Sadamori Kojaku

Assist. Prof. @ Binghamton Univ. Lang: Japanese 🇯🇵 Samurai English 🇬🇧🇯🇵. Hobby: Sailing, Running, and Kendo. Informal account👀 @SadamoriKojaku

[𝙲𝚘𝚖𝚙𝚕𝚎𝙽𝚎𝚝 𝟸𝟶𝟸𝟽 @CompleNet]

🔥 Best Talk → keynote!

The CompleNet Best Talk Prize comes with an invitation to return as a keynote the following year — so we're delighted to welcome back Fernando Diaz-Diaz (UC3M) for CompleNet 27.

U. of Rochester, Mar 9–12
Submissions close Sept 20 https://t.co/lmapca0mSZ

[Mathematical Physics Papers @MathPHYPapers]

Global Synchronization in Matrix-Weighted Networks. https://t.co/KjO2Jtei5g

[Sadamori Kojaku @skojaku]

Interested link prediction? We will talk about an undesirable shortcut that makes modes appear to be great on catalog spec despite being poor in practice. Join me at Machine Learning session 14:30 today. #NetSci2025

[Vision(Xin) Wang @VisonWang1]

At #CHI2025, I really want to talk to people who has following related research interests:
-LLM-based multi-agent reasoning (applying cognitive modeling and RLHF)
-Multimodal analysis in human-AI collaboration/communication
-Visualization for behavior analysis
DM me. 😆

[Giovanni Petri @lordgrilo]

And here we go! First position on my ERC grant is officially open. Fully funded 3.5 years PhD position at @NUnetsi London working with me and the @NPLab_
on modeling and reconstructing higher-order systems. Application deadline: 16th February 2025. https://t.co/HuzgquFa4B

[Sofia Teixeira @branmorrighan]

I’m looking for a new PhD student with a curious and interdisciplinary mindset to work on integrating multimodal data to better understand trajectories of mental and brain health disorders!

Deadline of applications: Feb 16!
Please spread the word.

https://t.co/7el3iWRVj9

[Sadamori Kojaku @skojaku]

I had my first hands on the “composer” in the cursor editor, an agent coding system. I wrote a unittest to test wish-to- implement features for graph neural nets, and asked to implement them. It edited files, git, run, and debugged. Feel like living in the future I imagined 😳

[NetSciX 2025 @NetSciX_2025]

All the plenary talks in NetSciX 2025 will be live streamed on our YouTube Channel. Subscribe our channel to stay tuned!! Link: https://t.co/T9V3iJYUeh

#NetSciX2025 #Networkscience #IITIndore
@netscisociety

@sarikajalan9

@HirokiSayama

[Sadamori Kojaku @skojaku]

一足早く新たな年が始まりました。新雪で街は真っ白に。真っ白な気持ちで、2025年も素晴らしい年になるよう、頑張ります。

[Jürgen Schmidhuber @SchmidhuberAI]

Yet another award for plagiarism. Of all the papers that could have won the #NeurIPS2024 Test of Time Award, it had to be the #NeurIPS 2014 paper on "Generative Adversarial Networks" [GAN1]. This is the notorious paper that republished the 1990 principle of Artificial Curiosity [AC90,AC90b,AC20,AC][R2] under a new name without citing it. See references [AC90,AC90b] (1990-91) that were published when compute was about 100,000 times more expensive than in 2014: two neural nets (NNs) fight each other. A control network with adaptive stochastic Gaussian units (a generative model) generates output data. This output is fed into a predictor NN which learns by gradient descent to predict the effects of the outputs. However, in a minimax game, the first NN maximizes the loss minimized by the second NN. See Section "Implementing Dynamic Curiosity and Boredom" of [AC90,AC90b]: it mentions preliminary experiments where (in absence of external reward) the predictor minimizes a linear function of what the generator maximizes.

Even later surveys by the authors failed to cite the original work [DLP].

One year later, in 1991, there was also another 2-network adversarial system called "Predictability Minimization" [PM0,PM1] for creating disentangled representations. The 2014 GAN paper [GAN1] cites it, but wrongly claims that PM is NOT a minimax game. However, PM experiments from 1991 [PM0,PM1] and 1996 [PM2] (with images) are of the minimax type. The 2014 GAN authors have never corrected their 2014 paper [DLP].

