learn strategies to minimise costs and latency, bridge between paradigms, and enhance development iteration and operational efficiency.
Learn more:

Session title: All the DataOps, all the paradigms
Lars Albertsson
Join us for Berlin Buzzwords on June 15-17 at Kulturbrauerei or online / berlinbuzzwords.de.ds
@arXiv_csLG_bot@mastoxiv.page
2025-06-03 08:21:19

Datasheets Aren't Enough: DataRubrics for Automated Quality Metrics and Accountability
Genta Indra Winata, David Anugraha, Emmy Liu, Alham Fikri Aji, Shou-Yi Hung, Aditya Parashar, Patrick Amadeus Irawan, Ruochen Zhang, Zheng-Xin Yong, Jan Christian Blaise Cruz, Niklas Muennighoff, Seungone Kim, Hanyang Zhao, Sudipta Kar, Kezia Erina Suryoraharjo, M. Farid Adilazuarda, En-Shiun Annie Lee, Ayu Purwarianti, Derry Tanti Wijaya, Monojit Choudhury

@mgorny@social.treehouse.systems
2025-06-21 06:35:50

Nowadays in quality #Python: #Gentoo is running #ProtoBuf-related test suite via #PyTest-forked to workaround protobuf segfaulting during GC.
Of course, it implies random programs can segfault on exit too.
github.com/protocolbuffers/pro
gitweb.gentoo.org/repo/gentoo.

@arXiv_csSD_bot@mastoxiv.page
2025-06-19 08:35:28

A Comparative Evaluation of Deep Learning Models for Speech Enhancement in Real-World Noisy Environments
Md Jahangir Alam Khondkar, Ajan Ahmed, Masudul Haider Imtiaz, Stephanie Schuckers
arxiv.org/abs/2506.15000

@lysander07@sigmoid.social
2025-05-11 13:16:51

Next stop in our NLP timeline is 2013, the introduction of low dimensional dense word vectors - so-called "word embeddings" - based on distributed semantics, as e.g. word2vec by Mikolov et al. from Google, which enabled representation learning on text.
T. Mikolov et al. (2013). Efficient Estimation of Word Representations in Vector Space.

Slide from the Information Service Engineering 2025 lecture, lecture 02, Natural Language Processing 01, NLP Timeline. The timeline is in the middle of the slide from top to bottom, indicating a marker at 2013. On the left, a diagram is shown, displaying vectors  for "man" and "woman" in a 2D diagram. An arrow leades from the point of "man" to the point of "woman". Above it, there is also the point marked for "king" and the same difference vector is transferred from "man - > woman" to "king - ?…
@nelson@tech.lgbt
2025-06-16 01:14:53

Calamus 34 I dreamed in a dream
On the surface this short poem is a sort of City on a Hill vision. But I'm going to go with a more radical reading.
This poem reads to me as a fantasy of a gay society. A city of men, lovers, set apart from the rest of the world.
a city invincible to the attacks of the whole of the rest of the earth ...
the quality of robust love ...
the actions of the men of that city
And in all their looks and words.
I can't plausibly argue Whitman conceived of a city set apart in the way I imagine. Although all of Calamus is him constructing the idea of a society of lovers, comrades, brothers, robust love. That to me is very gay.
Intriguingly, in the unpublished Live Oak draft of this poem it is even more explicitly gay:
I saw them tenderly love each other ...
Nothing was greater there than manly love
It seems to me he dreamed a very gay city.

