SubQ 1M-Preview scores 95% accuracy, compared to 94.8% for Claude Opus 4.6
在RULER 128K基准测试中,SubQ 1M-Preview准确率达到95%,略高于Claude Opus 4.6的94.8%。这个数据点表明SubQ在长上下文理解方面已达到前沿水平,同时突破了传统二次扩展模型的性能瓶颈。
SubQ 1M-Preview scores 95% accuracy, compared to 94.8% for Claude Opus 4.6
在RULER 128K基准测试中,SubQ 1M-Preview准确率达到95%,略高于Claude Opus 4.6的94.8%。这个数据点表明SubQ在长上下文理解方面已达到前沿水平,同时突破了传统二次扩展模型的性能瓶颈。
RLCR reduced calibration error by up to 90 percent while maintaining or improving accuracy
这一关键实验结果表明,RLCR方法在减少校准误差的同时,保持了甚至提高了模型的准确性,表明其有效性。
We do not publish AI-generated images, audio, or video as authentic documentation of real events.
这条规定指出Ars Technica不会将人工智能生成的图像、音频或视频作为真实事件的证明,体现了对真实性的坚持。
Claude Opus 4.7 is a solid upgrade with no regressions for Vercel. It's phenomenal on one-shot coding tasks, more correct and complete than Opus 4.6, and noticeably more honest about its own limits.
在单次编码任务中的卓越表现和对自身局限性的诚实认知,展示了AI在准确性和自我意识上的双重进步,这种对自身能力的准确评估对于构建可靠的AI系统至关重要。
Using these ability scores, the method predicts performance on new tasks with ~88% accuracy, including for models such as GPT-4o and Llama-3.1.
88%的预测准确率是一个令人印象深刻的数据点,表明ADeLe不仅能够解释现有性能,还能可靠预测模型在新任务上的表现。这一准确率远超传统方法,为AI系统的可靠部署提供了强有力的预测工具,可能是AI评估领域的重要突破。
Using these ability scores, the method predicts performance on new tasks with ~88% accuracy, including for models such as GPT-4o and Llama-3.1.
令人惊讶的是:ADeLe方法能够以约88%的准确度预测AI模型在新任务上的表现,这包括像GPT-4o和Llama-3.1这样先进的大模型。这种预测能力远超传统评估方法,为AI性能评估提供了革命性的突破,使研究人员能够更可靠地预见模型在未见过的任务上的表现。
TriAttention matches Full Attention reasoning accuracy while achieving 2.5x higher throughput or 10.7x KV memory reduction
大多数人认为在KV缓存压缩中,准确率和效率之间存在不可避免的权衡,但作者提出的TriAttention方法能够在保持全注意力推理准确度的同时,实现2.5倍的吞吐量提升或10.7倍的内存减少。这一结果挑战了当前领域内的效率-准确度权衡范式,表明可以通过创新方法打破这一传统限制。
TriAttention matches Full Attention reasoning accuracy while achieving 2.5x higher throughput or 10.7x KV memory reduction
大多数人认为在大幅压缩KV缓存时必然会牺牲模型推理的准确性,但作者声称TriAttention在实现10.7倍内存减少的同时,仍能保持与完整注意力相同的推理准确性。这一结果挑战了业界在KV压缩与准确性之间的权衡认知。
We've seen customers go from 10-20% field accuracy with a frontier model to 99-100% just by switching to using Reducto's Deep Extract.
大多数人认为从前沿模型到接近完美的准确率需要根本性的技术突破或大量数据训练。但作者声称仅通过切换到Deep Extract方法就能将准确率从10-20%提升到99-100%,这种巨大性能提升的幅度与行业通常预期的改进曲线相悖,暗示现有方法可能存在根本性缺陷。
Aortic dissection typically presents acutely with sudden, severe tearing chest or back pain, often described as lancinating in quality. [5-6] Approximately 50% of patients with thoracic aortic aneurysm may progress to dissection without timely intervention. [5] In contrast, thoracic aortic aneurysm is usually asymptomatic and discovered incidentally during physical examination or imaging for other indications. [5]
ChatGPT makes writing easier and more of a cleaner look, especially for people who aren’t native English speakers. But it also makes people worry and start thinking to themselves like “Is this really my work?” or “Am I cheating?” It can be helpful, but also very stressful to one.
