Tootfinder

‘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

We're eating good tonight! >:3

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 403394 nodes and 3387388 edges.
Tags: Economic, Commerce, Unweighted

"Meme Marketing in Social Media: Ein medienpraxeografischer Vergleich von Memes und Werbung" http://omeka.buechner-verlag.de/items/show/38 #socialmedia

Detecting Legend Items on Historical Maps Using GPT-4o with In-Context Learning
Sofia Kirsanova, Yao-Yi Chiang, Weiwei Duan
https://arxiv.org/abs/2510.08385 https://

Detecting Legend Items on Historical Maps Using GPT-4o with In-Context Learning
Historical map legends are critical for interpreting cartographic symbols. However, their inconsistent layouts and unstructured formats make automatic extraction challenging. Prior work focuses primarily on segmentation or general optical character recognition (OCR), with few methods effectively matching legend symbols to their corresponding descriptions in a structured manner. We present a method that combines LayoutLMv3 for layout detection with GPT-4o using in-context learning to detect and …

Wondering if this would be useful?
(I messed up while screen recording this & accidentally mentioned everyone 😂 — now deleted, sorry 🙇‍♂️)
#PhanpySocialDev (still on my local, not on dev site)
#Design

Building a Runtime JAR inspector in 10 hours
https://devblogs.microsoft.com/java/building-a-runtime-jar-inspector-in-10-hours/

Generation and annotation of item usage scenarios in e-commerce using large language models
Madoka Hagiri, Kazushi Okamoto, Koki Karube, Kei Harada, Atsushi Shibata
https://arxiv.org/abs/2510.07885

Generation and annotation of item usage scenarios in e-commerce using large language models
Complementary recommendations suggest combinations of useful items that play important roles in e-commerce. However, complementary relationships are often subjective and vary among individuals, making them difficult to infer from historical data. Unlike conventional history-based methods that rely on statistical co-occurrence, we focus on the underlying usage context that motivates item combinations. We hypothesized that people select complementary items by imagining specific usage scenarios an…

The General Expiration Streaming Model: Diameter, $k$-Center, Counting, Sampling, and Friends
Lotte Blank, Sergio Cabello, MohammadTaghi Hajiaghayi, Robert Krauthgamer, Sepideh Mahabadi, Andr\'e Nusser, Jeff M. Phillips, Jonas Sauer
https://arxiv.org/abs/2509.07587

The General Expiration Streaming Model: Diameter, $k$-Center, Counting, Sampling, and Friends
An important thread in the study of data-stream algorithms focuses on settings where stream items are active only for a limited time. We introduce a new expiration model, where each item arrives with its own expiration time. The special case where items expire in the order that they arrive, which we call consistent expirations, contains the classical sliding-window model of Datar, Gionis, Indyk, and Motwani [SICOMP 2002] and its timestamp-based variant of Braverman and Ostrovsky [FOCS 2007]. …

"Monopole im medienindustriellen Komplex? : Verwertungsgesellschaften gestern, heute, morgen" http://omeka.buechner-verlag.de/items/show/37 #GEMA

Dark prediction:
- Intellectual Property Class Action against AI companies gains traction
- AI companies use this as a plausible excuse to bail on AGI tech (that doesn’t exist)
- We see a pop like we saw “shipping heavy items by mail isn’t sustainable?!” pop in 2001
- AI companies fail, overwhelmingly, blaming only the IP Class Action
- The Money switches to a new/old grift; maybe back to crypto… lots of GPUs available
- In 5 years, everyone forgets and we have…

Chico Mello - "Helinho Brandão" (1984)
#NowPlaying #BrazilianMusic #MúsicaBrasileña

An analysis of nearly 50 Amazon purchases over six months in 2025: during the October 7-8 Prime Day sales, average savings were only 0.6% and some items went up (Geoffrey A. Fowler/Washington Post)
https://www.washingtonpost.com/technology/2025/10/09/amazon-prim…

I tracked Amazon’s Prime Day prices. We’ve been played.
Here’s what you should do to actually get a good deal on Amazon.

Panicked message from the boss. Looks like one of the documentation files is corrupted. We haven't had the time to cross train that process. Too many manual steps to extract the information from the repository, download to the network work folder, import into Word format, locate specific items and run the macro to format those, export to PDF and then reindex the production doc folder with the change.

