Tootfinder

An analysis of ~200 Shein items between April and July: prices spiked in April, settled at 12.5% above pre-tariff levels by late May, and jumped again in July (Reuters)
https://www.reuters.com/graphics/USA-TRUMP/TARIFF-SHEIN/lbpgzlrjzvq/

How price increases are adding up at Shein
Evidence for the impact of Trump’s trade war has shown up at the popular China-founded online retailer.

A goal-driven ruin and recreate heuristic for the 2D variable-sized bin packing problem with guillotine constraints
Jeroen Gardeyn, Tony Wauters
https://arxiv.org/abs/2508.19306

A goal-driven ruin and recreate heuristic for the 2D variable-sized bin packing problem with guillotine constraints
This paper addresses the two-dimensional bin packing problem with guillotine constraints. The problem requires a set of rectangular items to be cut from larger rectangles, known as bins, while only making use of edge-to-edge (guillotine) cuts. The goal is to minimize the total bin area needed to cut all required items. This paper also addresses variants of the problem which permit 90° rotation of items and/or a heterogeneous set of bins. A novel heuristic is introduced which is based on the ru…

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

Substack? Why would I want a substack if I can't keep up with the items from my main stack!

Happy July 29th. Shitpost4evar
#shitpost #july29

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

Enough Stuff is a free thrift store based in East Peoria, Illinois,
which is stocked with donated items and give away those items for free to customers.
They aim to meet the needs for those who are without the basic necessities of adequate clothing, home goods and food items.
But the shop is for all, whoever is in need of items but also if people just want to change up their wardrobe.

Enough Stuff

A dinner in #Cologne a long time ago

Tickling the goose's tail . . .
#ShamelesslyStolenFromSomewhereElseOnTheInternetHonestlyICantKeepTrackOfThisStuffAnymore

Recycling History: Efficient Recommendations from Contextual Dueling Bandits
Suryanarayana Sankagiri, Jalal Etesami, Pouria Fatemi, Matthias Grossglauser
https://arxiv.org/abs/2508.18841

Recycling History: Efficient Recommendations from Contextual Dueling Bandits
The contextual duelling bandit problem models adaptive recommender systems, where the algorithm presents a set of items to the user, and the user's choice reveals their preference. This setup is well suited for implicit choices users make when navigating a content platform, but does not capture other possible comparison queries. Motivated by the fact that users provide more reliable feedback after consuming items, we propose a new bandit model that can be described as follows. The algorithm rec…

Urban Diaspora IV 🎈
城市放逐 IV 🎈
📷 Nikon FE
🎞️Ilford FP4 Plus, expired 1994
buy me ☕️ ?/请我喝杯☕️？
#filmphotography

>Webshops that have no "open in new tab" option and items cannot be opened in a new tab using "crtl click". :drool:

A Non-Parametric Choice Model That Learns How Users Choose Between Recommended Options
Thorsten Krause, Harrie Oosterhuis
https://arxiv.org/abs/2507.20035 https://

A Non-Parametric Choice Model That Learns How Users Choose Between Recommended Options
Choice models predict which items users choose from presented options. In recommendation settings, they can infer user preferences while countering exposure bias. In contrast with traditional univariate recommendation models, choice models consider which competitors appeared with the chosen item. This ability allows them to distinguish whether a user chose an item due to preference, i.e., they liked it; or competition, i.e., it was the best available option. Each choice model assumes specific u…

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

Max-Min and 1-Bounded Space Algorithms for the Bin Packing Problem
Hiroshi Fujiwara, Rina Atsumi, Hiroaki Yamamoto
https://arxiv.org/abs/2508.18718 https://

Max-Min and 1-Bounded Space Algorithms for the Bin Packing Problem
In the (1-dimensional) bin packing problem, we are asked to pack all the given items into bins, each of capacity one, so that the number of non-empty bins is minimized. Zhu~[Chaos, Solitons \& Fractals 2016] proposed an approximation algorithm $MM$ that sorts the item sequence in a non-increasing order by size at the beginning, and then repeatedly packs, into the current single open bin, first as many of the largest items in the remaining sequence as possible and then as many of the smallest it…

Fairness under Equal-Sized Bundles: Impossibility Results and Approximation Guarantees
Alviona Mancho, Evangelos Markakis, Nicos Protopapas
https://arxiv.org/abs/2507.20899 http…