Transcranial magnetic stimulation (TMS) is a procedure in which magnetic pulses are applied to the brain of a living person with the goal of temporarily and safely deactivating a small brain region. The p
TMS is a simulation to determine issues resulting in speecific parts of the brain, and finding which ones.
in ected
In Grammar... change the form of (a word) to express a particular grammatical function or attribute, typically tense, mood, person, number, case, and gender.
2. vary the intonation or pitch of (the voice), especially to express mood or feeling.
we now realize the base pairs come to join each other up together as the system unravels and forms a new pair of DNA molecules well up to a point it does and that point is known to be accurate to about one in 10,000 base pairs now if you and I wrote an article and there was only one typo in a 10,000w article we'd be very pleased but this is nowhere near enough for a DNA sequence of three billion base pairs there would be half a million at least of Errors
for - DNA replication accuracy - 1 in 10,000 - too high for successful replication - another higher level mechanism to correct for these errors - need a whole body for that - Denis Noble
TRSP Desirable Characteristics The PID Manager MUST maintain entity metadata as accurately as possible in collaboration with the PID Owner. This copy is the authoritative version.
In the beginning of the film, a message appears that states the film encompasses historical facts as well as free personal impressions about Muhammad. Accordingly, some of the film's events did not actually take place in real life, but are indeed similar to events in Muhammad's biography.[6] Majidi stated that the objective behind presenting these scenes is to show that the whole existence could feel Muhammad's presence as well as his mercy.
Interesting. This is a general problem with historical movies. There is almost no such thing as objectivity. By making a movie, you make choices, you select what makes the cut and what doesn't. and by doing so, you form a certain image of the prophet, in this case. The free personal impressions of Majid are in fact a way to represent a certain image of Muhammad.
From what I have read, Majid is blamed for putting forward a Shi'ite Muhammed forward in the movie. Perhaps his free personal impressions are expressed in this regard?
The initial focus is on the learner’s home language (it’s currently being piloted with grade 3 isiZulu-speaking learners at a school in Soweto, Johannesburg). English is introduced gradually as a target language. The language and speech technology has been developed to provide linguistic accuracy and is grounded in teaching principles.
This application is for Grade 3 and up. It doesn't solve the problem I identified which is by Grade 2 most learners can't read for meaning. Stepping in early is key so there is still viability for an application like mine.
The development of the card system and itsmore universal adoption within recent years isundoubtedly due in the mail to the development in modernbusiness and factory organisation ; it may be regarded as anoffspring of manufacture in quantities. (Massenfabrikation, Gross-industrie.) The recognised principle in manufacture in quantities ismaximum of output with minimum of labour. The means to attainthis end is specialisation, which in its turn yields greater precisionand accuracy as it^ result. All this is equally applicable to thecard system, and the last factor, greater precision and accuracy,is one of its most conspicuous claims.
Julius Kaiser contemporaneously posits that mass manufacture and maximizing efficiency (greater output for minimum input) are the primary drivers of card index system use in the early 20th century. These also improve both precision and accuracy in handling information which allow for better company or factory operation, which would have been rising concerns for businesses and manufacturing operations at the rise of scientific management during the time period.
Accuracy and Precision
1.3: Accuracy, Precision, and Significant Figures
Precision and Accuracy Guide
Accuracy of the slide rule. From thediscussion of § 2 it appears that we read fourfigures of a result on one part of the scaleand three figures on the remaining part.Assuming that the error of a reading is onetenth of the smallest interval following theleft-hand index of D, we conclude that theerror is roughly 1 in 1000 or one tenth of oneper cent. The effect of the assumed errorin judging a distance is inversely propor-tional to the length of the rule. Hencewe associate with a 10-inch slide rule anerror of one tenth of one per cent, with a20-inch slide rule an error of one twentiethof one per cent or 1 part in 2000, and withthe Thacher Cylindrical slide rule an errorof a hundredth of one per cent or one part.in 10,000. The accuracy obtainable withthe 10-inch slide rule is sufficient for manypractical purposes; in any ease the sliderule result serves as a check.
