Tootfinder

An O(log log n)-approximate budget feasible mechanism for subadditive valuations
Rian Neogi, Kanstantsin Pashkovich, Chaitanya Swamy
https://arxiv.org/abs/2506.04665

An O(log log n)-approximate budget feasible mechanism for subadditive valuations
In budget-feasible mechanism design, there is a set of items $U$, each owned by a distinct seller. The seller of item $e$ incurs a private cost $\overline{c}_e$ for supplying her item. A buyer wishes to procure a set of items from the sellers of maximum value, where the value of a set $S\subseteq U$ of items is given by a valuation function $v:2^U\to \mathbb{R}_+$. The buyer has a budget of $B \in \mathbb{R}_+$ for the total payments made to the sellers. We wish to design a mechanism that is tr…

New #Bandcamp Purchase!
Title: Shiva (Webra Remix)
Artist: Avalon & Waio
Link: https://bandcamp.com/pmarg

I had this idea for a Cairn lifepath generator where there are three stages of life and you roll 1d6 for your stats at each stage, and also get appropriate items.
It has not been playtested, it's barely been proofread, but I've been having a lot of fun generating guys
perchance.org/lt8m69fg35
#ttrpg #CairnRpg

Cowboys nailed 4 of 6 items on offseason checklist, but 2 remaining items are big deals https://cowboyswire.usatoday.com/story/sports/nfl/cowboys/2025/06/03/cowboys-offseason-checklist-update/84011326007/

This https://arxiv.org/abs/2406.13785 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Efficient Implementation of a Quantum Search Algorithm for Arbitrary N
This paper presents an enhancement to Grover's search algorithm for instances where the number of items (or the size of the search problem) $N$ is not a power of 2. By employing an efficient algorithm for the preparation of uniform quantum superposition states over a subset of the computational basis states, we demonstrate that a considerable reduction in the number of oracle calls (and Grover's iterations) can be achieved in many cases. For special cases (i.e., when $N$ is of the form such tha…

Attack Effect Model based Malicious Behavior Detection
Limin Wang, Lei Bu, Muzimiao Zhang, Shihong Cang, Kai Ye
https://arxiv.org/abs/2506.05001 https://…

Attack Effect Model based Malicious Behavior Detection
Traditional security detection methods face three key challenges: inadequate data collection that misses critical security events, resource-intensive monitoring systems, and poor detection algorithms with high false positive rates. We present FEAD (Focus-Enhanced Attack Detection), a framework that addresses these issues through three innovations: (1) an attack model-driven approach that extracts security-critical monitoring items from online attack reports for comprehensive coverage; (2) effic…

The TSA is in the same category as ICE in terms of what fucking cruel shit it pulls.
https://unionrayo.com/en/tsa-ban-children-toys-flight/

Goodbye to children's toys on flights - the TSA bans these common items in carry-on luggage
The Transportation Security Administration (TSA) has started confiscating one of the most common items in the carry-on luggage of young children: stuffed

Go check out my Bandcamp wishlist, which even includes some tracks for just $1 at: #Bandcamp

London Design Museum Turns its Massive Warehouse Collection into Another Museum—with 250K Items https://www.goodnewsnetwork.org/london-design-museum-turns-its-massive-warehouse-collection-into-another-museu…

London Design Museum Turns its Massive Warehouse Collection into Another Museum—with 250K Items
Rather than hold the power of deciding what the public gets to see, in a stroke of democracy, they have given the reins over to the public.

BVLSM: Write-Efficient LSM-Tree Storage via WAL-Time Key-Value Separation
Ming Li, Wendi Cheng, Jiahe Wei, Xueqiang Shan, Liu Weikai, Xiaonan Zhao, Xiao Zhang
https://arxiv.org/abs/2506.04678

BVLSM: Write-Efficient LSM-Tree Storage via WAL-Time Key-Value Separation
Modern data-intensive applications increasingly store and process big-value items, such as multimedia objects and machine learning embeddings, which exacerbate storage inefficiencies in Log-Structured Merge-Tree (LSM)-based key-value stores. This paper presents BVLSM, a Write-Ahead Log (WAL)-time key-value separation mechanism designed to address three key challenges in LSM-Tree storage systems: write amplification, poor memory utilization, and I/O jitter under big-value workloads. Unlike state…

AliBoost: Ecological Boosting Framework in Alibaba Platform
Qijie Shen, Yuanchen Bei, Zihong Huang, Jialin Zhu, Keqin Xu, Boya Du, Jiawei Tang, Yuning Jiang, Feiran Huang, Xiao Huang, Hao Chen
https://arxiv.org/abs/2506.00954

AliBoost: Ecological Boosting Framework in Alibaba Platform
Maintaining a healthy ecosystem in billion-scale online platforms is challenging, as users naturally gravitate toward popular items, leaving cold and less-explored items behind. This ''rich-get-richer'' phenomenon hinders the growth of potentially valuable cold items and harms the platform's ecosystem. Existing cold-start models primarily focus on improving initial recommendation performance for cold items but fail to address users' natural preference for popular content. In this paper, we intr…

This https://arxiv.org/abs/2312.16139 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Abnormal component analysis
At the crossway of machine learning and data analysis, anomaly detection aims at identifying observations that exhibit abnormal behaviour. Be it measurement errors, disease development, severe weather, production quality default(s) (items) or failed equipment, financial frauds or crisis events, their on-time identification and isolation constitute an important task in almost any area of industry and science. While a substantial body of literature is devoted to detection of anomalies, little att…

The man is a national treasure. I remember watching the Secret Life of.... shows back in my youth.
The Secret Life of the Home: https://www.youtube.com/watch?v=cqpvl-YGFD4&t=1820
> Tim looks back at his gallery at London's Science Museum. It ope…