Fairness under Equal-Sized Bundles: Impossibility Results and Approximation Guarantees
We study the fair allocation of indivisible goods under cardinality constraints, where each agent must receive a bundle of fixed size. This models practical scenarios, such as assigning shifts or forming equally sized teams. Recently, variants of envy-freeness up to one/any item (EF1, EFX) were introduced for this setting, based on flips or exchanges of items. Namely, one can define envy-freeness up to one/any flip (EFF1, EFFX), meaning that an agent $i$ does not envy another agent $j$ after pe…

Earlier this morning the first student moved into Carol B. Bauer Hall at the Living Village—Karen Phan ‘27 M.A.R. from Plymouth, Mass. Welcome to Karen & all the other students moving today and tomorrow!
Learn more about this new regenerative student residence hall.
livingvillage.yale.edu

OmniFocus 4.7 is now available, introducing a new “Planned” date type (for specifying the date an item is scheduled for work), the ability to create mutually exclusive tags (handy in a variety of workflows, like prioritization and energy level assignment), and improved repeat functionality (including new support for setting a repeat to end after a specific date or set number of repetitions).
Enjoy!

I second Peter Sjökvist's suggestion and wonder if there is any library catalogue that has such granular identifiers.
From: Sjökvist, P. (2022). »Resource Description and Access (RDA)« – Transcription and the Dilemma of a Rare Materials Cataloger. Bibliothek Und Wissenschaft, 55, 279–285 (p. 284).

Technology-assisted Personalized Yoga for Better Health - Challenges and Outlook
Vivek Kumar, Himanshu Sahu, Hari Prabhat Gupta, Biplav Srivastava
https://arxiv.org/abs/2508.18283

Technology-assisted Personalized Yoga for Better Health - Challenges and Outlook
Yoga is a discipline of physical postures, breathing techniques, and meditative practices rooted in ancient Indian traditions, now embraced worldwide for promoting overall well-being and inner balance. The practices are a large set of items, our term for executable actions like physical poses or breath exercises, to offer for a person's well-being. However, to get benefits of Yoga tailored to a person's unique needs, a person needs to (a) discover their subset from the large and seemingly compl…

You've got mail!

Let It Go? Not Quite: Addressing Item Cold Start in Sequential Recommendations with Content-Based Initialization
Anton Pembek, Artem Fatkulin, Anton Klenitskiy, Alexey Vasilev
https://arxiv.org/abs/2507.19473

Let It Go? Not Quite: Addressing Item Cold Start in Sequential Recommendations with Content-Based Initialization
Many sequential recommender systems suffer from the cold start problem, where items with few or no interactions cannot be effectively used by the model due to the absence of a trained embedding. Content-based approaches, which leverage item metadata, are commonly used in such scenarios. One possible way is to use embeddings derived from content features such as textual descriptions as initialization for the model embeddings. However, directly using frozen content embeddings often results in sub…

A Markovian Approach for Cross-Category Complementarity in Choice Modeling
Omar El Housni, Shuo Sun, Rajan Udwani
https://arxiv.org/abs/2508.18566 https://…

A Markovian Approach for Cross-Category Complementarity in Choice Modeling
While single-purchase choice models have been widely studied in assortment optimization, customers in modern retail and e-commerce environments often purchase multiple items across distinct product categories, exhibiting both substitution and complementarity. We consider the cross-category assortment optimization problem where retailers jointly determine assortments across categories to maximize expected revenue. Most prior work on the topic either overlooks complementarity or proposes models t…

DiskJoin: Large-scale Vector Similarity Join with SSD
Yanqi Chen, Xiao Yan, Alexandra Meliou, Eric Lo
https://arxiv.org/abs/2508.18494 https://arxiv.org/pd…

DiskJoin: Large-scale Vector Similarity Join with SSD
Similarity join--a widely used operation in data science--finds all pairs of items that have distance smaller than a threshold. Prior work has explored distributed computation methods to scale similarity join to large data volumes but these methods require a cluster deployment, and efficiency suffers from expensive inter-machine communication. On the other hand, disk-based solutions are more cost-effective by using a single machine and storing the large dataset on high-performance external stor…

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.

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

After a discussion about why omitting coverage for tests is not a good idea, I added a tip to our test tutorial: https://python-basics-tutorial.readthedocs.io/en/latest/test/pytest/coverage.html#coverage-tip

Coverage
We have created an initial list of test cases. The tests in the tests/api directory test Items via the API. But how do we know whether these tests comprehensively test our code? This is where code ...