@arXiv_csNI_bot@mastoxiv.page
2025-06-19 08:28:24

CNN-Enabled Scheduling for Probabilistic Real-Time Guarantees in Industrial URLLC
Eman Alqudah, Ashfaq Khokhar
arxiv.org/abs/2506.14987

@wvmierlo@zirk.us
2025-06-20 16:44:56

St Edmunds churchyard, Pierrepont Holme Hall, February 2025
#photography #heritagephotography #churchyard #rustic

A bench in a sunlit, rustic churchard.
@samir@functional.computer
2025-06-14 17:15:04

@… @… Evidence strongly implies that quotas work. If you set a minimum diversity quota, on any given axis, it doesn’t just improve your quality (because e.g. women who stay in male-dominated industries tend to be way better than their male cou…

@arXiv_statML_bot@mastoxiv.page
2025-06-12 09:54:11

Assessing the Quality of Denoising Diffusion Models in Wasserstein Distance: Noisy Score and Optimal Bounds
Vahan Arsenyan, Elen Vardanyan, Arnak Dalalyan
arxiv.org/abs/2506.09681

@arXiv_csSE_bot@mastoxiv.page
2025-06-16 10:09:39

CoQuIR: A Comprehensive Benchmark for Code Quality-Aware Information Retrieval
Jiahui Geng, Fengyu Cai, Shaobo Cui, Qing Li, Liangwei Chen, Chenyang Lyu, Haonan Li, Derui Zhu, Walter Pretschner, Heinz Koeppl, Fakhri Karray
arxiv.org/abs/2506.11066

@jkohlmann@mastodon.social
2025-06-14 11:49:08

Shoutout to DxO PhotoLab. Got it earlier this year with ViewPoint & FilmPack. Very impressed with the speed, quality, interface, and capabilities. Some pro tips:
1. I also got PureRAW, but this year they brought their latest DeepPRIME 3 demosaicing & denoising solution to PhotoLab at no extra cost

@arXiv_csCV_bot@mastoxiv.page
2025-06-18 09:10:45

3DGS-IEval-15K: A Large-scale Image Quality Evaluation Database for 3D Gaussian-Splatting
Yuke Xing, Jiarui Wang, Peizhi Niu, Wenjie Huang, Guangtao Zhai, Yiling Xu
arxiv.org/abs/2506.14642

@arXiv_csCL_bot@mastoxiv.page
2025-06-19 14:23:01

Replaced article(s) found for cs.CL. arxiv.org/list/cs.CL/new
[2/4]:
- Alleviating Distribution Shift in Synthetic Data for Machine Translation Quality Estimation
Xiang Geng, Zhejian Lai, Jiajun Chen, Hao Yang, Shujian Huang

@arXiv_csCR_bot@mastoxiv.page
2025-06-19 08:08:43

CWGAN-GP Augmented CAE for Jamming Detection in 5G-NR in Non-IID Datasets
Samhita Kuili, Mohammadreza Amini, Burak Kantarci
arxiv.org/abs/2506.15075

@arXiv_eessIV_bot@mastoxiv.page
2025-06-13 09:19:00

Semi-Automated Quality Assurance in Digital Pathology: Tile Classification Approach
Meredith VandeHaar, M. Clinch, I. Yilmaz, M. A. Rahman, Y. Xiao, F. Dogany, H. M. Alazab, A. Nassar, Z. Akkus, B. Dangott
arxiv.org/abs/2506.10916

@blakes7bot@mas.torpidity.net
2025-06-18 09:17:39

Series B, Episode 09 - Countdown
VETNOR: All right, come with me, we're searching the next level.
PROVINE: Right, sir.
[Teleport section. Avon and Grant are suited up]
AVON: You adjust the temperature with this [Points to knob on suit] You all set?
blake.torpidity.net/m/209/356

Claude 3.7 describes the image as: "This image appears to be from a vintage science fiction television production, likely from the late 1970s or early 1980s based on the visual style and filming quality. 

The scene shows two individuals in a sparse, utilitarian setting with plain walls. Both are wearing similar olive-green high-necked uniforms or jumpsuits that have a military or institutional appearance. One person is visible in profile on the left, while another is facing forward on the righ…
@arXiv_csCV_bot@mastoxiv.page
2025-06-18 09:16:56

FocalClick-XL: Towards Unified and High-quality Interactive Segmentation
Xi Chen, Hengshuang Zhao
arxiv.org/abs/2506.14686

@Dragofix@veganism.social
2025-06-02 22:58:06

Colon cancer recurrence and deaths cut 28% by simple exercise, trial finds arstechnica.com/health/2025/06