This is pretty awesome, well done #Pembrokeshire CC!
Small electrical items now accepted in kerbside #recycling collections
https://newsroom.pembrokeshire.gov.uk/news/small-electrical-items-now-accepted-in-kerbside-recycling-collections

A Hierarchical Bin Packing Framework with Dual Manipulators via Heuristic Search and Deep Reinforcement Learning
Beomjoon Lee, Changjoo Nam
https://arxiv.org/abs/2506.01628

A Hierarchical Bin Packing Framework with Dual Manipulators via Heuristic Search and Deep Reinforcement Learning
We address the bin packing problem (BPP), which aims to maximize bin utilization when packing a variety of items. The offline problem, where the complete information about the item set and their sizes is known in advance, is proven to be NP-hard. The semi-online and online variants are even more challenging, as full information about incoming items is unavailable. While existing methods have tackled both 2D and 3D BPPs, the 2D BPP remains underexplored in terms of fully maximizing utilization. …

An LLM (Copilot, in this case) made an impressive looking graph of collection items over time for a colleague, but after a bit of probing he came to the most 2025 realisation possible:
'Oh wait I've just realised it's made the whole thing up....DOH!'
#AI #LLM

I finally got rid of the old bed I’d kept since moving in, so the room feels pretty empty right now.
I’m in the process of reorganizing everything and plan to turn this space into my own anarchist sanctuary.
Soon, I’ll add a bookshelf and more anarchist art to the wall, right next to the communist hammer and sickle symbol.
#Declutter

When Less Is More: Binary Feedback Can Outperform Ordinal Comparisons in Ranking Recovery
Shirong Xu, Jingnan Zhang, Junhui Wang
https://arxiv.org/abs/2507.01613

When Less Is More: Binary Feedback Can Outperform Ordinal Comparisons in Ranking Recovery
Paired comparison data, where users evaluate items in pairs, play a central role in ranking and preference learning tasks. While ordinal comparison data intuitively offer richer information than binary comparisons, this paper challenges that conventional wisdom. We propose a general parametric framework for modeling ordinal paired comparisons without ties. The model adopts a generalized additive structure, featuring a link function that quantifies the preference difference between two items and…

Kam Wai Dim Sum
Article content
249 East Pender St., Vancouver
The pork siu mai and har gow are bestsellers in a long menu of items. There’s another to open in the Hastings-Sunrise neighbourhood in late summer — bigger and with more tables.

US won't send some weapons pledged to Ukraine following a Pentagon review of military aid
A Pentagon review determined that stocks were too low on some weapons previously pledged to Ukraine,
so pending shipments of some items won’t be sent,
according to a U.S. official who spoke on condition of anonymity to provide information that has not yet been made public.

The Defense Department did not provide details on what specific weapons were being held back.

The…

US won't send some weapons pledged to Ukraine following a Pentagon review of military aid
The U.S. is halting some shipments of weapons to Ukraine amid concerns that its own stockpiles have declined too much

In the last few days, I"ve heard about TACO (Turnip Always Chickens Out). It's a reference to the fact that #POTUS47 often will make some bold move (e.g. declaring huge tariffs), only to back down a few days later when the move proves to be unpopular or unsuccessful.
Now it is reported that Trump Burger restaurant is getting flooded with inquiries about whether they serve chicken tac…

Texas ‘Trump Burger’ joint getting spammed by chicken taco comments online. Why?
Trump Burger has 4 locations in Texas with MAGA-themed menu items. Commenters have asked for a chicken taco, acronym for “Trump always chickens out.”

Life Sample 🈚️
生活样本 🈚️
📷 Nikomat FT
🎞️Fujifilm Neopan SS, expired 1995
buy me ☕️ ?/请我喝杯☕️？
#filmphotography

Yiding Cao Geld mit PayPal.Me senden
Folgen Sie dem Link PayPal.Me/dingsterdingster und geben Sie den Betrag ein. Es ist bequem und sicher. Sie haben noch kein PayPal-Konto? Kein Problem.

Exploring AR Label Placements in Visually Cluttered Scenarios
Ji Hwan Park, Braden Roper, Amirhossein Arezoumand, Tien Tran
https://arxiv.org/abs/2507.00198

Exploring AR Label Placements in Visually Cluttered Scenarios
We investigate methods for placing labels in AR environments that have visually cluttered scenes. As the number of items increases in a scene within the user' FOV, it is challenging to effectively place labels based on existing label placement guidelines. To address this issue, we implemented three label placement techniques for in-view objects for AR applications. We specifically target a scenario, where various items of different types are scattered within the user's field of view, and multip…

Grow a Garden, a hit game on Roblox, has spawned a market where in-game items are sold for real money on sites like eBay, potentially violating Roblox's ToS (Cecilia D'Anastasio/Bloomberg)
https://www.bloomberg.com/news/articles/20…

Knowledge Graphs for Digitized Manuscripts in Jagiellonian Digital Library Application
Jan Ignatowicz, Krzysztof Kutt, Grzegorz J. Nalepa
https://arxiv.org/abs/2506.03180

Knowledge Graphs for Digitized Manuscripts in Jagiellonian Digital Library Application
Digitizing cultural heritage collections has become crucial for preservation of historical artifacts and enhancing their availability to the wider public. Galleries, libraries, archives and museums (GLAM institutions) are actively digitizing their holdings and creates extensive digital collections. Those collections are often enriched with metadata describing items but not exactly their contents. The Jagiellonian Digital Library, standing as a good example of such an effort, offers datasets acc…

Excellent keynote in the #SemDH2025 workshop by Laura Hollink on Cultural Bias in Linked Open Data. Laura is addressing all bias related aspects in cultural heritage items itself, in the data representing it, the data schemata, vocabularies, and ontologies on which the data are based, as well as in the knowledge representation languages used to create the schemata.