There is a peer-reviewed journal publication on this priority dispute [AC20]. (Other early adversarial machine learning settings since 1959 [S59][H90] were very different - they neither involved self-supervised NNs where one NN sees the output of another generative NN and tries to predict its consequences, nor were about modeling data, nor used gradient descent [AC20].)

Of course, it is well known that plagiarism can be either "unintentional" or "intentional or reckless" [PLAG1-6], and the more innocent of the two may very well be partially the case here [NOB][DLP]. But science has a well-established way of dealing with "multiple discovery" and plagiarism - be it unintentional [PLAG1-6][CONN21] or not [FAKE,FAKE2] - based on facts such as time stamps of publications and patents. The deontology of science requires that unintentional plagiarists correct their publications through errata and then credit the original sources properly in the future. The awardees didn't; instead the awardees kept collecting citations for inventions of other researchers [DLP]. Isn't this behaviour intentional plagiarism as it turns even unintentional plagiarism [PLAG1-6] into an intentional form [FAKE2][NOB][DLP]?

Some people have lost their titles or jobs due to plagiarism. Harvard's former president resigned after some drama [PLAG7][NOB]. But how can advisors from the field of Machine Learning now continue to tell their PhD students that they should avoid plagiarism?

REFERENCES

[GAN1] I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, Y. Bengio. Generative adversarial nets. NIPS 2014, 2672-2680, Dec 2014. A description of GANs that does not cite J. Schmidhuber's original GAN principle of 1990 [AC90,AC90b][AC20][AC][DLP] (also containing wrong claims about J. Schmidhuber's separate adversarial NNs for Predictability Minimization [PM1-2][AC20][DLP]).

[AC90] J. Schmidhuber. Making the world differentiable: On using self-supervised fully recurrent neural networks for dynamic reinforcement learning and planning in non-stationary environments. Technical Report FKI-126-90, TUM, Feb 1990, revised Nov 1990. The first paper on planning with reinforcement learning recurrent neural networks (NNs) and on generative adversarial networks where a generator NN is fighting a predictor NN in a minimax game.

[AC90b] J. Schmidhuber. A possibility for implementing curiosity and boredom in model-building neural controllers. In J. A. Meyer and S. W. Wilson, editors, Proc. of the International Conference on Simulation of Adaptive Behavior: From Animals to Animats, pages 222-227. MIT Press/Bradford Books, 1991. Based on [AC90].

[AC20] J. Schmidhuber. Generative Adversarial Networks are Special Cases of Artificial Curiosity (1990) and also Closely Related to Predictability Minimization (1991). Neural Networks, Volume 127, p 58-66, 2020.

[AC] J. Schmidhuber (AI Blog, 2021). Artificial Curiosity & Creativity Since 1990-91.

[PM0] J. Schmidhuber. Learning factorial codes by predictability minimization. TR CU-CS-565-91, Univ. Colorado at Boulder, 1991.

[PM1] J. Schmidhuber. Learning factorial codes by predictability minimization. Neural Computation, 4(6):863-879, 1992.

[PM2] J. Schmidhuber, M. Eldracher, B. Foltin. Semilinear predictability minimzation produces well-known feature detectors. Neural Computation, 8(4):773-786, 1996.

[R2] Reddit/ML, 2019. J. Schmidhuber really had GANs in 1990.

[S59] A. L. Samuel. Some studies in machine learning using the game of checkers. IBM Journal on Research and Development, 3:210-229, 1959.

[H90] W. D. Hillis. Co-evolving parasites improve simulated evolution as an optimization procedure. Physica D: Nonlinear Phenomena, 42(1-3):228-234, 1990.

[DLP] J. Schmidhuber (2023). How 3 Turing awardees republished key methods and ideas whose creators they failed to credit. Technical Report IDSIA-23-23, Swiss AI Lab IDSIA, 14 Dec 2023.