@… @… looks like adjusting your image sizes in Eleventy Image, inlining your CSS, and maybe a fetchpriority=high paired with loading=eager to improve your LCP are the big ticket items reported there!
But the site is fast as-is so …

aus der reihe "amüsante buchtitel" heute: "»Vrummmummmmm FVISH!« : Soundscapes as Part of Constant Conversations in Action-Adventure Video Game Heterotopias" http://omeka.buechner-verlag.de/items/show/39

Post from a friend about his bike getting stolen:
"My bike was in the very back corner of our garage, they passed my wife's bike, and they left our cars and other garage items alone.
They left a Schwinn mountain bike leaned against the garage.
I'm not upset to lose a rather uncomfortable old bike I paid $300 off of Craigslist 14 years ago. I won't be able to take the kids on a bike ride until I fix this.
I'd rather help whoever this is get the ri…

Efficient Multimodal Streaming Recommendation via Expandable Side Mixture-of-Experts
Yunke Qu, Liang Qu, Tong Chen, Quoc Viet Hung Nguyen, Hongzhi Yin
https://arxiv.org/abs/2508.05993

Efficient Multimodal Streaming Recommendation via Expandable Side Mixture-of-Experts
Streaming recommender systems (SRSs) are widely deployed in real-world applications, where user interests shift and new items arrive over time. As a result, effectively capturing users' latest preferences is challenging, as interactions reflecting recent interests are limited and new items often lack sufficient feedback. A common solution is to enrich item representations using multimodal encoders (e.g., BERT or ViT) to extract visual and textual features. However, these encoders are pretrained…

Love watching artisans and craftspeople at work.
https://www.instagram.com/reel/DQjobwXidDZ/?igsh=MWxrbmZ4cHY4eG1lNg==

Alexey Dmitriev on Instagram: ""Homeless" Knitted items always contain a touch of the author's warmth and love, and in a sense, strong bonds are established between the giver and the receiver. But when this love is conditional and the warmth is insufficient, the bonds quickly break down. * * * #contemporaryart #sculptor #metalwork #reklamdeğil #modernartist"
34K likes, 545 comments - demant_made on November 2, 2025: ""Homeless" Knitted items always contain a touch of the author's warmth and love, and in a sense, strong bonds are established between the giver and the receiver. But when this love is conditional and the warmth is insufficient, the bonds quickly break down. * * * #contemporaryart #sculptor #metalwork #reklamdeğil #modernartist".

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 403394 nodes and 3387388 edges.
Tags: Economic, Commerce, Unweighted

Der Standard überraschte in seiner Besprechung der Fleisch!-Ausstellung des Wien Museum heute mit einer gar nicht so trivialen Kurrent-Leseübung. https://www.wienmuseum.at/items/uploads/images/1756113454_iqFPz8JM7wxF.jpg

Forget about nation-states for a moment: The top four items in today's Metacurity all deal with serious cybersecurity threats emanating from teen hackers.
Don't miss today's issue for the complete run-down of infosec developments you should know, including
--ShinyHunters threatens to release data stolen from dozens of Fortune 500 firms,
--Salesforce refuses to pay ShinyHunters ransom,
--Qantas braces for the release of its data,
--Two teens busted for…

ShinyHunters threatens to release data stolen from dozens of Fortune 500 firms
Salesforce refuses to pay ShinyHunters ransom, Qantas braces for the release of its data, Two teens busted for Kido nurseries cyberattack, Qilin claims attack on Asahi, Chinese hackers infiltrated Williams & Connolly, DPRK hackers have stolen $2b in crypto so far in 2025, much more

#30DayMapChallenge 🗺️ Day 4️⃣: My data
Here is a hexbinned map of the over 1600 #Wikidata items I’ve created that have coordinates in the #Philippines 🇵🇭. The vast majority of these are items o…

Trump Claims Video Of Items Being Tossed From WH Window Is AI (White House Spox Says Video Is Real) - Joe.My.God.
https://www.joemygod.com/2025/09/trump-claims-video-of-items-being-tossed-from-wh-window-is-ai-white-house-spox-says-video-is-real/

Re the “expert” opinion: see items 4-5 in https://how.complexsystems.fail

"From beef to timber, a new era of labels will reveal where your shopping comes from"
#Food #Climate #ClimateChange

From beef to timber, a new era of labels will reveal where your shopping comes from
Have you noticed new country-of-origin labels or QR codes on your shopping? Tighter labelling on items such as beef and timber mean shoppers can avoid products linked to illegal logging or deforestation.