Partitioning to solve Bin Packing Problems
Angshuman Robin Goswami
https://arxiv.org/abs/2508.15780 https://arxiv.org/pdf/2508.15780

Partitioning to solve Bin Packing Problems
The Bin Packing Problem involves efficiently packing items into a limited number of bins without exceeding their capacity. In this paper, we try to answer a specific question in this field. Mathematically the combinatorial optimization problem of this classical Bin Packing can be formulated as follows "Will it be possible to distribute $n$ items with sizes $a_1, \cdots ,a_n$ in total $k$ numbers of bins such that each of the bins consists of exactly $\ell$ number of items whose combined item …

‘The ocean is spitting our rubbish back’: Italy’s museum of plastic pollution https://www.theguardian.com/environment/2025/aug/09/italy-museum-of-plastic-pollution-faded-items-beaches-ocean

Okay, so that install went well. Except for that darn Dank stuff. But I'll ask Jay about that, waybar is fine for now.
EDIT: on Slackware you start it by adding { spawn-at-startup "qs" "-c" "DankMaterialShell" } to your config.kdl
Where I stranded last time was (not) running Brave, but a { spawn "brave-browser-stable" "--enable-features=UseOzonePlatform" "--ozone-platform=wayland" } fixed that 🥳 .
Two items …

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…

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

Police recover items at NYC shooter's apartment https://www.espn.com/nfl/story/_/id/45882079/police-recover-items-nyc-shooter-las-vegas-apartment

A Self-Supervised Mixture-of-Experts Framework for Multi-behavior Recommendation
Kyungho Kim, Sunwoo Kim, Geon Lee, Kijung Shin
https://arxiv.org/abs/2508.19507 https://

A Self-Supervised Mixture-of-Experts Framework for Multi-behavior Recommendation
In e-commerce, where users face a vast array of possible item choices, recommender systems are vital for helping them discover suitable items they might otherwise overlook. While many recommender systems primarily rely on a user's purchase history, recent multi-behavior recommender systems incorporate various auxiliary user behaviors, such as item clicks and cart additions, to enhance recommendations. Despite their overall performance gains, their effectiveness varies considerably between visit…

Food Lion had a bottle of Cabernet with a dollar off offer if you bought meat. Just make a copy of your receipt, circle the meat items, and mail it in. Current postage costs 78 cents. Wot??.?

amazon_copurchases: Amazon co-purchasing network (2003)
Network of items for sale on amazon.com in 2003 and the items they "recommend" (via the "Customers Who Bought This Item Also Bought" feature). If one item is frequently co-purchased with another, then the first item recommends the second.
This network has 400727 nodes and 3200440 edges.
Tags: Economic, Commerce, Unweighted

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 …

Citizen science illuminates the nature of city lights: #LightPollution

Fair distribution of bundles
Pablo Sober\'on
https://arxiv.org/abs/2507.13421 https://arxiv.org/pdf/2507.13421

Fair distribution of bundles
In this paper, we study the problem of splitting fairly bundles of items. We show that given $n$ bundles with $m$ kinds of items in them, it is possible to distribute the value of each kind of item fairly among $r$ persons by breaking apart at most $(r-1)m$ bundles. Moreover, we can guarantee that each participant will receive roughly $n/r - mr/2$ full bundles. The proof methods are topological and use a modified form of the configuration space/test map scheme. We obtain optimal results when $r…

HathiTrust was founded in 2008 as a not-for-profit collaborative of academic and research libraries now preserving 18 million digitized items in the HathiTrust Digital Library. We offer reading access to the fullest extent allowable by U.S. and international copyright law, text and data mining tools for the entire corpus, and other emerging services based on the combined collection.

Parks gift shops directed to remove items that ‘disparage Americans’
Trump officials have directed staff at national parks to review all items in gift shops for anti-American content.
The move is part of the administration’s wider campaign to scrub federal institutions of “corrosive ideology” recognizing historical racism and sexism.

The directive instructs park staff to report by Friday any retail items that have content that “inappropriately disparages Americans past or…

Parks gift shops directed to remove items that ‘disparage Americans’
The National Park Service’s directive is part of a wider Trump administration effort to reshape how American history is told at federal institutions.

