Joined October 2013
- Tweets 51
- Following 20
- Followers 222
- Likes 97
4 Photos and videos
12 Feb 2024
With a few selected prompts, I can identify which LLM engine is being used by #ChatbotArena. At this point, if I am a malicious agent, I can carry out several rounds of evaluation, and each time I identify my target LLM, I can vote accordingly.
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19 Sep 2023
The LERI workshop at @ACMRecSys started with a very interesting presentation from @netflix researcher @panjiangwei
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19 Sep 2023
We are proud to announce that a team of @Polimi students the winners of the prestigious @ACMRecSys Challange 2023 as the best academic team
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Paolo Cremonesi retweeted
22 Mar 2023
Netflix algorithms vs. GPT4. I know I am shooting myself in the foot here a bit, but I am getting much better Netflix recommendations from GPT4 than from Netflix.
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Paolo Cremonesi retweeted
15 Sep 2022
I am thrilled to announce that our paper "Off-Policy Evaluation with Deficient Support Using Side Information" has been accepted at #NeurIPS2022 !🥳
@Maurizio_fd M. Restelli @crmpla67
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Paolo Cremonesi retweeted
23 Nov 2022
Have you ever noticed how Chinese and American researchers both publish at #NeurIPS, go to the same conference---and then barely cite or talk to each other? @BingchenZhao @gu_yuling @in4dmatics & I have, and we'll be presenting on it at @AiCultures! arxiv.org/pdf/2211.12424.pdf
ALT One Venue, Two Conferences: The Separation of Chinese and American Citation Networks Abstract At NeurIPS, American and Chinese institutions cite papers from each other’s regions substantially less than they cite endogamously. We build a citation graph to quantify this divide, compare it to European connectivity, and discuss the causes and consequences of the separation.
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Paolo Cremonesi retweeted
3 Nov 2021
We’re thrilled to announce that our @Cleafy LABS research “TeaBot: a new Android malware emerged in Italy, targets banks in Europe” has been quoted into @Apple’s paper “Building a Trusted Ecosystem for Millions of Apps”.
Read the full report➡️hubs.ly/H0-xBPb0
#teabot
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19 Nov 2021
I have a vision, a vision in which quantum computing will push artificial intelligence far beyond the limits of our imagination. I believe we are on the brink of a new era.
A collaboration between @moviri, @contentwisetv and @AWS bears quantum fruit! Our research team, led by Paolo Cremonesi, develops an innovative quantum approach to improve recommendation algorithms using Amazon Braket.
Read the AWS Quantum Computing Blog: loom.ly/76-w6Uw
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19 Nov 2021
With this first project we are just peeking at what the future promises for all of us, and I hope this is just the beginning of a new, great adventure.
Call me naïve, but that's what makes me a researcher.
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19 Nov 2021
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18 Nov 2021
A beautiful and easy-to-read blog post from @balazshidasi with takeaways from #RecSys2021
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9 Aug 2021
The first journal paper from our new team working on Quantum Computing at @polimi, in cooperation with @contentwisetv . A new research adventure!
29 Jul 2021
#mdpientropy "Feature Selection for Recommender Systems with Quantum Computing" mdpi.com/1099-4300/23/8/970
#quantumcomputing
#quantumannealing
#recommendersystems
#featureselection
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Paolo Cremonesi retweeted
29 Jul 2021
#mdpientropy "Feature Selection for Recommender Systems with Quantum Computing" mdpi.com/1099-4300/23/8/970
#quantumcomputing
#quantumannealing
#recommendersystems
#featureselection
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16 Jul 2021
I'm proud to announce that a team of students from @polimi, coordinated by @Maurizio_fd, @BernardisCesare and @FernandoBPerezM , won the first place of the academic part of the @ACMRecSys @recsyschallenge 2021, co-sponsored by @Twitter
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Paolo Cremonesi retweeted
14 Jul 2021
I am glad we were invited to present our TOIS paper "A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research" at #SIGIR2021. The second session will be at 2-3 AM for me, I have never given a presentation this late. Let's see how it goes😂
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Paolo Cremonesi retweeted
17 Jun 2021
1/ In this episode of #TheDataExchangePod I speak w/ @crmpla67 @maurizio_fd of the #RecSys group @polimi. We discussed their recent survey papers on the use of #DeepLearning in recommendation systems: they found it difficult to reproduce research results
thedataexchange.media/questi…
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Paolo Cremonesi retweeted
25 Jun 2020
4/ They found a disconnect between what companies like Facebook are using in production, and what ML Systems researchers are working on. @DrKimHazelwood & her colleagues @Facebook discovered that the (ML systems) research community publish few papers on recommenders
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