Fair metric distortion for matching with preferences
Jabari Hastings, Prasanna Ramakrishnan
https://arxiv.org/abs/2510.05460 https://arxiv.org/pdf/2510.054…

Fair metric distortion for matching with preferences
We consider the matching problem in the metric distortion framework. There are $n$ agents and $n$ items occupying points in a shared metric space, and the goal is to design a matching mechanism that outputs a low-cost matching between the agents and items, using only agents' ordinal rankings of the candidates by distance. A mechanism has distortion $α$ if it always outputs a matching whose cost is within a factor of $α$ of the optimum, in every instance regardless of the metric space. Typic…

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 403394 nodes and 3387388 edges.
Tags: Economic, Commerce, Unweighted

Emotionally Vulnerable Subtype of Internet Gaming Disorder: Measuring and Exploring the Pathology of Problematic Generative AI Use
Haocan Sun, Di Wua, Weizi Liu, Guoming Yua, Mike Yao
https://arxiv.org/abs/2510.06908

Emotionally Vulnerable Subtype of Internet Gaming Disorder: Measuring and Exploring the Pathology of Problematic Generative AI Use
Concerns over the potential over-pathologization of generative AI (GenAI) use and the lack of conceptual clarity surrounding GenAI addiction call for empirical tools and theoretical refinement. This study developed and validated the PUGenAIS-9 (Problematic Use of Generative Artificial Intelligence Scale-9 items) and examined whether PUGenAIS reflects addiction-like patterns under the Internet Gaming Disorder (IGD) framework. Using samples from China and the United States (N = 1,508), we conduct…

Optimal streaming algorithm for detecting $\ell_2$ heavy hitters in random order streams
Santhoshini Velusamy, Huacheng Yu
https://arxiv.org/abs/2509.07286 https://

Optimal streaming algorithm for detecting $\ell_2$ heavy hitters in random order streams
Given a stream $x_1,x_2,\dots,x_n$ of items from a Universe $U$ of size $\mathsf{poly}(n)$, and a parameter $ε>0$, an item $i\in U$ is said to be an $\ell_2$ heavy hitter if its frequency $f_i$ in the stream is at least $\sqrt{εF_2}$, where $F_2=\sqrt{\sum_{i\in U} f_i^2}$. The classical $\mathsf{CountSketch}$ algorithm due to Charikar, Chen, and Farach-Colton [2004], was the first algorithm to detect $\ell_2$ heavy hitters using $O\left(\frac{\log^2 n}ε\right)$ bits of space, and their algo…

Cover 32: Will Daniel Jones become the latest late bloomer QB? Game balls, biggest gaffes from Week 1

https://www.cbssports.com/nfl/news/cover-3

A nutritionally informed model for Bayesian variable selection with metabolite response variables
Dylan Clark-Boucher, Brent A Coull, Harrison T Reeder, Fenglei Wang, Qi Sun, Jacqueline R Starr, Kyu Ha Lee
https://arxiv.org/abs/2509.06779

A nutritionally informed model for Bayesian variable selection with metabolite response variables
Understanding the pathways through which diet affects human metabolism is a central task in nutritional epidemiology. This article proposes novel methodology to identify food items associated with blood metabolites in two cohorts of healthcare professionals. We analyze 30 food intake variables that exhibit relationship structure through their correlations and nutritional attributes. The metabolic responses include 244 compounds measured by mass spectrometry, presenting substantial challenges th…

'It's Just a Mess:' 23 People Explain How Tariffs Have Suddenly Ruined Their Hobby https://www.404media.co/its-just-a-mess-23-people-explain-how-tariffs-have-suddenly-ruined-their-hobby/

New #Bandcamp purchase!
Imperium Delirium by Shadow Of Intent
#BandcampFriday

Classic - Breakfast in America (1979) von
#Supertramp #Model Kate Murtagh im Jahr 2016
https://www.instagram.com/p/DJquMx6Oany/