This https://arxiv.org/abs/2505.09795 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

Beyond Pairwise Learning-To-Rank At Airbnb
There are three fundamental asks from a ranking algorithm: it should scale to handle a large number of items, sort items accurately by their utility, and impose a total order on the items for logical consistency. But here's the catch-no algorithm can achieve all three at the same time. We call this limitation the SAT theorem for ranking algorithms. Given the dilemma, how can we design a practical system that meets user needs? Our current work at Airbnb provides an answer, with a working solutio…

Thanks a lot @…, you’ve turned @… into a 3D-printing nerd. Every conversation has been about 3D-printed items the last few days. 🤣

https://wgme.com/news/i-team/while-in-mourning-hacker-used-a-maine-moms-facebook-to-sell-her-late-daughters-items
Oh lord

While in mourning, hacker used Maine mom's Facebook to 'sell' her late daughter's items
We share our lives online. Family photos. Health updates. But those years of memories are vulnerable.

At my keynote for the 2025 Acadia Ethics Conference, a number of clinical therapists in attendance surprised me by embracing AI's potential to bridge mental health gaps and even flag anxiety-producing items in their offices from a single photo.
https://www.

»How to build a copy-to-clipboard HTML«
– by @…
With JavaScript set HTML to easy use web GUI's.
📃 https://gomakethings.com/how-…

How to build a copy-to-clipboard HTML Web Component
Yesterday, we looked at how to copy items to a user’s clipboard with JavaScriprt. Today, we’re going to turn that into an HTML Web Component. Let’s dig in! The Custom Element For this Web Component, let’s use a element. With the HTML Web Component approach, we start with HTML and enhance it rather than rendering all the things with JavaScript. Let’s add a with our desired text inside the custom element.

NC Republicans Banished Diversity, Equity and Inclusion. Now the Only Perspective That Matters to Them Is Their Own (Herald Sun, 30 June 2025)
https://www.heraldsun.com/opinion/article309546875.html

Impact of Rankings and Personalized Recommendations in Marketplaces
Omar Besbes, Yash Kanoria, Akshit Kumar
https://arxiv.org/abs/2506.03369 https://

Impact of Rankings and Personalized Recommendations in Marketplaces
Individuals often navigate several options with incomplete knowledge of their own preferences. Information provisioning tools such as public rankings and personalized recommendations have become central to helping individuals make choices, yet their value proposition under different marketplace environments remains unexplored. This paper studies a stylized model to explore the impact of these tools in two marketplace settings: uncapacitated supply, where items can be selected by any number of a…

Building a Recommendation System Using Amazon Product Co-Purchasing Network
Minghao Liu, Catherine Zhao, Nathan Zhou
https://arxiv.org/abs/2506.02482 https…

Building a Recommendation System Using Amazon Product Co-Purchasing Network
This project develops an online, inductive recommendation system for newly listed products on e-commerce platforms, focusing on suggesting relevant new items to customers as they purchase other products. Using the Amazon Product Co-Purchasing Network Metadata dataset, we construct a co-purchasing graph where nodes represent products and edges capture co-purchasing relationships. To address the challenge of recommending new products with limited information, we apply a modified GraphSAGE method …

Synteesiraportti: Luonnonvaraiset eläimet konfliktin osana ‒ kokemuksia ja suosituksia #luonto

Breath of the Wild taught me that I should *not* order the third one.

Prom tonight! Kids turned up in two helicopters, a couple of Bentleys, at least one Aston, a Lamborghini, lots of Porches, Mercs and assorted other sports cars and one kid drove himself in a Fendt! This is just a state high school but there's plenty of money sloshing about behind the scenes in the shire. Thank god my shoe waited til I was picking up fish & chips afterwards to fall apart. I've had to bin three disintegrated items of clothing today, a rarity ever for me 🙄

ProxAnn: Use-Oriented Evaluations of Topic Models and Document Clustering
Alexander Hoyle, Lorena Calvo-Bartolom\'e, Jordan Boyd-Graber, Philip Resnik
https://arxiv.org/abs/2507.00828

ProxAnn: Use-Oriented Evaluations of Topic Models and Document Clustering
Topic model and document-clustering evaluations either use automated metrics that align poorly with human preferences or require expert labels that are intractable to scale. We design a scalable human evaluation protocol and a corresponding automated approximation that reflect practitioners' real-world usage of models. Annotators -- or an LLM-based proxy -- review text items assigned to a topic or cluster, infer a category for the group, then apply that category to other documents. Using this p…

By 24%
Prices for common baby items are rising due to Trump's tariffs, congressional analysis says
https://www.nbcnews.com/business/consumer/prices-common-baby-items-are-rising-due-trumps-tariffs-congressional-a-rcna212753

Disney launches a new perks program for Disney US subscribers, offering discounts, free items, and more; Hulu plans to debut its own perks program on June 2 (Thomas Buckley/Bloomberg)
https://www.bloomberg.com/news/articles/20

Breaker: Removing Shortcut Cues with User Clustering for Single-slot Recommendation System
Chao Wang, Yue Zheng, Yujing Zhang, Yan Feng, Zhe Wang, Xiaowei Shi, An You, Yu Chen
https://arxiv.org/abs/2506.00828

Breaker: Removing Shortcut Cues with User Clustering for Single-slot Recommendation System
In a single-slot recommendation system, users are only exposed to one item at a time, and the system cannot collect user feedback on multiple items simultaneously. Therefore, only pointwise modeling solutions can be adopted, focusing solely on modeling the likelihood of clicks or conversions for items by users to learn user-item preferences, without the ability to capture the ranking information among different items directly. However, since user-side information is often much more abundant tha…