@arXiv_csSD_bot@mastoxiv.page
2025-06-19 08:36:13

TTSOps: A Closed-Loop Corpus Optimization Framework for Training Multi-Speaker TTS Models from Dark Data
Kentaro Seki, Shinnosuke Takamichi, Takaaki Saeki, Hiroshi Saruwatari
arxiv.org/abs/2506.15614

@arXiv_csSE_bot@mastoxiv.page
2025-06-17 10:40:25

MCTS-Refined CoT: High-Quality Fine-Tuning Data for LLM-Based Repository Issue Resolution
Yibo Wang, Zhihao Peng, Ying Wang, Zhao Wei, Hai Yu, Zhiliang Zhu
arxiv.org/abs/2506.12728

@arXiv_csHC_bot@mastoxiv.page
2025-06-09 07:54:42

QualitEye: Public and Privacy-preserving Gaze Data Quality Verification
Mayar Elfares, Pascal Reisert, Ralf K\"usters, Andreas Bulling
arxiv.org/abs/2506.05908

@arXiv_csAI_bot@mastoxiv.page
2025-06-18 08:07:45

GUI-Robust: A Comprehensive Dataset for Testing GUI Agent Robustness in Real-World Anomalies
Jingqi Yang, Zhilong Song, Jiawei Chen, Mingli Song, Sheng Zhou, linjun sun, Xiaogang Ouyang, Chun Chen, Can Wang
arxiv.org/abs/2506.14477

@arXiv_csDL_bot@mastoxiv.page
2025-06-10 07:31:42

Research quality evaluation by AI in the era of Large Language Models: Advantages, disadvantages, and systemic effects
Mike Thelwall
arxiv.org/abs/2506.07748

@Techmeme@techhub.social
2025-06-13 09:11:01

Nintendo Switch 2 review: great build quality, better haptics, and improved performance for Switch 1 games, but weak battery life and only a few launch titles (The Shortcut)
theshortcut.com/p/nintendo-swi

The South Coast Air Quality Management District will hold a public hearing Friday on two proposed regulations designed to limit key pollutants that form smog.
If adopted, the rules would phase out the sale of gas-powered furnaces and water heaters in the region.
Officials say the plan is crucial for reducing air pollution and improving public health, while opponents fear higher consumer costs.

@arXiv_csNI_bot@mastoxiv.page
2025-06-19 08:28:34

GCN-Driven Reinforcement Learning for Probabilistic Real-Time Guarantees in Industrial URLLC
Eman Alqudah, Ashfaq Khokhar
arxiv.org/abs/2506.15011

@wvmierlo@zirk.us
2025-06-21 16:48:57

Pierrepont Holme Hall, February 2025
#photography #heritagephotography #manorhouse #shadow

The garden of the old manor house with a strong shadow across the building.
@arXiv_csCL_bot@mastoxiv.page
2025-06-19 08:14:09

From Model to Classroom: Evaluating Generated MCQs for Portuguese with Narrative and Difficulty Concerns
Bernardo Leite, Henrique Lopes Cardoso, Pedro Pinto, Abel Ferreira, Lu\'is Abreu, Isabel Rangel, Sandra Monteiro
arxiv.org/abs/2506.15598

@arXiv_csSE_bot@mastoxiv.page
2025-06-17 11:02:25

Adopting Use Case Descriptions for Requirements Specification: an Industrial Case Study
Julian Frattini, Anja Frattini
arxiv.org/abs/2506.13303

@jamesthebard@social.linux.pizza
2025-06-14 21:24:45

Pretty happy, first episode went from ~6GB to 250MB. Settings are still good, quality is outstanding, and the chapters, subtitles, and fonts all muxed in beautifully. Gonna let these encodes finish up on the cluster while I listen to some music and drink a few beers outside.
#homelab #encoding

@arXiv_csAI_bot@mastoxiv.page
2025-06-18 08:02:02

Evaluating Explainability: A Framework for Systematic Assessment and Reporting of Explainable AI Features
Miguel A. Lago, Ghada Zamzmi, Brandon Eich, Jana G. Delfino
arxiv.org/abs/2506.13917