COVER ART MATTERS on Instagram: "In 2016, Kate Murtagh, the actress and model who famously portrayed the waitress on Supertramp’s iconic Breakfast in America album cover, was 95 years old. That year, a touching photo surfaced online showing her recreating the playful expression she made in 1979, a wide, cheeky smile and raised eyebrows that had become part of rock history. The original album cover featured Murtagh dressed as a diner waitress styled after the Statue of Liberty, holding a glass of orange juice in place of a torch and a menu instead of a tablet. Behind her was a whimsical model of the New York City skyline made entirely from breakfast items like cereal boxes, egg cartons, and cutlery, perfectly matching the album’s satirical take on American culture. Kate Murtagh passed away in October 2017 at the age of 96, leaving behind one of the most memorable images in rock music history. Art Direction by Mike Doud Design by Mick Haggerty Photography by Aaron Rapoport"
151K likes, 570 comments - coverartmatters on May 15, 2025: "In 2016, Kate Murtagh, the actress and model who famously portrayed the waitress on Supertramp’s iconic Breakfast in America album cover, was 95 years old. That year, a touching photo surfaced online showing her recreating the playful expression she made in 1979, a wide, cheeky smile and raised eyebrows that had become part of rock history. The original album cover featured Murtagh dressed as a diner waitress styled after the Statu…

Ok, another complaint about MacOS26... when a file modal appears, switching between sidebar items is slow. It used to be instant, now it take a few seconds.
FWIW, I'm using a Mac Mini M2Pro 16/500
#MacOS26 #Apple

deep new project by john brackett, @…, examining documents from the #GratefulDead business archive at UC santa cruz. he's got a new scholarly book out in the spring about "touch of grey" (!!). his last was…

"Hauling items for the mob": "Independent promotion companies," payola, and "Touch of Grey" (1987)
This is a document that I examine in my forthcoming book, Touch of Grey, or, How the Grateful Dead Became Pop Stars (forthcoming spring 2026 from Duke University Press).

Semantic Item Graph Enhancement for Multimodal Recommendation
Xiaoxiong Zhang, Xin Zhou, Zhiwei Zeng, Dusit Niyato, Zhiqi Shen
https://arxiv.org/abs/2508.06154 https://

Semantic Item Graph Enhancement for Multimodal Recommendation
Multimodal recommendation systems have attracted increasing attention for their improved performance by leveraging items' multimodal information. Prior methods often build modality-specific item-item semantic graphs from raw modality features and use them as supplementary structures alongside the user-item interaction graph to enhance user preference learning. However, these semantic graphs suffer from semantic deficiencies, including (1) insufficient modeling of collaborative signals among ite…

Had so much fun today at the V&A East Storehouse in London - a spectacular #museum and public display of their stored items.
Marvellous exhibits inside great #architecture
#exhibition

Are international happiness rankings reliable?
Christopher P Barrington-Leigh
https://arxiv.org/abs/2509.06867 https://arxiv.org/pdf/2509.06867

Are international happiness rankings reliable?
Global comparisons of wellbeing increasingly rely on survey questions that ask respondents to evaluate their lives, most commonly in the form of "life satisfaction" and "Cantril ladder" items. These measures underpin international rankings such as the World Happiness Report and inform policy initiatives worldwide, yet their comparability has not been established with contemporary global data. Using the Gallup World Poll, Global Flourishing Study, and World Values Survey, I show that the two que…

Some notes as a tiny blogpost on #BerlinFediDay: https://blog.johl.io/berlin-fediverse-day-2025/

I'm in tears... my old #Synology DS416play is bloody fast after I've upgraded the RAM from the default 1GB to 8GB. The web interface now loads snappy while it almost wasn't loading at all before.

Replaced article(s) found for cs.DM. https://arxiv.org/list/cs.DM/new
[1/1]:
- Allocation of Indivisible Items with a Common Preference Graph: Minimizing Total Dissatisfaction
Chiarelli, Dallard, Darmann, Lendl, Milani\v{c}, Mur\v{s}i\v{c}, Pferschy

Just grabbed the Play for Peace - Games for Palestine 2025 Charity Bundle. It has 382 games from 248 creators for just $8, and they've raised over $14k so far. The bundle has cozy narrative sims, meditative adventures, action games, visual novel tools, experimental sims, an RPG about being a cow, and much more: https://

Moody Urbanity II 🟩
情绪化城市 II 🟩
📷 Nikon FE
🎞️ Lucky SHD 400
#filmphotography #Photography #blackandwhite

On the Capacity of Self-Attention
Micah Adler
https://arxiv.org/abs/2509.22840 https://arxiv.org/pdf/2509.22840

On the Capacity of Self-Attention
While self-attention is known to learn relations among tokens, we lack a formal understanding of its capacity: how many distinct relations can a single layer reliably recover for a given budget? To formalize this, we introduce Relational Graph Recognition (RGR), where the key-query channel represents a graph on $m$ items with $m'$ directed edges, and, given a context of items, must recover the neighbors of each item. We measure resources by the total key dimension $D_K = h\,d_k$. Within this …