Disposable E-Cigarettes More Toxic Than Traditional Cigarettes | UC Davis
Some disposable e-cigarettes, including vape pods, have alarmingly high levels of toxic metals in their vapor, found a UC Davis study. The items are especially popular with young adults and teens.
https://www.ucdavis.edu/news/disposable-e-cigarettes-more-toxic-traditional-cigarettes

Simultaneously Fair Allocation of Indivisible Items Across Multiple Dimensions
Yasushi Kawase, Bodhayan Roy, Mohammad Azharuddin Sanpui
https://arxiv.org/abs/2506.21727

Simultaneously Fair Allocation of Indivisible Items Across Multiple Dimensions
This paper explores the fair allocation of indivisible items in a multidimensional setting, motivated by the need to address fairness in complex environments where agents assess bundles according to multiple criteria. Such multidimensional settings are not merely of theoretical interest but are central to many real-world applications. For example, cloud computing resources are evaluated based on multiple criteria such as CPU cores, memory, and network bandwidth. In such cases, traditional one d…

The cafe I visit the most often clearly knows every product that I buy as they email me after every order asking how it was...
... so why do they also keep emailing me photos of meat and dairy items. They know I'm Vegan!
#Vegan

We sold about 200 items in our yard sale last Saturday, and today, I took two carloads of stuff to the donation site at our recycling centre. I feel like I'm being judged by the quality of my junk (" OH... we don't want that") even though I realize the community thrift store is flooded with donations and can't take everything. Only about 10% of my junk was deemed trash, so I'll take that as a win.
#Recycling #Donation

Citizen science illuminates the nature of city lights: #LightPollution

Fair Diversity Maximization with Few Representatives
Florian Adriaens, Nikolaj Tatti
https://arxiv.org/abs/2506.08110 https://arxiv.o…

Fair Diversity Maximization with Few Representatives
Diversity maximization problem is a well-studied problem where the goal is to find $k$ diverse items. Fair diversity maximization aims to select a diverse subset of $k$ items from a large dataset, while requiring that each group of items be well represented in the output. More formally, given a set of items with labels, our goal is to find $k$ items that maximize the minimum pairwise distance in the set, while maintaining that each label is represented within some budget. In many cases, one is …

Don’t start with your most emotionally charged items. Don’t start with your difficult items or your most expensive items to make decisions about. Start with low stakes things. https://www.overcomecompulsivehoarding.co.uk/podcast-ep-188-decision-making…

My man here doing the late night grocery shopping in his bathrobe. 😂 🤔 👏

Bridging UI Design and chatbot Interactions: Applying Form-Based Principles to Conversational Agents
Sanjay Krishna Anbalagan, Xinrui Nie, Umesh Mohan, Vijay Kumar Kanamarlapudi, Anughna Kommalapati, Xiaodan Zhao
https://arxiv.org/abs/2507.01862

Bridging UI Design and chatbot Interactions: Applying Form-Based Principles to Conversational Agents
Domain specific chatbot applications often involve multi step interactions, such as refining search filters, selecting multiple items, or performing comparisons. Traditional graphical user interfaces (GUIs) handle these workflows by providing explicit "Submit" (commit data) and "Reset" (discard data) actions, allowing back-end systems to track user intent unambiguously. In contrast, conversational agents rely on subtle language cues, which can lead to confusion and incomplete context management…

Quantifying Query Fairness Under Unawareness
Thomas Jaenich, Alejandro Moreo, Alessandro Fabris, Graham McDonald, Andrea Esuli, Iadh Ounis, Fabrizio Sebastiani
https://arxiv.org/abs/2506.04140

Quantifying Query Fairness Under Unawareness
Traditional ranking algorithms are designed to retrieve the most relevant items for a user's query, but they often inherit biases from data that can unfairly disadvantage vulnerable groups. Fairness in information access systems (IAS) is typically assessed by comparing the distribution of groups in a ranking to a target distribution, such as the overall group distribution in the dataset. These fairness metrics depend on knowing the true group labels for each item. However, when groups are defin…

From
"A forever home for your collection #Pocket becomes your permanent library—so even if a page you’ve saved is taken down, you’ll still have a copy of it in Pocket."
to
"Your export file will include links (URLs) of your saved items. The export does not extract the text of saved links."
Thanks for nothing,

Optimal Non-Adaptive Group Testing with One-Sided Error Guarantees
Daniel McMorrow, Jonathan Scarlett
https://arxiv.org/abs/2506.10374 https://

Optimal Non-Adaptive Group Testing with One-Sided Error Guarantees
The group testing problem consists of determining a sparse subset of defective items from within a larger set of items via a series of tests, where each test outcome indicates whether at least one defective item is included in the test. We study the approximate recovery setting, where the recovery criterion of the defective set is relaxed to allow a small number of items to be misclassified. In particular, we consider one-sided approximate recovery criteria, where we allow either only false neg…

In 1967
artist Michael Bowen advertised
"A Gathering of Tribes for the Human Be-In"
in the underground newspaper the San Francisco Oracle
to bring together the "tribes" of psychedelic San Francisco hippies and Berkeley anti-war activists.
https://exhibits.library.uc…

I'm a day or two behind with reading toots in my usual time line, but I do have some lists covering current events. And it feels very disturbing reading about the bombing in Iran (and Trump's erratic statements) AND official news items stating that and how “Europe” urges Iran to negotiate with Trump. As if there would have been any chance to solve this mess

Online Fair Allocations with Binary Valuations and Beyond
Yuanyuan Wang, Tianze Wei
https://arxiv.org/abs/2505.24321 https://arxiv.or…

Online Fair Allocations with Binary Valuations and Beyond
In an online fair allocation problem, a sequence of indivisible items arrives online and needs to be allocated to offline agents immediately and irrevocably. In our paper, we study the online allocation of either goods or chores. We adapt popular fairness notions, including envy-freeness up to one item (EF1) and maximin share fairness (MMS), and use utilitarian social welfare (USW) to measure efficiency. For both settings of items, we present a series of positive results regarding the existence…