Russian attack hits US electronics plant in western Ukraine: https://benborges.xyz/2025/08/21/russian-attack-hits-us-electronics.html

Use as Directed? A Comparison of Software Tools Intended to Check Rigor and Transparency of Published Work
Peter Eckmann, Adrian Barnett, Alexandra Bannach-Brown, Elisa Pilar Bascunan Atria, Guillaume Cabanac, Louise Delwen Owen Franzen, Ma{\l}gorzata Anna Gazda, Kaitlyn Hair, James Howison, Halil Kilicoglu, Cyril Labbe, Sarah McCann, Vladislav Nachev, Martijn Roelandse, Maia Salholz-Hillel, Robert Schulz, Gerben ter Riet, Colby Vorland, Anita Bandrowski, Tracey Weissgerber

Use as Directed? A Comparison of Software Tools Intended to Check Rigor and Transparency of Published Work
The causes of the reproducibility crisis include lack of standardization and transparency in scientific reporting. Checklists such as ARRIVE and CONSORT seek to improve transparency, but they are not always followed by authors and peer review often fails to identify missing items. To address these issues, there are several automated tools that have been designed to check different rigor criteria. We have conducted a broad comparison of 11 automated tools across 9 different rigor criteria from t…

"‘The ocean is spitting our rubbish back’: Italy’s museum of plastic pollution"
#Italy #Plastic #Plastics

If you do modelling of real-world items, put this on your must-watch list: @… on FRBR, what led up to it, and how to use it wrong.
https://www.youtube.com/watch?v=d0CMuxZsAIY

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

Setup fee gets withdrawn immediately when you make a buy order or a sell order in Albion Online.
If you have 0 silver while you create a buy order or a sell order you can't make the order!
Thus if you wanna know your TRUE profit you just do [total]-(amount of items you are selling/buying * your price*0.025)
I think I probably got this right.
In my case: 161000 - 4375(calculated automatically) = 156625 = 156k silver in profit!

Google launches its virtual clothes try-on feature, letting users upload photos of themselves, in the US and updates price alerts to let users specify an amount (Aisha Malik/TechCrunch)
https://techcrunch.com/2025/07/24/googles-new-ai-feature-lets-…

Google's new AI feature lets you virtually try on clothes | TechCrunch
The feature is launching in the United States today, letting users try on apparel items in Google's Shopping Graph across Search, Google Shopping and product results on Google Images.

Integrating LLM-Derived Multi-Semantic Intent into Graph Model for Session-based Recommendation
Shuo Zhang, Xiao Li, Jiayi Wu, Fan Yang, Xiang Li, Ming Gao
https://arxiv.org/abs/2507.20147

Integrating LLM-Derived Multi-Semantic Intent into Graph Model for Session-based Recommendation
Session-based recommendation (SBR) is mainly based on anonymous user interaction sequences to recommend the items that the next user is most likely to click. Currently, the most popular and high-performing SBR methods primarily leverage graph neural networks (GNNs), which model session sequences as graph-structured data to effectively capture user intent. However, most GNNs-based SBR methods primarily focus on modeling the ID sequence information of session sequences, while neglecting the rich …

ThinkSound: Chain-of-Thought Reasoning in Multimodal Large Language Models for Audio Generation and Editing
Huadai Liu, Jialei Wang, Kaicheng Luo, Wen Wang, Qian Chen, Zhou Zhao, Wei Xue
https://arxiv.org/abs/2506.21448

ThinkSound: Chain-of-Thought Reasoning in Multimodal Large Language Models for Audio Generation and Editing
While end-to-end video-to-audio generation has greatly improved, producing high-fidelity audio that authentically captures the nuances of visual content remains challenging. Like professionals in the creative industries, such generation requires sophisticated reasoning about items such as visual dynamics, acoustic environments, and temporal relationships. We present \textbf{ThinkSound}, a novel framework that leverages Chain-of-Thought (CoT) reasoning to enable stepwise, interactive audio gener…

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…

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/

Seven short items I call #7points.
#blogging

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.

Enriching Object-Centric Event Data with Process Scopes: A Framework for Aggregation and Analysis
Shahrzad Khayatbashi, Majid Rafiei, Jiayuan Chen, Timotheus Kampik, Gregor Berg, Amin Jalali
https://arxiv.org/abs/2508.18830

Enriching Object-Centric Event Data with Process Scopes: A Framework for Aggregation and Analysis
Object-Centric Process Mining enables the analysis of complex operational behavior by capturing interactions among multiple business objects (e.g., orders, items, deliveries). These interactions are recorded using Object-Centric Event Data (OCED) formats, such as the Object-Centric Event Log (OCEL). However, existing formats lack explicit definitions of process scopes, which restricts analysis to individual processes and limits insights to a low level of granularity. In practice, OCED often spa…

Retro style fantasy fps Wizordum is coming to consoles September 23, and I'm psyched to grab it (when it goes on sale, as I usually wait for). Have to decide if I want it for Switch and/or Xbox. I played the demo on Steam a while back (it's here: https://store.steampowered.com/app/1715…

Wizordum on Steam
Wizordum is a retro FPS that puts you in the role of a Mage on a quest to track down the source of Chaos. With a wide arsenal of spells and magic items, battle your way through the world of Terrabruma in this unique blend of classic 90s shooters and modern gaming elements.