The accuracy of most 10 inch slide rules is approximately 1 in 1000 or one tenth of one percent.
Because the error in approximating distance is inversely proportion to the length of a slide rule, longer slide rules will have proportionally smaller errors, so while a 10 inch slide rule has an error of 1 in 1000, a 20 inch will have an error of 1 in 2000 and larger rules can be accurate to within 1 in 10,000 or better.
To increase the granularity of vcontrol, HTML elements can be subclasssed
The "subclassing" word choice here is interesting. It matches the model eventually suggested in HTML 3.x, but at the time of this draft, HTML was in a draft specification stage (third revision — "02") for HTML 2.0
I'm interested in the discussion that led to this.
Laurent, C. de S., Murphy, G., Hegarty, K., & Greene, C. (2021). Measuring the effects of misinformation exposure on behavioural intentions. PsyArXiv. https://doi.org/10.31234/osf.io/2xngy
Epstein, Z., Berinsky, A., Cole, R., Gully, A., Pennycook, G., & Rand, D. (2021). Developing an accuracy-prompt toolkit to reduce COVID-19 misinformation online. PsyArXiv. https://doi.org/10.31234/osf.io/sjfbn
Prof Francois Balloux [@BallouxFrancois]. (2021, December 9). This may have sounded somewhat naïve in early 2020, but by now, I would have expected that anyone with an interest in covid-19 might have acquired some basic notions in infectious disease epidemiology. 1/ [Tweet]. Twitter. https://twitter.com/BallouxFrancois/status/1469063480334561285
ReconfigBehSci. (2022, January 5). RT @thehowie: "...Rapid antigen tests may not be as fit-for-purpose in routine workplace screening to prevent asymptomatic spread of Omicro… [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1478796550004486151
Arechar, A. A., Allen, J. N. L., berinsky, a., Cole, R., Epstein, Z., Garimella, K., … Rand, D. G. (2022, February 11). Understanding and Reducing Online Misinformation Across 16 Countries on Six Continents. https://doi.org/10.31234/osf.io/a9frz
Tom Moultrie. (2021, December 12). Given the comedic misinterpretation of the South African testing data offered by @BallouxFrancois (and many others!) last night ... I offer some tips having contributed to the analysis of the testing data for the @nicd_sa since April last year. (1/6) [Tweet]. @tomtom_m. https://twitter.com/tomtom_m/status/1469954015932915718
Epstein, Z., Sirlin, N., Arechar, A. A., Pennycook, G., & Rand, D. (2021). Social Media Sharing Reduces Truth Discernment. PsyArXiv. https://doi.org/10.31234/osf.io/q4bd2
Covid: Lateral flow tests more accurate than first thought, study finds—BBC News. (n.d.). Retrieved October 15, 2021, from https://www.bbc.co.uk/news/health-58899612
Pennycook, G., & Rand, D. (2021). Nudging social media sharing towards accuracy. PsyArXiv. https://doi.org/10.31234/osf.io/tp6vy
Home - COVID 19 scenario model hub. (n.d.). Retrieved July 5, 2021, from https://covid19scenariomodelinghub.org/
Klein, Alice. “Cheap Covid-19 Antibody Test Shows If You Have Immunity in 5 Minutes.” New Scientist. Accessed September 20, 2021. https://www.newscientist.com/article/2290120-cheap-covid-19-antibody-test-shows-if-you-have-immunity-in-5-minutes/.