[NOB] J. Schmidhuber (Dec 2024). A Nobel Prize for Plagiarism. Technical Report IDSIA-24-24. Sadly, the Nobel Prize in Physics 2024 for Hopfield & Hinton is a Nobel Prize for plagiarism. They republished methodologies developed in Ukraine and Japan by Ivakhnenko and Amari in the 1960s & 1970s, as well as other techniques, without citing the original papers. Even in later surveys, they didn't credit the original inventors (thus turning what may have been unintentional plagiarism into a deliberate form). None of the important algorithms for modern Artificial Intelligence were created by Hopfield & Hinton.

[PLAG1] Oxford's guide to types of plagiarism (2021). Quote: "Plagiarism may be intentional or reckless, or unintentional."

[PLAG2] Jackson State Community College (2022). Unintentional Plagiarism.

[PLAG3] R. L. Foster. Avoiding Unintentional Plagiarism. Journal for Specialists in Pediatric Nursing; Hoboken Vol. 12, Iss. 1, 2007.

[PLAG4] N. Das. Intentional or unintentional, it is never alright to plagiarize: A note on how Indian universities are advised to handle plagiarism. Perspect Clin Res 9:56-7, 2018.

[PLAG5] InfoSci-OnDemand (2023). What is Unintentional Plagiarism?

[PLAG6] Copyrighted dot com (2022). How to Avoid Accidental and Unintentional Plagiarism (2023). Quote: "May it be accidental or intentional, plagiarism is still plagiarism."

[PLAG7] Cornell Review, 2024. Harvard president resigns in plagiarism scandal. 6 January 2024.

[FAKE] H. Hopf, A. Krief, G. Mehta, S. A. Matlin. Fake science and the knowledge crisis: ignorance can be fatal. Royal Society Open Science, May 2019. Quote: "Scientists must be willing to speak out when they see false information being presented in social media, traditional print or broadcast press" and "must speak out against false information and fake science in circulation and forcefully contradict public figures who promote it."

[FAKE2] L. Stenflo. Intelligent plagiarists are the most dangerous. Nature, vol. 427, p. 777 (Feb 2004). Quote: "What is worse, in my opinion, ..., are cases where scientists rewrite previous findings in different words, purposely hiding the sources of their ideas, and then during subsequent years forcefully claim that they have discovered new phenomena."

[Sadamori Kojaku @skojaku]

Wonderful dinner reunion with @yang3kc, Xuan Wang and Vision Wang last night 🥳! Time flies so fast! Safe trip back.

[Sadamori Kojaku @skojaku]

wonderful!!

[Santo Fortunato @santo_fortunato]

Happy to see that @NatureComms has put our recent article on embedding and clustering (https://t.co/VdVFYCVTTt) in their list of top 50 papers in Applied Math and Physics @skojaku @filrad @IULuddy @ApsGsnp
https://t.co/mE12fu4Hfw

[Sadamori Kojaku @skojaku]

Now submitted 20 minutes before the deadline. New record achieved 🏆

[Takahiro Yabe @takayabe_0505]

📣Please RT!
I'm recruiting a PhD student @nyutandon to explore the social & economic impacts of urban infrastructure using complex systems & behavioral data-driven approaches.

Pls reach out if you're passionate about cities, systems, & data!

Details: https://t.co/JEn85Ob67Z

[Ximing Lu @GXiming]

Are LLMs 🤖 as creative as humans 👩‍🎓? Not quite!

Introducing CREATIVITY INDEX: a metric that quantifies the linguistic creativity of a text by reconstructing it from existing text snippets on the web. Spoiler: professional human writers like Hemingway are still far more creative than LLMs! 😲

[Sadamori Kojaku @skojaku]

@YulinYuResearch @NatureComms @santo_fortunato @filrad Thanks!

[Sadamori Kojaku @skojaku]

Our paper on the detectability limit of neural embeddings is finally out from @NatureComms! We showed that a simple shallow neural net w/o non-linear activation can achieve the optimal community detectability limit. Let's dive in! @santo_fortunato @filrad https://t.co/DJM1NgDEfl

[Sadamori Kojaku @skojaku]

Finally, many many thanks to @santo_fortunato , @filrad and yy for being patient for my slow pace. It took around nearly 2y and it has been a very fun project!

[Sadamori Kojaku @skojaku]

📝 Note: The limit is about detecting communities better than random chance, not about how accurately we can identify them. Performance improvements within detectable regimes are still possible! 👉 https://t.co/rvrOAjBWWX