Poisson Inventory Models with Many Items: An Empirical Bayes Approach
Edward Anderson, Nam Ho-Nguyen, Peter Radchenko
https://arxiv.org/abs/2508.03074 https://

Poisson Inventory Models with Many Items: An Empirical Bayes Approach
We consider inventory decisions with many items, each of which has Poisson demand. The rate of demand for individual items is estimated on the basis of observations of past demand. The problem is to determine the items to hold in stock and the amount of each one. Our setting provides a natural framework for the application of the empirical Bayes methodology. We show how to do this in practice and demonstrate the importance of making posterior estimates of different demand levels, rather than ju…

Urban Diaspora III 🎈
城市放逐 III 🎈
📷 Nikon FE
🎞️Ilford FP4 Plus, expired 1994
buy me ☕️ ?/请我喝杯☕️？
#filmphotography

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…

We’re closing in on this month’s release of OmniFocus 4.7, with planned dates, mutually-exclusive tags, and improved repeats!
Updated test builds are now available, adding new settings for Forecast counts and summary dots, adding support for keyboard modifiers when using drag-and-drop in Forecast on iPad and visionOS (bringing parity with the support already on Mac), and making other improvements and bug fixes.

Si bien esto no es exactamente un šlbum, fue publicado en plataformas de streaming como una serie de singles luego de ser lanzado de forma exclusiva en la web de la vocalista de Paramore, Hayley Williams. 17 canciones que han titulado «Ego»
https://open.spotify.com/playlist/3gOkujQB…

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…

lol 🤦‍♂️ https://github.com/bluesky-social/social-app/commit/965bcc44dc6b5c5fa9d013b32da3cc9f8fdce93a

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

Series B, Episode 08 - Hostage
SERVALAN: Have your decoded It?
VOICE: Not yet.
SERVALAN: What is the origin of the message?
VOICE: Unspecified. No Federation code sign was given.
SERVALAN: Decode at once.
VOICE: And Counsellor Joban is here.
https://blake.torpidity.net/m/208/192

Opening the Black Box: Interpretable Remedies for Popularity Bias in Recommender Systems
Parviz Ahmadov, Masoud Mansoury
https://arxiv.org/abs/2508.17297 https://

Opening the Black Box: Interpretable Remedies for Popularity Bias in Recommender Systems
Popularity bias is a well-known challenge in recommender systems, where a small number of popular items receive disproportionate attention, while the majority of less popular items are largely overlooked. This imbalance often results in reduced recommendation quality and unfair exposure of items. Although existing mitigation techniques address this bias to some extent, they typically lack transparency in how they operate. In this paper, we propose a post-hoc method using a Sparse Autoencoder (S…

Pawn shop owner admits to fencing Burrow items https://www.espn.com/nfl/story/_/id/45781024/pawn-shop-owner-admits-fencing-joe-burrow-stolen-property

From multi-allocations to allocations, with subadditive valuations
Uriel Feige
https://arxiv.org/abs/2506.21493 https://arxiv.org/pdf…

From multi-allocations to allocations, with subadditive valuations
We consider the problem of fair allocation of $m$ indivisible items to $n$ agents with monotone subadditive valuations. For integer $d \ge 2$, a $d$-multi-allocation is an allocation in which each item is allocated to at most $d$ different agents. We show that $d$-multi-allocations can be transformed into allocations, while not losing much more than a factor of $d$ in the value that each agent receives. One consequence of this result is that for allocation instances with equal entitlements and …

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).