Roberts, M. (n.d.). Artificial intelligence has been of little use for diagnosing covid-19. New Scientist. Retrieved 24 May 2021, from https://www.newscientist.com/article/mg25033350-100-artificial-intelligence-has-been-of-little-use-for-diagnosing-covid-19/
Jigsaw. (2021, March 17). Distraction Helps Misinformation Spread. Thinking About Accuracy Can Reduce it. Medium. https://medium.com/jigsaw/distraction-helps-misinformation-spread-thinking-about-accuracy-can-reduce-it-a4e5d8371a85
Rapid Covid tests used in mass UK programme get scathing US report | Coronavirus | The Guardian. (n.d.). Retrieved June 12, 2021, from https://www.theguardian.com/world/2021/jun/11/us-health-agency-gives-innova-lateral-flow-covid-tests-scathing-review
Gu, T., Wang, L., Xie, N., Meng, X., Li, Z., Postlethwaite, A. E., Aleya, L., Howard, S., Gu, W., & Wang, Y. (2021). Towards a country-based prediction model of COVID-19 infections and deaths between disease apex and end: -Evidence from countries with contained numbers of COVID-19. Frontiers in Medicine, 8. https://doi.org/10.3389/fmed.2021.585115
Carbon, C. C. (2020). Wearing face masks strongly confuses counterparts in reading emotions [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/x3uh6
Pennycook, G., McPhetres, J., Zhang, Y., Lu, J. G., & Rand, D. G. (2020). Fighting COVID-19 Misinformation on Social Media: Experimental Evidence for a Scalable Accuracy-Nudge Intervention. Psychological Science, 0956797620939054. https://doi.org/10.1177/0956797620939054
Wu, K. J. (2020, November 2). A Rapid Virus Test Falters in People Without Symptoms, Study Finds. The New York Times. https://www.nytimes.com/2020/11/02/health/coronavirus-testing-quidel-sofia.html
🔥 Kareem Carr 🔥 on Twitter. (n.d.). Twitter. Retrieved 1 May 2021, from https://twitter.com/kareem_carr/status/1383925269132582912
Fischer, H., Said, N., & Huff, M. (2021). Insight into the accuracy of COVID-19 beliefs predicts behavior during the pandemic. PsyArXiv. https://doi.org/10.31234/osf.io/x2qv3
ReconfigBehSci. (2020, November 9). Session 2: The policy interface followed with a really helpful presentation by Lindsey Pike, from Bristol, and then panel discussion with Mirjam Jenny (Robert Koch Insitute), Paulina Lang (UK Cabinet Office), Rachel McCloy (Reading Uni.), and Rene van Bavel (European Commission) [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1325795286065815552
Longoni, C., Fradkin, A., Cian, L., & Pennycook, G. (2021, February 16). News from Artificial Intelligence is Believed Less. https://doi.org/10.31234/osf.io/wgy9e
Pennycook, G., & Rand, D. (2020). The Cognitive Science of Fake News. PsyArXiv. https://doi.org/10.31234/osf.io/ar96c
Bauer, B., Larsen, K. L., Caulfield, N., Elder, D., Jordan, S., & Capron, D. (2020). Review of Best Practice Recommendations for Ensuring High Quality Data with Amazon’s Mechanical Turk. PsyArXiv. https://doi.org/10.31234/osf.io/m78sf
Royal Statistical Society on Twitter. (n.d.). Twitter. Retrieved October 25, 2020, from https://twitter.com/RoyalStatSoc/status/1317133702183456769
Jaeger, B., Oud, B., Williams, T., Krumhuber, E., Fehr, E., & Engelmann, J. B. (2020, October 20). Trustworthiness detection from faces: Does reliance on facial impressions pay off?. https://doi.org/10.31234/osf.io/ayqeh
Martin, G. P., Sperrin, M., & Sotgiu, G. (2020). Performance of Prediction Models for Covid-19: The Caudine Forks of the External Validation. European Respiratory Journal. https://doi.org/10.1183/13993003.03728-2020
Abbott, K. R., & Sherratt, T. N. (2013). Optimal sampling and signal detection: Unifying models of attention and speed–accuracy trade-offs. Behavioral Ecology, 24(3), 605–616. https://doi.org/10.1093/beheco/art001
Surkova, E., Nikolayevsskyy, V., Drobniewski, F. (2020). False-positive COVID-19 results: hidden problems and costs. The Lancet Respiratory Medicine. https://doi.org/10.1016/S2213-2600(20)30453-7
Humphries, R., Mulchrone, K., Tratalos, J., More, S., & Hövel, P. (2020). A Systematic Framework of Modelling Epidemics on Temporal Networks. ArXiv:2009.11965 [Nlin, Physics:Physics]. http://arxiv.org/abs/2009.11965