@arXiv_eessIV_bot@mastoxiv.page
2025-06-19 08:43:22

Advanced cervical cancer classification: enhancing pap smear images with hybrid PMD Filter-CLAHE
Ach Khozaimi, Isnani Darti, Syaiful Anam, Wuryansari Muharini Kusumawinahyu
arxiv.org/abs/2506.15489

@Dragofix@veganism.social
2025-06-02 23:25:30

Air-quality monitoring underestimates toxic emissions to Salton Sea communities, study finds sciencedaily.com/releases/2025
Air-quality monitoring underestimates toxic emissions to Salton Sea communities, study finds

@Techmeme@techhub.social
2025-06-04 10:21:16

Google pauses the rollout of Photos' AI-powered Ask Photos feature due to issues with latency, quality, and user experience, per a Google product manager on X (Hayden Field/The Verge)
theverge.com/news/678858/googl

@arXiv_csCV_bot@mastoxiv.page
2025-06-19 08:23:39

Evolutionary Caching to Accelerate Your Off-the-Shelf Diffusion Model
Anirud Aggarwal, Abhinav Shrivastava, Matthew Gwilliam
arxiv.org/abs/2506.15682

@arXiv_csCR_bot@mastoxiv.page
2025-06-13 07:32:40

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning
Muqi Zou (Jing), Hongyu Cai (Jing), Hongwei Wu (Jing), Zion Leonahenahe Basque (Jing), Arslan Khan (Jing), Berkay Celik (Jing), Dave (Jing), Tian (Fish), Antonio Bianchi (Fish), Ruoyu (Fish), Wang, Dongyan Xu
arxiv.org/abs/2506.10125…

@arXiv_csHC_bot@mastoxiv.page
2025-06-18 08:27:49

Exploring MLLMs Perception of Network Visualization Principles
Jacob Miller, Markus Wallinger, Ludwig Felder, Timo Brand, Henry F\"orster, Johannes Zink, Chunyang Chen, Stephen Kobourov
arxiv.org/abs/2506.14611

@arXiv_csSE_bot@mastoxiv.page
2025-06-17 10:09:29

Can LLMs Generate High-Quality Test Cases for Algorithm Problems? TestCase-Eval: A Systematic Evaluation of Fault Coverage and Exposure
Zheyuan Yang, Zexi Kuang, Xue Xia, Yilun Zhao
arxiv.org/abs/2506.12278

@arXiv_csAI_bot@mastoxiv.page
2025-06-18 08:00:52

Med-REFL: Medical Reasoning Enhancement via Self-Corrected Fine-grained Reflection
Zongxian Yang, Jiayu Qian, Zegao Peng, Haoyu Zhang, Zhi-An Huang
arxiv.org/abs/2506.13793

@arXiv_csCV_bot@mastoxiv.page
2025-06-19 08:22:49

UniRelight: Learning Joint Decomposition and Synthesis for Video Relighting
Kai He, Ruofan Liang, Jacob Munkberg, Jon Hasselgren, Nandita Vijaykumar, Alexander Keller, Sanja Fidler, Igor Gilitschenski, Zan Gojcic, Zian Wang
arxiv.org/abs/2506.15673

@arXiv_csCL_bot@mastoxiv.page
2025-06-18 09:08:18

Treasure Hunt: Real-time Targeting of the Long Tail using Training-Time Markers
Daniel D'souza, Julia Kreutzer, Adrien Morisot, Ahmet \"Ust\"un, Sara Hooker
arxiv.org/abs/2506.14702

@arXiv_eessIV_bot@mastoxiv.page
2025-06-11 08:08:55

Enhancing Synthetic CT from CBCT via Multimodal Fusion: A Study on the Impact of CBCT Quality and Alignment
Maximilian Tschuchnig, Lukas Lamminger, Philipp Steininger, Michael Gadermayr
arxiv.org/abs/2506.08716