Beyond Single Labels: Improving Conversational Recommendation through LLM-Powered Data Augmentation
Haozhe Xu, Xiaohua Wang, Changze Lv, Xiaoqing Zheng
https://arxiv.org/abs/2508.05657

Beyond Single Labels: Improving Conversational Recommendation through LLM-Powered Data Augmentation
Conversational recommender systems (CRSs) enhance recommendation quality by engaging users in multi-turn dialogues, capturing nuanced preferences through natural language interactions. However, these systems often face the false negative issue, where items that a user might like are incorrectly labeled as negative during training, leading to suboptimal recommendations.Expanding the label set through data augmentation presents an intuitive solution but faces the challenge of balancing two key as…

Leather shop customers want their items back #guthrie #Oklahoma
https://kfor.com/…

Amazon opens a new 10,000-square-foot automated Whole Foods store in Pennsylvania partly staffed by robots; customers can scan and order items from the aisles (Matt Day/Bloomberg)
https://www.bloomberg.com/news/articles/2025-11-05…

From SPEC
Repair Café News
Next up:
📍 Kitsilano Community Centre
📅 Saturday, October 11, 2025
🕤 9:30am–1:30pm PT
Bring your small appliances, clothing, bikes, and more — our team of volunteer fixers is ready to help you repair, learn, and connect with your community. Full schedule available and registration for the October Café available at

Repair Café - SPEC
SPEC brings together repair volunteers and community members at Repair Cafés in Metro Vancouver to fix household items and divert waste.

Does anyone have experience with using yt-dlp to download a large number of ... items? Does YT block your IP at some point?
Asking for a friend ...

Wat ik al zei: het #kieskompas is dusdanig slecht, ik vind het een scam. Als het per ongeluk is, dan zouden ze het in moeten trekken. https://stukroodvlees.nl/kieskompas-nou-doet-u-het-weer/

Kieskompas gaat weer in de fout - StukRoodVlees
Gisteren kwam het Kieskompas voor de Tweede Kamerverkiezingen van 2025 online. Vier geleden schreef ik een kritisch stuk over deze populaire stemhulp. Op in ieder geval deze punten rammelde het Kieskompas: 1) het ruimtelijk model was geen goede weergave van de partijenruimte en 2) het Kieskompas gebruikte ten onrechte wisselende items om veranderingen door de […]

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

ITDR: An Instruction Tuning Dataset for Enhancing Large Language Models in Recommendations
Zekun Liu, Xiaowen Huang, Jitao Sang
https://arxiv.org/abs/2508.05667 https://

ITDR: An Instruction Tuning Dataset for Enhancing Large Language Models in Recommendations
Large language models (LLMs) have demonstrated outstanding performance in natural language processing tasks. However, in the field of recommendation systems, due to the structural differences between user behavior data and natural language, LLMs struggle to effectively model the associations between user preferences and items. Although prompt-based methods can generate recommendation results, their inadequate understanding of recommendation tasks leads to constrained performance. To address thi…

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 262111 nodes and 1234877 edges.
Tags: Economic, Commerce, Unweighted

"Repair cafes bringing new life to cherished items, building communities and boosting sustainability"
#UK #UnitedKingdom #Ireland

2 issues resolved in the #Jellyfin for #Roku 3.0.9 RC-1!
I know I said it last time, but I'm loving this release methodology!
The items found weren't bugs, but side effects of changes that only occur if you use Jellyfin in a specific way.
I love catching these before we…

New #Bandcamp purchase!
Mushroom Song (Electric Universe Remix) by Killerwatts & Faders
https://bandcamp.com/pmarg

"Over 1,000 items stolen from California museum’s collection in early morning heist"
’Tis the Season? 🥷
#heist #museum #California

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…

Turnover machine Geno Smith becoming historic disaster for last-place Raiders

https://www.cbssports.com/nfl/news/turnover-machine-geno-smith-becoming-hi…

You've got mail!