Leuker, C., Hertwig, R., Gumenik, K., Eggeling, L. M., Hechtlinger, S., Kozyreva, A., Samaan, L., & Fleischhut, N. (2020). Wie informiert sich die Bevölkerung in Deutschland rund um das Coronavirus? Umfrage zu vorherrschenden Themen und Gründen, dem Umgang mit Fehlinformationen, sowie der Risikowahrnehmung und dem Wissen der Bevölkerung rund um das Coronavirus (Version 5, p. 966670) [Application/pdf]. Max-Planck-Institut für Bildungsforschung. https://doi.org/10.17617/2.3247925
Vlasceanu, M., & Coman, A. (2020). The Impact of Social Norms on Belief Update [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/gsem6
COVID Projections Tracker. (n.d.). Retrieved September 7, 2020, from https://www.covid-projections.com/
Bergstrom, T., Bergstrom, C. T., & Li, H. (n.d.). Frequency and accuracy of proactive testing for COVID-19. 20.
Yang, Scott Cheng-Hsin, Chirag Rank, Jake Alden Whritner, Olfa Nasraoui, and Patrick Shafto. ‘Unifying Recommendation and Active Learning for Information Filtering and Recommender Systems’. Preprint. PsyArXiv, 25 August 2020. https://doi.org/10.31234/osf.io/jqa83.
Warning witnesses of the possibility of misinformation helps protect their memory accuracy. (2020, August 30). Tufts Now. https://now.tufts.edu/news-releases/warning-witnesses-possibility-misinformation-helps-protect-their-memory-accuracy
Smith, C. F., Drew, S., Ziebland, S., & Nicholson, B. D. (2020). Understanding the role of GPs’ gut feelings in diagnosing cancer in primary care: A systematic review and meta-analysis of existing evidence. British Journal of General Practice, 70(698), e612–e621. https://doi.org/10.3399/bjgp20X712301
Cheng, A., Williamson, D., & Lewin, S. (n.d.). Explainer: What’s the new coronavirus saliva test, and how does it work? The Conversation. Retrieved July 6, 2020, from http://theconversation.com/explainer-whats-the-new-coronavirus-saliva-test-and-how-does-it-work-141877
Shan, B., Broza, Y. Y., Li, W., Wang, Y., Wu, S., Liu, Z., Wang, J., Gui, S., Wang, L., Zhang, Z., Liu, W., Zhou, S., Jin, W., Zhang, Q., Hu, D., Lin, L., Zhang, Q., Li, W., Wang, J., … Haick, H. (2020). Multiplexed Nanomaterial-Based Sensor Array for Detection of COVID-19 in Exhaled Breath. ACS Nano. https://doi.org/10.1021/acsnano.0c05657
Mohammadi, A., Esmaeilzadeh, E., Li, Y., Bosch, R. J., & Li, J. Z. (2020). SARS-CoV-2 detection in different respiratory sites: A systematic review and meta-analysis. EBioMedicine, 0(0). https://doi.org/10.1016/j.ebiom.2020.102903
Shi, W., Wang, L., & Qin, J. (2020). Extracting user influence from ratings and trust for rating prediction in recommendations. Scientific Reports, 10(1), 13592. https://doi.org/10.1038/s41598-020-70350-1
Engelhardt, R., Hendricks, V. F., & Stærk-Østergaard, J. (2020). The Wisdom and Persuadability of Threads. ArXiv:2008.05203 [Physics]. http://arxiv.org/abs/2008.05203
Manski, C. F. (2020). Bounding the Predictive Values of COVID-19 Antibody Tests (Working Paper No. 27226; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27226
Manski, C. F., & Molinari, F. (2020). Estimating the COVID-19 Infection Rate: Anatomy of an Inference Problem (Working Paper No. 27023; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27023
Taraborelli, D., Taraborelli, D., & Taraborelli, D. (2020, August 5). How the COVID-19 crisis has prompted a revolution in scientific publishing. Fast Company. https://www.fastcompany.com/90537072/how-the-covid-19-crisis-has-prompted-a-revolution-in-scientific-publishing
Kaptchuk, G., Goldstein, D. G., Hargittai, E., Hofman, J., & Redmiles, E. M. (2020). How good is good enough for COVID19 apps? The influence of benefits, accuracy, and privacy on willingness to adopt. ArXiv:2005.04343 [Cs]. http://arxiv.org/abs/2005.04343
Cazabet, R., Boudebza, S., & Rossetti, G. (2020). Evaluating Community Detection Algorithms for Progressively Evolving Graphs. ArXiv:2007.08635 [Physics]. http://arxiv.org/abs/2007.08635
Behrmann, Ole, and Martin Spiegel. ‘COVID-19: From Rapid Genome Sequencing to Fast Decisions’. The Lancet Infectious Diseases 0, no. 0 (14 July 2020). https://doi.org/10.1016/S1473-3099(20)30580-6.