This https://arxiv.org/abs/2410.21844 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Optimizing Perishable and Non-Perishable Product Assignment to Packaging Lines in a Sustainable Manufacturing System: An AUGMECON2VIKOR Algorithm
Identifying appropriate manufacturing systems for products can be considered a pivotal manufacturing task contributing to the optimization of operational and planning activities. It has gained importance in the food industry due to the distinct constraints and considerations posed by perishable and non-perishable items in this problem. Hence, this study proposes a new mathematical model according to knowledge discovery as well as an assignment model to optimize manufacturing systems for perisha…

that's... one way to describe it, royal mail

Earlier this month, the Copyright Office issued the third part of its report on on AI: this one covering how generative AI may infringe on copyright and whether that's fair use (short answer: maybe, maybe not). I have a new article up summarizing the report.
https://www.…

Copyright Office's report discusses whether generative AI use is fair use
Earlier this month, the Copyright Office issued the third part of its report on AI. As with the first two parts, the Copyright Office discusses arguments from people who responded to its call for comments and then provides its analysis. The three main sections in this part focus on infringement, fair use, and licensing regimes. Here, I’m going to cover what the report says about the first two items: whether using copyrighted material in generative AI infringes on owners’ rights and whether…

This https://arxiv.org/abs/2411.03502 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_eco…

Adaptive Shock Compensation in the Multi-layer Network of Global Food Production and Trade
Global food production and trade networks are highly dynamic, especially in response to shortages when countries adjust their supply strategies. In this study, we examine adjustments across 123 agri-food products from 192 countries resulting in 23616 individual scenarios of food shortage, and calibrate a multi-layer network model to understand the propagation of the shocks. We analyze shock mitigation actions, such as increasing imports, boosting production, or substituting food items. Our find…

Seven short items I call #7points.
#blogging

It can be hard to keep up with crucial news at the University of Florida because of the minimal communication from the administration. To make it easier for folks to keep up I'm starting
@index@ufwatch.org to provide short summaries of key news items with links to the sources.
https://ufwatch.org/uf-watch-keep-up-with-crucial-news-about-the-university-of-florida/
If that's helpful to you can keep up using:
Mastodon/Fediverse: @index@ufwatch.org
BlueSky: @ufwatch.bsky.social
Newsletter/Website: ufwatch.org
RSS: ufwatch.org/rss

Interact2Vec -- An efficient neural network-based model for simultaneously learning users and items embeddings in recommender systems
Pedro R. Pires, Tiago A. Almeida
https://arxiv.org/abs/2506.22648

Interact2Vec -- An efficient neural network-based model for simultaneously learning users and items embeddings in recommender systems
Over the past decade, recommender systems have experienced a surge in popularity. Despite notable progress, they grapple with challenging issues, such as high data dimensionality and sparseness. Representing users and items as low-dimensional embeddings learned via neural networks has become a leading solution. However, while recent studies show promising results, many approaches rely on complex architectures or require content data, which may not always be available. This paper presents Intera…

Clothes from UK brands found discarded in Ghana wetland dumps – video https://www.theguardian.com/environment/video/2025/jun/18/clothes-from-uk-brands-found-discarded-in-ghana-wetland-dumps-video

Taiichi Ohno: I wrote about how items waiting in a queue are a form of waste, as a cautionary tale
Scrum guys coming up with the backlog: we have created the work queue from the classic manual "Don't Create A Work Queue"

Even the export is crap
"What is contained in the export file?
Your export file will include links (URLs) of your saved items. The export does not extract the text of saved links. Additionally, the export does contain tags or highlights."

Poisoning Attacks to Local Differential Privacy for Ranking Estimation
Pei Zhan (School of Cyber Science and Technology, Shandong University, State Key Laboratory of Cryptography and Digital Economy Security, Shandong University, Qingdao, China), Peng Tang (School of Cyber Science and Technology, Shandong University, State Key Laboratory of Cryptography and Digital Economy Security, Shandong University, Qingdao, China), Yangzhuo Li (School of Cyber Science and Technology, Shandong Univ…

Poisoning Attacks to Local Differential Privacy for Ranking Estimation
Local differential privacy (LDP) involves users perturbing their inputs to provide plausible deniability of their data. However, this also makes LDP vulnerable to poisoning attacks. In this paper, we first introduce novel poisoning attacks for ranking estimation. These attacks are intricate, as fake attackers do not merely adjust the frequency of target items. Instead, they leverage a limited number of fake users to precisely modify frequencies, effectively altering item rankings to maximize ga…

How Walmart, seeking to compete with e-commerce rivals like Amazon, built a multibillion-dollar HQ in Bentonville, aiming to attract workers and woo shoppers (Kevin Draper/New York Times)
https://www.nytimes.com/2025/06/21/business/walmart-rebrand-hea…

Walmart Tries to Shed a Stodgy Vibe to Battle Digital-Native Rivals
The retailing giant is spending billions to attract workers to a new headquarters and woo shoppers with drone delivery and a broader range of items (like Louis Vuitton handbags).