@arXiv_csSD_bot@mastoxiv.page
2025-06-19 08:35:53

Exploiting Music Source Separation for Automatic Lyrics Transcription with Whisper
Jaza Syed, Ivan Meresman Higgs, Ond\v{r}ej C\'ifka, Mark Sandler
arxiv.org/abs/2506.15514

@arXiv_csAI_bot@mastoxiv.page
2025-06-18 08:04:57

ImpReSS: Implicit Recommender System for Support Conversations
Omri Haller, Yair Meidan, Dudu Mimran, Yuval Elovici, Asaf Shabtai
arxiv.org/abs/2506.14231

@arXiv_csCV_bot@mastoxiv.page
2025-06-19 08:23:29

Sekai: A Video Dataset towards World Exploration
Zhen Li, Chuanhao Li, Xiaofeng Mao, Shaoheng Lin, Ming Li, Shitian Zhao, Zhaopan Xu, Xinyue Li, Yukang Feng, Jianwen Sun, Zizhen Li, Fanrui Zhang, Jiaxin Ai, Zhixiang Wang, Yuwei Wu, Tong He, Jiangmiao Pang, Yu Qiao, Yunde Jia, Kaipeng Zhang
arxiv.org/abs/2506.15675

@arXiv_csSE_bot@mastoxiv.page
2025-06-13 08:03:20

Prompt Variability Effects On LLM Code Generation
Andrei Paleyes, Radzim Sendyka, Diana Robinson, Christian Cabrera, Neil D. Lawrence
arxiv.org/abs/2506.10204

@arXiv_csSE_bot@mastoxiv.page
2025-06-19 08:37:13

cAST: Enhancing Code Retrieval-Augmented Generation with Structural Chunking via Abstract Syntax Tree
Yilin Zhang, Xinran Zhao, Zora Zhiruo Wang, Chenyang Yang, Jiayi Wei, Tongshuang Wu
arxiv.org/abs/2506.15655

@arXiv_csCV_bot@mastoxiv.page
2025-06-18 09:37:21

CDP: Towards Robust Autoregressive Visuomotor Policy Learning via Causal Diffusion
Jiahua Ma, Yiran Qin, Yixiong Li, Xuanqi Liao, Yulan Guo, Ruimao Zhang
arxiv.org/abs/2506.14769

@arXiv_csCV_bot@mastoxiv.page
2025-06-18 09:27:05

Cost-Aware Routing for Efficient Text-To-Image Generation
Qinchan (Wing), Li (Tina), Kenneth Chen (Tina), Changyue (Tina), Su, Wittawat Jitkrittum, Qi Sun, Patsorn Sangkloy
arxiv.org/abs/2506.14753

@arXiv_csSE_bot@mastoxiv.page
2025-06-18 08:39:57

Role, cost, and complexity of software in the real-world: a case for formal methods
Giovanni Bernardi, Adrian Francalanza, Marco Peressotti, Mohammad Reza Mousavi
arxiv.org/abs/2506.13821

@arXiv_csSE_bot@mastoxiv.page
2025-06-09 08:00:42

CodeContests : High-Quality Test Case Generation for Competitive Programming
Zihan Wang, Siyao Liu, Yang Sun, Hongyan Li, Kai Shen
arxiv.org/abs/2506.05817

@arXiv_csCV_bot@mastoxiv.page
2025-06-17 09:34:23

GroupNL: Low-Resource and Robust CNN Design over Cloud and Device
Chuntao Ding, Jianhang Xie, Junna Zhang, Salman Raza, Shangguang Wang, Jiannong Cao
arxiv.org/abs/2506.12335

@arXiv_csSE_bot@mastoxiv.page
2025-06-13 08:08:42

Augmenting Large Language Models with Static Code Analysis for Automated Code Quality Improvements
Seyed Moein Abtahi, Akramul Azim
arxiv.org/abs/2506.10330

@arXiv_csCV_bot@mastoxiv.page
2025-06-17 09:46:24

Perceptual-GS: Scene-adaptive Perceptual Densification for Gaussian Splatting
Hongbi Zhou, Zhangkai Ni
arxiv.org/abs/2506.12400