Fairness in Repeated Matching: A Maximin Perspective
Eugene Lim, Tzeh Yuan Neoh, Nicholas Teh
https://arxiv.org/abs/2510.04624 https://arxiv.org/pdf/2510.0…

Fairness in Repeated Matching: A Maximin Perspective
We study a sequential decision-making model where a set of items is repeatedly matched to the same set of agents over multiple rounds. The objective is to determine a sequence of matchings that either maximizes the utility of the least advantaged agent at the end of all rounds (optimal) or at the end of every individual round (anytime optimal). We investigate the computational challenges associated with finding (anytime) optimal outcomes and demonstrate that these problems are generally computa…

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 403394 nodes and 3387388 edges.
Tags: Economic, Commerce, Unweighted

AgentDR Dynamic Recommendation with Implicit Item-Item Relations via LLM-based Agents
Mingdai Yang, Nurendra Choudhary, Jiangshu Du, Edward W. Huang, Philip S. Yu, Karthik Subbian, Danai Kourta
https://arxiv.org/abs/2510.05598

AgentDR Dynamic Recommendation with Implicit Item-Item Relations via LLM-based Agents
Recent agent-based recommendation frameworks aim to simulate user behaviors by incorporating memory mechanisms and prompting strategies, but they struggle with hallucinating non-existent items and full-catalog ranking. Besides, a largely underexplored opportunity lies in leveraging LLMs'commonsense reasoning to capture user intent through substitute and complement relationships between items, which are usually implicit in datasets and difficult for traditional ID-based recommenders to capture. …

Walmart plans to attach sensors to the 90M grocery pallets it ships each year to its 4,600-store US chain by the end of 2026; tracked items include perishables (Gregory Meyer/Financial Times)
https://www.ft.com/content/3bc2afe8-aaed-4224-a0b9-7a0e2e5dd603

Which reusable grocery bags passed, and failed, Marketplace's durability test?
https://flip.it/GKg9nN

My local supermarket keeps changing how the product offers work...
Buy 4 for 3, cheapest item free
Buy 2 for some random reduced price
Buy 1 for some price that's reduced from whatever it was previously offered at.
Then there's loyalty card prices, which only apply to some items.
Why can't they just offer slightly lower prices across the range so everyone benefits without jumping through hoops?!

I like progressive psytrance, symphonic death metal and avant-garde metal, the kind of noise that reminds me nothing matters and everything still moves in color.
Zoë Straub, Shadow of Intent, Avalon, Tristan, and Mad Tribe stay in the rotation because they actually sound like something real.
My #Bandcamp:

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…

Ranking Items from Discrete Ratings: The Cost of Unknown User Thresholds
Oscar Villemaud, Suryanarayana Sankagiri, Matthias Grossglauser
https://arxiv.org/abs/2510.01871 https:/…

Ranking Items from Discrete Ratings: The Cost of Unknown User Thresholds
Ranking items is a central task in many information retrieval and recommender systems. User input for the ranking task often comes in the form of ratings on a coarse discrete scale. We ask whether it is possible to recover a fine-grained item ranking from such coarse-grained ratings. We model items as having scores and users as having thresholds; a user rates an item positively if the item's score exceeds the user's threshold. Although all users agree on the total item order, estimating that or…

Bin Packing and Covering: Pushing the Frontier on the Maximin Share Fairness
Bo Li, Ankang Sun, Zunyu Wang, Yu Zhou
https://arxiv.org/abs/2510.04425 https://

Bin Packing and Covering: Pushing the Frontier on the Maximin Share Fairness
We study a fundamental fair allocation problem, where the agent's value is determined by the number of bins either used to pack or cover the items allocated to them. Fairness is evaluated using the maximin share (MMS) criterion. This problem is not only motivated by practical applications, but also serves as a natural framework for studying group fairness. As MMS is not always satisfiable, we consider two types of approximations: cardinal and ordinal. For cardinal approximation, we relax the re…

Online Multiple Resource Allocation Problems with Departures via the Primal-Dual Approach
Yusuf Amidu, Khaled Elbassioni, Adriana F. Gabor
https://arxiv.org/abs/2510.04737 https…

Online Multiple Resource Allocation Problems with Departures via the Primal-Dual Approach
In this paper we propose primal-dual algorithms for different variants of the online resource allocation problem with departures. In the basic variant, requests (items) arrive over time to a set of resources (knapsacks) and upon arrival, the duration of time a request may occupy a resource, the demand and reward if the request can be granted, become known. %We assume that the duration of stay of a request may depend on the resource. %and that resources may have different capacity sizes. The goa…

Pricempire: after Valve updated the exchange rate of Counter-Strike digital items, the market fell by $1.75B, or 25%, on October 23; in 2024, a gun sold for $1M (Cecilia D'Anastasio/Bloomberg)
https://www.bloomberg.com/news/articles/20

I am a responsible kitty and can be trusted with your items near the edge of a table.