Parsons, Sam. ‘Reliability Multiverse’, 26 June 2020. https://doi.org/10.31234/osf.io/y6tcz.
David G. Rand en Twitter: “Today @GordPennycook & I wrote a @nytimes op ed ‘The Right Way to Fix Fake News’ https://t.co/dyF84g6oqv tl;dr: Platforms must rigorously TEST interventions, b/c intuitions about what will work are often wrong In this thread I unpack the many studies behind our op ed 1/” / Twitter. (n.d.). Twitter. Retrieved April 15, 2020, from https://twitter.com/DG_Rand/status/1242526565793136641
Chen, C. (2020, April 28). What Antibody Studies Can Tell You—And More Importantly, What They Can’t. ProPublica. https://www.propublica.org/article/what-antibody-studies-can-tell-you-and-more-importantly-what-they-cant
Lee, S. M. (2020, April 22) Two Antibody Studies Say Coronavirus Infections Are More Common Than We Think. Scientists Are Mad. https://www.buzzfeednews.com/article/stephaniemlee/coronavirus-antibody-test-santa-clara-los-angeles-stanford
Attali, Y., Budescu, D., & Arieli-Attali, M. (2020). An item response approach to calibration of confidence judgments. Decision, 7(1), 1–19. https://doi.org/10.1037/dec0000111
Winman, A., Hansson, P., & Juslin, P. (2004). Subjective Probability Intervals: How to Reduce Overconfidence by Interval Evaluation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30(6), 1167–1175. https://doi.org/10.1037/0278-7393.30.6.1167
Is the “science” behind the lockdown any good? (n.d.). Financial Times. Retrieved June 2, 2020, from http://ftalphaville.ft.com/2020/05/21/1590091709000/It-s-all-very-well--following-the-science---but-is-the-science-any-good--/
Why We Fall Prey to Misinformation. (n.d.). Association for Psychological Science - APS. Retrieved May 29, 2020, from https://www.psychologicalscience.org/news/releases/why-we-fall-prey-to-misinformation.html
Mei, X., Lee, H.-C., Diao, K., Huang, M., Lin, B., Liu, C., Xie, Z., Ma, Y., Robson, P. M., Chung, M., Bernheim, A., Mani, V., Calcagno, C., Li, K., Li, S., Shan, H., Lv, J., Zhao, T., Xia, J., … Yang, Y. (2020). Artificial intelligence for rapid identification of the coronavirus disease 2019 (COVID-19). MedRxiv, 2020.04.12.20062661. https://doi.org/10.1101/2020.04.12.20062661
Mandel, D. R., Collins, R. N., Risko, E. F., & Fugelsang, J. A. (2020). Effect of Confidence Interval Construction on Judgment Accuracy. https://doi.org/10.31234/osf.io/mktgj
Michalak, N. M., Sng, O., Wang, I., & Ackerman, J. (2020, May 14). Sounds of sickness: Can people identify infectious disease using sounds of coughs and sneezes?. https://doi.org/10.1098/rspb.2020.0944
Smelter, T. J., & Calvillo, D. P. (2020). Pictures and repeated exposure increase perceived accuracy of news headlines. Applied Cognitive Psychology, acp.3684. https://doi.org/10.1002/acp.3684
they’ve contested its accuracy
Rafiei, F., & Rahnev, D. (2020, April 9). Does the diffusion model account for the effects of speed-accuracy tradeoff on response times?. https://doi.org/10.31234/osf.io/bhj85
Tiokhin, L., & Derex, M. (n.d.). Competition for novelty reduces information sampling in a research game—A registered report. Royal Society Open Science, 6(5), 180934. https://doi.org/10.1098/rsos.180934
WebQuests typically contain an introduction, task, process, evaluation, and conclusion
The process of obtaining information from the web which can help students to understand the type of information they are recieving and deciding if it is relevant and accurate
Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the Robustness of 18 Deep Image Classification Models