Refining Text Generation for Realistic Conversational Recommendation via Direct Preference Optimization
Manato Tajiri, Michimasa Inaba
https://arxiv.org/abs/2508.19918 https://

Refining Text Generation for Realistic Conversational Recommendation via Direct Preference Optimization
Conversational Recommender Systems (CRSs) aim to elicit user preferences via natural dialogue to provide suitable item recommendations. However, current CRSs often deviate from realistic human interactions by rapidly recommending items in brief sessions. This work addresses this gap by leveraging Large Language Models (LLMs) to generate dialogue summaries from dialogue history and item recommendation information from item description. This approach enables the extraction of both explicit user s…

amazon_copurchases: Amazon co-purchasing network (2003)
Network of items for sale on amazon.com in 2003 and the items they "recommend" (via the "Customers Who Bought This Item Also Bought" feature). If one item is frequently co-purchased with another, then the first item recommends the second.
This network has 410236 nodes and 3356824 edges.
Tags: Economic, Commerce, Unweighted

Follow me on Ko-fi to receive page, gallery, and commission updates.
Remember to check out the Free and Pay What You Want items in the shop!
#KoFi #KofiChallenge

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…

On Albion EU right now in "Highland Cross Marketplace" part of Martlock's beginner area
they are not selling T7 Pork Pies at all...so here presents itself an opportunity...
I could sell I dunno, depending on price, 20% the price I buy em with from Martlock. I could start at 50 items or less...and then we'll see...
25 in the chest and 25 that I put inside the marketplace...so now I'm going to Martlock...to buy and then return with the sell order...

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 …

PBiLoss: Popularity-Aware Regularization to Improve Fairness in Graph-Based Recommender Systems
Mohammad Naeimi, Mostafa Haghir Chehreghani
https://arxiv.org/abs/2507.19067 http…

PBiLoss: Popularity-Aware Regularization to Improve Fairness in Graph-Based Recommender Systems
Recommender systems, especially those based on graph neural networks (GNNs), have achieved remarkable success in capturing user-item interaction patterns. However, they remain susceptible to popularity bias--the tendency to over-recommend popular items--resulting in reduced content diversity and compromised fairness. In this paper, we propose PBiLoss, a novel regularization-based loss function designed to counteract popularity bias in graph-based recommender models explicitly. PBiLoss augments …

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…

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

Fashion-AlterEval: A Dataset for Improved Evaluation of Conversational Recommendation Systems with Alternative Relevant Items
Maria Vlachou
https://arxiv.org/abs/2507.18017 http…

Fashion-AlterEval: A Dataset for Improved Evaluation of Conversational Recommendation Systems with Alternative Relevant Items
In Conversational Recommendation Systems (CRS), a user provides feedback on recommended items at each turn, leading the CRS towards improved recommendations. Due to the need for a large amount of data, a user simulator is employed for both training and evaluation. Such user simulators critique the current retrieved item based on knowledge of a single target item. However, system evaluation in offline settings with simulators is limited by the focus on a single target item and their unlimited pa…

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

Group Fair Matchings using Convex Cost Functions
Atasi Panda, Harsh Sharma, Anand Louis, Prajakta Nimbhorkar
https://arxiv.org/abs/2508.12549 https://arxiv…

Group Fair Matchings using Convex Cost Functions
We consider the problem of assigning items to platforms where each item has a utility associated with each of the platforms to which it can be assigned. Each platform has a soft constraint over the total number of items it serves, modeled via a convex cost function. Additionally, items are partitioned into groups, and each platform also incurs group-specific convex cost over the number of items from each group that can be assigned to the platform. These costs promote group fairness by penalizin…

Park Discovery 🏞️
公园探险 🏞️
📷 Nikon FE
🎞️Lucky SHD 400
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.

Designing Rules to Pick a Rule: Aggregation by Consistency
Ratip Emin Berker, Ben Armstrong, Vincent Conitzer, Nihar B. Shah
https://arxiv.org/abs/2508.17177 https://

Designing Rules to Pick a Rule: Aggregation by Consistency
Given a set of items and a set of evaluators who all individually rank them, how do we aggregate these evaluations into a single societal ranking? Work in social choice and statistics has produced many aggregation methods for this problem, each with its desirable properties, but also with its limitations. Further, existing impossibility results rule out designing a single method that achieves every property of interest. Faced with this trade-off between incompatible desiderata, how do we decide…

Smash-and-grab thieves in Seattle made off with an estimated $2m in diamonds, luxury watches, gold and other items in a daring midday jewelry store robbery that took just about 90 seconds, police said on Friday.
Video from the west Seattle store’s surveillance cameras shows four masked suspects shattering the locked glass front door with hammers and then ransacking six display cases on Thursday.
One display held about $750,000 worth in Rolex watches, police said in a statement, and…

Membership Inference Attacks on LLM-based Recommender Systems
Jiajie He, Yuechun Gu, Min-Chun Chen, Keke Chen
https://arxiv.org/abs/2508.18665 https://arxi…