I’ve just cleared out my #Bandcamp #wishlist. If you’re thinking of #gifting something, the list updated.
You can check it out here:

Knowledge-Augmented Relation Learning for Complementary Recommendation with Large Language Models
Chihiro Yamasaki, Kai Sugahara, Kazushi Okamoto
https://arxiv.org/abs/2509.05564

Knowledge-Augmented Relation Learning for Complementary Recommendation with Large Language Models
Complementary recommendations play a crucial role in e-commerce by enhancing user experience through suggestions of compatible items. Accurate classification of complementary item relationships requires reliable labels, but their creation presents a dilemma. Behavior-based labels are widely used because they can be easily generated from interaction logs; however, they often contain significant noise and lack reliability. While function-based labels (FBLs) provide high-quality definitions of com…

Amazon unveils Amazon Grocery, a new private-label brand that offers 1,000 grocery items largely priced below $5, available online and at Amazon Fresh stores (Robin Ajello/Bloomberg)
https://www.bloomberg.com/news/articles/20

AudioBoost: Increasing Audiobook Retrievability in Spotify Search with Synthetic Query Generation
Enrico Palumbo, Gustavo Penha, Alva Liu, Marcus Eltscheminov, Jefferson Carvalho dos Santos, Alice Wang, Hugues Bouchard, Humberto Jes\'us Corona Pampin, Michelle Tran Luu
https://arxiv.org/abs/2509.06452

AudioBoost: Increasing Audiobook Retrievability in Spotify Search with Synthetic Query Generation
Spotify has recently introduced audiobooks as part of its catalog, complementing its music and podcast offering. Search is often the first entry point for users to access new items, and an important goal for Spotify is to support users in the exploration of the audiobook catalog. More specifically, we would like to enable users without a specific item in mind to broadly search by topic, genre, story tropes, decade, and discover audiobooks, authors and publishers they may like. To do this, we ne…

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

When you’ve spent two years lost in psychedelic soundscapes, vibing through psytrance and twisting realities, that moment you lock onto Progressive psytrance is pure cosmic bliss.
#Psytrance

Empowering Denoising Sequential Recommendation with Large Language Model Embeddings
Tongzhou Wu, Yuhao Wang, Maolin Wang, Chi Zhang, Xiangyu Zhao
https://arxiv.org/abs/2510.04239

Empowering Denoising Sequential Recommendation with Large Language Model Embeddings
Sequential recommendation aims to capture user preferences by modeling sequential patterns in user-item interactions. However, these models are often influenced by noise such as accidental interactions, leading to suboptimal performance. Therefore, to reduce the effect of noise, some works propose explicitly identifying and removing noisy items. However, we find that simply relying on collaborative information may result in an over-denoising problem, especially for cold items. To overcome these…

Fair Division of Indivisible Items
Kevin Hsu
https://arxiv.org/abs/2510.12158 https://arxiv.org/pdf/2510.12158

Fair Division of Indivisible Items
We study the fair division of indivisible items. In the general model, the goal is to allocate $m$ indivisible items to $n$ agents while satisfying fairness criteria such as MMS, EF1, and EFX. We also study a recently-introduced graphical model that represents the fair division problem as a multigraph, in which vertices correspond to agents and edges to items. The graphical model stipulates that an item can have non-zero marginal utility to an agent only if its corresponding edge is incident to…

Modeling shopper interest broadness with entropy-driven dialogue policy in the context of arbitrarily large product catalogs
Firas Jarboui, Issa Memari
https://arxiv.org/abs/2509.06185

Modeling shopper interest broadness with entropy-driven dialogue policy in the context of arbitrarily large product catalogs
Conversational recommender systems promise rich interactions for e-commerce, but balancing exploration (clarifying user needs) and exploitation (making recommendations) remains challenging, especially when deploying large language models (LLMs) with vast product catalogs. We address this challenge by modeling the breadth of user interest via the entropy of retrieval score distributions. Our method uses a neural retriever to fetch relevant items for a user query and computes the entropy of the r…

New #Bandcamp purchase, Ritual Girl by Atmos & Born Sleepy (Iboga Records).
#Psytrance

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 403394 nodes and 3387388 edges.
Tags: Economic, Commerce, Unweighted

eBay agrees to acquire Tise, a social marketplace for secondhand fashion and interior design items that has raised $45M in funding, for an undisclosed sum (Aisha Malik/TechCrunch)
https://techcrunch.com/2025/09/22/ebay-to-acquire-social-marketplace-platfor…

eBay to acquire social marketplace platform Tise | TechCrunch
eBay’s acquisition of Tise indicates that it's looking to modernize its platform to attract younger shoppers, expand its social commerce tools, and build a stronger presence in the sustainable retail market.