Achieving Equitability with Subsidy
Yuanyuan Wang, Tianze Wei
https://arxiv.org/abs/2505.23251 https://arxiv.org/pdf/2505.23251

Achieving Equitability with Subsidy
We study the fair allocation problem of indivisible items with subsidies. In this paper, we mainly consider the notion of fairness - equitability (EQ), which requires that items be allocated such that all agents value the bundle they receive equally. Firstly, we study the upper bounds of the required subsidy to achieve EQ in different settings of items and provide the corresponding lower bounds. Secondly, we consider the bounded subsidy for achieving EQ and another popular notion of fairness - …

A dinner in #Cologne a long time ago

Natura Urbana VII 🏡
城市自然 VII 🏡
📷 Nikon FE
🎞️Ilford FP4 Plus, expired 1995
buy me ☕️ ?/请我喝杯☕️？
#filmphotography

Yiding Cao Geld mit PayPal.Me senden
Folgen Sie dem Link PayPal.Me/dingsterdingster und geben Sie den Betrag ein. Es ist bequem und sicher. Sie haben noch kein PayPal-Konto? Kein Problem.

This https://arxiv.org/abs/2503.09492 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

Learning Cascade Ranking as One Network
Cascade Ranking is a prevalent architecture in large-scale top-k selection systems like recommendation and advertising platforms. Traditional training methods focus on single-stage optimization, neglecting interactions between stages. Recent advances have introduced interaction-aware training paradigms, but still struggle to 1) align training objectives with the goal of the entire cascade ranking (i.e., end-to-end recall of ground-truth items) and 2) learn effective collaboration patterns for d…

And now I’m in Krispy Kreme having a 🍩 ☕️
One of the few places around here that actually have vegan food items at breakfast
#Vegan #KrispyKreme

My neighbour dropped by to kill some time. As we are chatting in the garage, two other groups, 5 people in total, arrive and start looking over items. My neighbour suddenly raises his voice and says, "So... it was a messy divorce?"
#YardSaleHumour

This https://arxiv.org/abs/2402.08533 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csGT_…

Grace Period is All You Need: Individual Fairness without Revenue Loss in Revenue Management
Imagine you and a friend purchase identical items at a store, yet only your friend received a discount. Would your friend's discount make you feel unfairly treated by the store? And would you be less willing to purchase from that store again in the future? Based on a large-scale online survey that we ran on Prolific, it turns out that the answers to the above questions are positive. Therefore, when allocating resources to different customers, sellers should consider both the total reward and in…

The presentations at the 2nd #AAS246 presser were about the papers https://iopscience.iop.org/article/10.3847/2041-8213/adc911 (Discovery of the Seven-ring Polycyclic Aromatic Hydrocarbon Cyanocoronene (C24H11CN) in GOTHAM Observations of TMC-1, also https://public.nrao.edu/news/cosmic-chemistry-breakthrough-largest-aromatic-molecule-found-in-deep-space/), https://arxiv.org/abs/2506.05575 (A map of the outer gas disk of the Galaxy with direct distances from young stars, also https://www.uah.edu/news/items/uah-researcher-unveils-new-map-of-milky-way-galaxy-in-atomic-hydrogen-revealing-its-clumped-flocculent-nature-for-first-time) and https://iopscience.iop.org/article/10.3847/1538-4357/adbbd9 (Surveying the Giant H ii Regions of the Milky Way with SOFIA. VII. Galactic Center Regions Sgr B1, Sgr B2, and Sgr C, also https://www.seti.org/press-release/unusual-stellar-nurseries-near-our-galaxys-center-puzzle-scientists) plus two results with apparently neither papers nor press releases going with them.

This https://arxiv.org/abs/2410.21844 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Optimizing Perishable and Non-Perishable Product Assignment to Packaging Lines in a Sustainable Manufacturing System: An AUGMECON2VIKOR Algorithm
Identifying appropriate manufacturing systems for products can be considered a pivotal manufacturing task contributing to the optimization of operational and planning activities. It has gained importance in the food industry due to the distinct constraints and considerations posed by perishable and non-perishable items in this problem. Hence, this study proposes a new mathematical model according to knowledge discovery as well as an assignment model to optimize manufacturing systems for perisha…

Improving Online Bin Covering with Little Advice
Andrej Brodnik, Bengt J. Nilsson, Gordana Vujovi\'c
https://arxiv.org/abs/2506.09004 https://

Improving Online Bin Covering with Little Advice
The online bin covering problem is: given an input sequence of items find a placement of the items in the maximum number of bins such that the sum of the items' sizes in each bin is at least~1. Boyar~{\em et~al}.\@~\cite{boyar2021} present a strategy that with $O(\log \log n)$ bits of advice, where $n$ is the length of the input sequence, achieves a competitive ratio of $8/15\approx0.5333\ldots$. We show that with a strengthened analysis and some minor improvements, the same strategy achieves t…

I want to bring back polishing, dusting, and maintaining household items, because then you actually feel them in your hands https://www.overcomecompulsivehoarding.co.uk/podcast-ep-185-engaging-with-ou…

Calibrated Recommendations: Survey and Future Directions
Diego Corr\^ea da Silva, Dietmar Jannach
https://arxiv.org/abs/2507.02643 https://

Calibrated Recommendations: Survey and Future Directions
The idea of calibrated recommendations is that the properties of the items that are suggested to users should match the distribution of their individual past preferences. Calibration techniques are therefore helpful to ensure that the recommendations provided to a user are not limited to a certain subset of the user's interests. Over the past few years, we have observed an increasing number of research works that use calibration for different purposes, including questions of diversity, biases, …

Why Multi-Interest Fairness Matters: Hypergraph Contrastive Multi-Interest Learning for Fair Conversational Recommender System
Yongsen Zheng, Zongxuan Xie, Guohua Wang, Ziyao Liu, Liang Lin, Kwok-Yan Lam
https://arxiv.org/abs/2507.02000

Why Multi-Interest Fairness Matters: Hypergraph Contrastive Multi-Interest Learning for Fair Conversational Recommender System
Unfairness is a well-known challenge in Recommender Systems (RSs), often resulting in biased outcomes that disadvantage users or items based on attributes such as gender, race, age, or popularity. Although some approaches have started to improve fairness recommendation in offline or static contexts, the issue of unfairness often exacerbates over time, leading to significant problems like the Matthew effect, filter bubbles, and echo chambers. To address these challenges, we proposed a novel fram…

Amazon's Ad Video Generator, a free tool to create gen AI ads and depict items as they would be used in the real world, is now available for sellers in the US (Jess Weatherbed/The Verge)
https://www.theverge.com/news/685160/amazon-ads-…

Amazon is about to be flooded with AI-generated video ads
Amazon Ad’s Video Generator has some new tricks and is now generally available in the US to create “photorealistic video assets” in five minutes or less.