这文帅了~ 信息丰富 超多的图~ 让人眼前一亮~
探讨了18个模型的鲁棒性和准确率。结论很多,如模型构架是影响鲁棒性和准确率的重要因素(似乎是废话);相似模型构架基础上增加“深度”对鲁棒性的提升很微弱;有些模型(Vgg类)的表现出很强的对抗样本迁移性。。。
Accuracy and completeness in filling out reports73.66
73.66
Similarly, theories of informant accuracy posit that those with accurate domainknowledge provide more reliable responses with less error than those without such knowledge (Romney et al.,1986; Romneyand Weller,1984; Sudman et al.,1996; Weller and Romney,1988). Their observations will cluster around a single“truth”whileinaccurate observations (i.e. error) will be randomly scattered around the truth; that is, error is inhomogeneous and does nottypically converge around a small number of data points.
Informant accuracy is also new to me.
Get these papers. This framework might help strengthen the information quality/data validity as a broader notion of my sociotemporal representations research.
Accuracy in Media
This may be a front group. Investigate, find additional sources, and leave research notes in the comments.
Accuracy in Media
This may be a front group. Investigate, find additional sources, and leave research notes in the comments.
Accuracy in Media
This may be a front group. Investigate, find additional sources, and leave research notes in the comments.
Accuracy in Media
This may be a front group. Investigate, find additional sources, and leave research notes in the comments.
Accuracy in Media
This may be a front group. Investigate, find additional sources, and leave research notes in the comments.
Accuracy in Media
This may be a front group. Investigate, find additional sources, and leave research notes in the comments.
Accuracy in Media
This may be a front group. Investigate, find additional sources, and leave research notes in the comments.
Accuracy in Media
This may be a front group. Investigate, find additional sources, and leave research notes in the comments.
Accuracy in Media
This may be a front group. Investigate, find additional sources, and leave research notes in the comments.
Accuracy in Media
This may be a front group. Investigate, find additional sources, and leave research notes in the comments.
Accuracy in Media
This may be a front group. Investigate, find additional sources, and leave research notes in the comments.
Accuracy in Media
This may be a front group. Investigate, find additional sources, and leave research notes in the comments.
Accuracy in Media
This may be a front group. Investigate, find additional sources, and leave research notes in the comments.
Accuracy in Media
This may be a front group. Investigate, find additional sources, and leave research notes in the comments.
Accuracy in Media
This may be a front group. Investigate, find additional sources, and leave research notes in the comments.
Accuracy in Media
This may be a front group. Investigate, find additional sources, and leave research notes in the comments.
AI criticism is also limited by the accuracy of human labellers, who must carry out a close reading of the ‘training’ texts before the AI can kick in. Experiments show that readers tend to take longer to process events that are distant in time or separated by a time shift (such as ‘a day later’).
The enthymeme must consist of few propositions, fewer often than those which make up the normal syllogism. For if any of these propositions is a familiar fact, there is no need even to mention it
Be accurate. (From chapter 1.)
irrelevant speaking is forbidden in the law-courts
Rhetoric always has to be accurate to the point.