Membership Inference Attacks on LLM-based Recommender Systems
Large language models (LLMs) based Recommender Systems (RecSys) can flexibly adapt recommendation systems to different domains. It utilizes in-context learning (ICL), i.e., the prompts, to customize the recommendation functions, which include sensitive historical user-specific item interactions, e.g., implicit feedback like clicked items or explicit product reviews. Such private information may be exposed to novel privacy attack. However, no study has been done on this important issue. We desig…

Modeling User Preferences as Distributions for Optimal Transport-based Cross-domain Recommendation under Non-overlapping Settings
Ziyin Xiao, Toyotaro Suzumura
https://arxiv.org/abs/2508.16210

Modeling User Preferences as Distributions for Optimal Transport-based Cross-domain Recommendation under Non-overlapping Settings
Cross-Domain Recommender (CDR) systems aim to transfer knowledge from dense to sparse domains, alleviating data sparsity and cold-start issues in single-domain recommendation. While many methods assume overlapping users or items to connect domains, this is often unrealistic in real-world settings. Thus, non-overlapping CDR systems, which require no shared users or items, are needed. However, non-overlapping CDR is challenging due to: (1) the absence of overlap preventing direct bridges betwee…

MMQ: Multimodal Mixture-of-Quantization Tokenization for Semantic ID Generation and User Behavioral Adaptation
Yi Xu, Moyu Zhang, Chenxuan Li, Zhihao Liao, Haibo Xing, Hao Deng, Jinxin Hu, Yu Zhang, Xiaoyi Zeng, Jing Zhang
https://arxiv.org/abs/2508.15281

MMQ: Multimodal Mixture-of-Quantization Tokenization for Semantic ID Generation and User Behavioral Adaptation
Recommender systems traditionally represent items using unique identifiers (ItemIDs), but this approach struggles with large, dynamic item corpora and sparse long-tail data, limiting scalability and generalization. Semantic IDs, derived from multimodal content such as text and images, offer a promising alternative by mapping items into a shared semantic space, enabling knowledge transfer and improving recommendations for new or rare items. However, existing methods face two key challenges: (1) …

Diverse Negative Sampling for Implicit Collaborative Filtering
Yueqing Xuan, Kacper Sokol, Mark Sanderson, Jeffrey Chan
https://arxiv.org/abs/2508.14468 https://

Diverse Negative Sampling for Implicit Collaborative Filtering
Implicit collaborative filtering recommenders are usually trained to learn user positive preferences. Negative sampling, which selects informative negative items to form negative training data, plays a crucial role in this process. Since items are often clustered in the latent space, existing negative sampling strategies normally oversample negative items from the dense regions. This leads to homogeneous negative data and limited model expressiveness. In this paper, we propose Diverse Negative …

Fair Allocation with Money: What is Your Objective?
Noga Klein Elmalem, Rica Gonen, Erel Segal-Halevi
https://arxiv.org/abs/2506.18794 https://

Fair Allocation with Money: What is Your Objective?
When allocating indivisible items, there are various ways to use monetary transfers for eliminating envy. Particularly, one can apply a balanced vector of transfer payments, or charge each agent a positive amount, or -- contrarily -- give each agent a positive amount as a ``subsidy''. In each model, one can aim to minimize the amount of payments used; this aim translates into different optimization objectives in each setting. This note compares the various models, and the relations between uppe…

Semantic-enhanced Modality-asymmetric Retrieval for Online E-commerce Search
Zhigong Zhou, Ning Ding, Xiaochuan Fan, Yue Shang, Yiming Qiu, Jingwei Zhuo, Zhiwei Ge, Songlin Wang, Lin Liu, Sulong Xu, Han Zhang
https://arxiv.org/abs/2506.20330

Semantic-enhanced Modality-asymmetric Retrieval for Online E-commerce Search
Semantic retrieval, which retrieves semantically matched items given a textual query, has been an essential component to enhance system effectiveness in e-commerce search. In this paper, we study the multimodal retrieval problem, where the visual information (e.g, image) of item is leveraged as supplementary of textual information to enrich item representation and further improve retrieval performance. Though learning from cross-modality data has been studied extensively in tasks such as visual…

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…

LLM-Enhanced Reranking for Complementary Product Recommendation
Zekun Xu, Yudi Zhang
https://arxiv.org/abs/2507.16237 https://arxiv.o…

LLM-Enhanced Reranking for Complementary Product Recommendation
Complementary product recommendation, which aims to suggest items that are used together to enhance customer value, is a crucial yet challenging task in e-commerce. While existing graph neural network (GNN) approaches have made significant progress in capturing complex product relationships, they often struggle with the accuracy-diversity tradeoff, particularly for long-tail items. This paper introduces a model-agnostic approach that leverages Large Language Models (LLMs) to enhance the reranki…