ManifoldMind: Dynamic Hyperbolic Reasoning for Trustworthy Recommendations
Anoushka Harit, Zhongtian Sun, Suncica Hadzidedic
https://arxiv.org/abs/2507.02014

ManifoldMind: Dynamic Hyperbolic Reasoning for Trustworthy Recommendations
We introduce ManifoldMind, a probabilistic geometric recommender system for exploratory reasoning over semantic hierarchies in hyperbolic space. Unlike prior methods with fixed curvature and rigid embeddings, ManifoldMind represents users, items, and tags as adaptive-curvature probabilistic spheres, enabling personalised uncertainty modeling and geometry-aware semantic exploration. A curvature-aware semantic kernel supports soft, multi-hop inference, allowing the model to explore diverse concep…

Oversharing is becoming part of who I am, a way I process the world, connect with others, and just be unapologetically myself.
If it’s not your thing, no worries at all, I totally get it, and I’ve got a handy pinned mute ready just for you whenever you need it.
📌 Pinned Oversharing
https://s…

Combining social relations and interaction data in Recommender System with Graph Convolution Collaborative Filtering
Tin T. Tran, Vaclav Snasel, Loc Tan Nguyen
https://arxiv.org/abs/2506.02834

Combining social relations and interaction data in Recommender System with Graph Convolution Collaborative Filtering
A recommender system is an important subject in the field of data mining, where the item rating information from users is exploited and processed to make suitable recommendations with all other users. The recommender system creates convenience for e-commerce users and stimulates the consumption of items that are suitable for users. In addition to e-commerce, a recommender system is also used to provide recommendations on books to read, movies to watch, courses to take or websites to visit. Simi…

Exact and approximate maximin share allocations in multi-graphs
George Christodoulou, Symeon Mastrakoulis
https://arxiv.org/abs/2506.20317 https://

Exact and approximate maximin share allocations in multi-graphs
We study the problem of (approximate) maximin share (MMS) allocation of indivisible items among a set of agents. We focus on the graphical valuation model, previously studied by Christodolou, Fiat, Koutsoupias, and Sgouritsa ("Fair allocation in graphs", EC 2023), where the input is given by a graph where edges correspond to items, and vertices correspond to agents. An edge may have non-zero marginal value only for its incident vertices. We study additive, XOS and subadditive valuations and we …

Engineering Serendipity through Recommendations of Items with Atypical Aspects
Ramit Aditya, Razvan Bunescu, Smita Nannaware, Erfan Al-Hossami
https://arxiv.org/abs/2505.23580

Engineering Serendipity through Recommendations of Items with Atypical Aspects
A restaurant dinner or a hotel stay may lead to memorable experiences when guests encounter unexpected aspects that also match their interests. For example, an origami-making station in the waiting area of a restaurant may be both surprising and enjoyable for a customer who is passionate about paper crafts. Similarly, an exhibit of 18th century harpsichords would be atypical for a hotel lobby and likely pique the interest of a guest who has a passion for Baroque music. Motivated by this insight…

A Principled Approach to Randomized Selection under Uncertainty
Alexander Goldberg, Giulia Fanti, Nihar B. Shah
https://arxiv.org/abs/2506.19083 https://…

A Principled Approach to Randomized Selection under Uncertainty
Many decision-making processes involve evaluating and then selecting items; examples include scientific peer review, job hiring, school admissions, and investment decisions. The eventual selection is performed by applying rules or deliberations to the raw evaluations, and then deterministically selecting the items deemed to be the best. These domains feature error-prone evaluations and uncertainty about future outcomes, which undermine the reliability of such deterministic selection rules. As a…

GLoSS: Generative Language Models with Semantic Search for Sequential Recommendation
Krishna Acharya, Aleksandr V. Petrov, Juba Ziani
https://arxiv.org/abs/2506.01910

GLoSS: Generative Language Models with Semantic Search for Sequential Recommendation
We propose Generative Low-rank language model with Semantic Search (GLoSS), a generative recommendation framework that combines large language models with dense retrieval for sequential recommendation. Unlike prior methods such as GPT4Rec, which rely on lexical matching via BM25, GLoSS uses semantic search to retrieve relevant items beyond lexical matching. For query generation, we employ 4-bit quantized LlaMA-3 models fine-tuned with low-rank adaptation (LoRA), enabling efficient training and …

RecCoT: Enhancing Recommendation via Chain-of-Thought
Shuo Yang, Jiangxia Cao, Haipeng Li, Yuqi Mao, Shuchao Pang
https://arxiv.org/abs/2506.21032 https://…

RecCoT: Enhancing Recommendation via Chain-of-Thought
In real-world applications, users always interact with items in multiple aspects, such as through implicit binary feedback (e.g., clicks, dislikes, long views) and explicit feedback (e.g., comments, reviews). Modern recommendation systems (RecSys) learn user-item collaborative signals from these implicit feedback signals as a large-scale binary data-streaming, subsequently recommending other highly similar items based on users' personalized historical interactions. However, from this collaborat…

Dividing Conflicting Items Fairly
Ayumi Igarashi, Pasin Manurangsi, Hirotaka Yoneda
https://arxiv.org/abs/2506.14149 https://arxiv.or…