LLMs for estimating positional bias in logged interaction data
Aleksandr V. Petrov, Michael Murtagh, Karthik Nagesh
https://arxiv.org/abs/2509.03696 https://

LLMs for estimating positional bias in logged interaction data
Recommender and search systems commonly rely on Learning To Rank models trained on logged user interactions to order items by predicted relevance. However, such interaction data is often subject to position bias, as users are more likely to click on items that appear higher in the ranking, regardless of their actual relevance. As a result, newly trained models may inherit and reinforce the biases of prior ranking models rather than genuinely improving relevance. A standard approach to mitigate …

PayPal CEO Alex Chriss says the company signed a deal with OpenAI to let shoppers use PayPal's digital wallet in ChatGPT to pay for items, starting in 2026 (Hugh Son/CNBC)
https://www.cnbc.com/2025/10/28/paypal-openai-chatgpt-payments-deal.html

PayPal shares surge 14% after OpenAI deal to become the first payments wallet in ChatGPT
The move makes PayPal an early part of OpenAI's efforts to broaden ChatGPT's use for e-commerce.

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 262111 nodes and 1234877 edges.
Tags: Economic, Commerce, Unweighted

MARCO: A Cooperative Knowledge Transfer Framework for Personalized Cross-domain Recommendations
Lili Xie, Yi Zhang, Ruihong Qiu, Jiajun Liu, Sen Wang
https://arxiv.org/abs/2510.04508

MARCO: A Cooperative Knowledge Transfer Framework for Personalized Cross-domain Recommendations
Recommender systems frequently encounter data sparsity issues, particularly when addressing cold-start scenarios involving new users or items. Multi-source cross-domain recommendation (CDR) addresses these challenges by transferring valuable knowledge from multiple source domains to enhance recommendations in a target domain. However, existing reinforcement learning (RL)-based CDR methods typically rely on a single-agent framework, leading to negative transfer issues caused by inconsistent doma…

Items Proxy Bridging: Enabling Frictionless Critiquing in Knowledge Graph Recommendations
Huanyu Zhang, Xiaoxuan Shen, Yu Lei, Baolin Yi, Jianfang Liu, Yinao xie
https://arxiv.org/abs/2509.26107

Items Proxy Bridging: Enabling Frictionless Critiquing in Knowledge Graph Recommendations
Modern recommender systems place great inclination towards facilitating user experience, as more applications enabling users to critique and then refine recommendations immediately. Considering the real-time requirements, critique-able recommender systems typically straight modify the model parameters and update the recommend list through analyzing the user critiquing keyphrases in the inference phase. Current critiquing methods require first constructing a specially designated model which esta…

A Simple but Effective Elaborative Query Reformulation Approach for Natural Language Recommendation
Qianfeng Wen, Yifan Liu, Justin Cui, Joshua Zhang, Anton Korikov, George-Kirollos Saad, Scott Sanner
https://arxiv.org/abs/2510.02656

A Simple but Effective Elaborative Query Reformulation Approach for Natural Language Recommendation
Natural Language (NL) recommender systems aim to retrieve relevant items from free-form user queries and item descriptions. Existing systems often rely on dense retrieval (DR), which struggles to interpret challenging queries that express broad (e.g., "cities for youth friendly activities") or indirect (e.g., "cities for a high school graduation trip") user intents. While query reformulation (QR) has been widely adopted to improve such systems, existing QR methods tend to focus only on expandin…

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…

SMILE: SeMantic Ids Enhanced CoLd Item Representation for Click-through Rate Prediction in E-commerce SEarch
Qihang Zhao, Zhongbo Sun, Xiaoyang Zheng, Xian Guo, Siyuan Wang, Zihan Liang, Mingcan Peng, Ben Chen, Chenyi Lei
https://arxiv.org/abs/2510.12604

SMILE: SeMantic Ids Enhanced CoLd Item Representation for Click-through Rate Prediction in E-commerce SEarch
With the rise of modern search and recommendation platforms, insufficient collaborative information of cold-start items exacerbates the Matthew effect of existing platform items, challenging platform diversity and becoming a longstanding issue. Existing methods align items' side content with collaborative information to transfer collaborative signals from high-popularity items to cold-start items. However, these methods fail to account for the asymmetry between collaboration and content, nor th…