A Universal Framework for Offline Serendipity Evaluation in Recommender Systems via Large Language Models
Yu Tokutake, Kazushi Okamoto, Kei Harada, Atsushi Shibata, Koki Karube
https://arxiv.org/abs/2508.17571

A Universal Framework for Offline Serendipity Evaluation in Recommender Systems via Large Language Models
Serendipity in recommender systems (RSs) has attracted increasing attention as a concept that enhances user satisfaction by presenting unexpected and useful items. However, evaluating serendipitous performance remains challenging because its ground truth is generally unobservable. The existing offline metrics often depend on ambiguous definitions or are tailored to specific datasets and RSs, thereby limiting their generalizability. To address this issue, we propose a universally applicable eval…

Multidimensional Budget-Feasible Mechanism Design
Rian Neogi, Kanstantsin Pashkovich, Chaitanya Swamy
https://arxiv.org/abs/2508.09367 https://arxiv.org/pd…

Multidimensional Budget-Feasible Mechanism Design
In budget-feasible mechanism design, a buyer wishes to procure a set of items of maximum value from self-interested players. We have a valuation function $v:2^U \to \mathbb{R}_+$, where $U$ is the set of all items, where $v(S)$ specifies the value obtained from set $S$ of items. The entirety of current work on budget-feasible mechanisms has focused on the single-dimensional setting, wherein each player holds a single item $e$ and incurs a private cost $c_e$ for supplying item $e$. We introduc…

Bootstrapping Conditional Retrieval for User-to-Item Recommendations
Hongtao Lin, Haoyu Chen, Jaewon Jang, Jiajing Xu
https://arxiv.org/abs/2508.16793 https://

Bootstrapping Conditional Retrieval for User-to-Item Recommendations
User-to-item retrieval has been an active research area in recommendation system, and two tower models are widely adopted due to model simplicity and serving efficiency. In this work, we focus on a variant called \textit{conditional retrieval}, where we expect retrieved items to be relevant to a condition (e.g. topic). We propose a method that uses the same training data as standard two tower models but incorporates item-side information as conditions in query. This allows us to bootstrap new c…

Preference Trajectory Modeling via Flow Matching for Sequential Recommendation
Li Li, Mingyue Cheng, Yuyang Ye, Zhiding Liu, Enhong Chen
https://arxiv.org/abs/2508.17618 https:/…

Preference Trajectory Modeling via Flow Matching for Sequential Recommendation
Sequential recommendation predicts each user's next item based on their historical interaction sequence. Recently, diffusion models have attracted significant attention in this area due to their strong ability to model user interest distributions. They typically generate target items by denoising Gaussian noise conditioned on historical interactions. However, these models face two critical limitations. First, they exhibit high sensitivity to the condition, making it difficult to recover target …

MISS: Multi-Modal Tree Indexing and Searching with Lifelong Sequential Behavior for Retrieval Recommendation
Chengcheng Guo, Junda She, Kuo Cai, Shiyao Wang, Qigen Hu, Qiang Luo, Kun Gai, Guorui Zhou
https://arxiv.org/abs/2508.14515

MISS: Multi-Modal Tree Indexing and Searching with Lifelong Sequential Behavior for Retrieval Recommendation
Large-scale industrial recommendation systems typically employ a two-stage paradigm of retrieval and ranking to handle huge amounts of information. Recent research focuses on improving the performance of retrieval model. A promising way is to introduce extensive information about users and items. On one hand, lifelong sequential behavior is valuable. Existing lifelong behavior modeling methods in ranking stage focus on the interaction of lifelong behavior and candidate items from retrieval stag…

CORONA: A Coarse-to-Fine Framework for Graph-based Recommendation with Large Language Models
Junze Chen, Xinjie Yang, Cheng Yang, Junfei Bao, Zeyuan Guo, Yawen Li, Chuan Shi
https://arxiv.org/abs/2506.17281

CORONA: A Coarse-to-Fine Framework for Graph-based Recommendation with Large Language Models
Recommender systems (RSs) are designed to retrieve candidate items a user might be interested in from a large pool. A common approach is using graph neural networks (GNNs) to capture high-order interaction relationships. As large language models (LLMs) have shown strong capabilities across domains, researchers are exploring their use to enhance recommendation. However, prior work limits LLMs to re-ranking results or dataset augmentation, failing to utilize their power during candidate filtering…

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…