Dividing Conflicting Items Fairly
We study the allocation of indivisible goods under conflicting constraints, represented by a graph. In this framework, vertices correspond to goods and edges correspond to conflicts between a pair of goods. Each agent is allocated an independent set in the graph. In a recent work of Kumar et al. (2024), it was shown that a maximal EF1 allocation exists for interval graphs and two agents with monotone valuations. We significantly extend this result by establishing that a maximal EF1 allocation e…

Synergizing Implicit and Explicit User Interests: A Multi-Embedding Retrieval Framework at Pinterest
Zhibo Fan, Hongtao Lin, Haoyu Chen, Bowen Deng, Hedi Xia, Yuke Yan, James Li
https://arxiv.org/abs/2506.23060

Synergizing Implicit and Explicit User Interests: A Multi-Embedding Retrieval Framework at Pinterest
Industrial recommendation systems are typically composed of multiple stages, including retrieval, ranking, and blending. The retrieval stage plays a critical role in generating a high-recall set of candidate items that covers a wide range of diverse user interests. Effectively covering the diverse and long-tail user interests within this stage poses a significant challenge: traditional two-tower models struggle in this regard due to limited user-item feature interaction and often bias towards t…

This https://arxiv.org/abs/2404.15996 has been replaced.
link: https://scholar.google.com/scholar?q=a

Asymptotically Fair and Truthful Allocation of Public Goods
We study the fair and truthful allocation of m divisible public items among n agents, each with distinct preferences for the items. To aggregate agents' preferences fairly, we focus on finding a core solution. For divisible items, a core solution always exists and can be calculated by maximizing the Nash welfare objective. However, such a solution is easily manipulated; agents might have incentives to misreport their preferences. To mitigate this, the current state-of-the-art finds an approxima…

JointRank: Rank Large Set with Single Pass
Evgeny Dedov
https://arxiv.org/abs/2506.22262 https://arxiv.org/pdf/2506.22262

JointRank: Rank Large Set with Single Pass
Efficiently ranking relevant items from large candidate pools is a cornerstone of modern information retrieval systems -- such as web search, recommendation, and retrieval-augmented generation. Listwise rerankers, which improve relevance by jointly considering multiple candidates, are often limited in practice: either by model input size constraints, or by degraded quality when processing large sets. We propose a model-agnostic method for fast reranking large sets that exceed a model input limi…

This https://arxiv.org/abs/2506.04665 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csGT_…

An O(log log n)-approximate budget feasible mechanism for subadditive valuations
In budget-feasible mechanism design, there is a set of items $U$, each owned by a distinct seller. The seller of item $e$ incurs a private cost $\overline{c}_e$ for supplying her item. A buyer wishes to procure a set of items from the sellers of maximum value, where the value of a set $S\subseteq U$ of items is given by a valuation function $v:2^U\to \mathbb{R}_+$. The buyer has a budget of $B \in \mathbb{R}_+$ for the total payments made to the sellers. We wish to design a mechanism that is tr…

Education-Oriented Graph Retrieval-Augmented Generation for Learning Path Recommendation
Xinghe Cheng, Zihan Zhang, Jiapu Wang, Liangda Fang, Chaobo He, Quanlong Guan, Shirui Pan, Weiqi Luo
https://arxiv.org/abs/2506.22303

Education-Oriented Graph Retrieval-Augmented Generation for Learning Path Recommendation
Learning path recommendation seeks to provide learners with a structured sequence of learning items (e.g., knowledge concepts or exercises) to optimize their learning efficiency. Despite significant efforts in this area, most existing methods primarily rely on prerequisite relationships, which present two major limitations: 1) Many educational datasets do not explicitly provide prerequisite relationships between knowledge concepts, hindering the application of current learning path recommendati…

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation
Yingzhi He, Xiaohao Liu, An Zhang, Yunshan Ma, Tat-Seng Chua
https://arxiv.org/abs/2506.21579

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation
Sequential recommendation aims to predict users' future interactions by modeling collaborative filtering (CF) signals from historical behaviors of similar users or items. Traditional sequential recommenders predominantly rely on ID-based embeddings, which capture CF signals through high-order co-occurrence patterns. However, these embeddings depend solely on past interactions, lacking transferable knowledge to generalize to unseen domains. Recent advances in large language models (LLMs) have mo…

This https://arxiv.org/abs/2505.04209 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

To Judge or not to Judge: Using LLM Judgements for Advertiser Keyphrase Relevance at eBay
E-commerce sellers are recommended keyphrases based on their inventory on which they advertise to increase buyer engagement (clicks/sales). The relevance of advertiser keyphrases plays an important role in preventing the inundation of search systems with numerous irrelevant items that compete for attention in auctions, in addition to maintaining a healthy seller perception. In this work, we describe the shortcomings of training Advertiser keyphrase relevance filter models on click/sales/search …

This https://arxiv.org/abs/2503.09492 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

Learning Cascade Ranking as One Network
Cascade Ranking is a prevalent architecture in large-scale top-k selection systems like recommendation and advertising platforms. Traditional training methods focus on single-stage optimization, neglecting interactions between stages. Recent advances have introduced interaction-aware training paradigms, but still struggle to 1) align training objectives with the goal of the entire cascade ranking (i.e., end-to-end recall of ground-truth items) and 2) learn effective collaboration patterns for d…

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

Next-User Retrieval: Enhancing Cold-Start Recommendations via Generative Next-User Modeling
The item cold-start problem is critical for online recommendation systems, as the success of this phase determines whether high-quality new items can transition to popular ones, receive essential feedback to inspire creators, and thus lead to the long-term retention of creators. However, modern recommendation systems still struggle to address item cold-start challenges due to the heavy reliance on item and historical interactions, which are non-trivial for cold-start items lacking sufficient ex…