At a time when the far-right, aided by toxic social media algorithms and billionaire media, are selling hate to billions, the Left has seen a huge resurgence based on a radical hope.
#FarRight #Algorithms #RecommenderSystems #Hate
#FarRight #Algorithms #RecommenderSystems #Hate
November 5, 2025 at 10:57 PM
At a time when the far-right, aided by toxic social media algorithms and billionaire media, are selling hate to billions, the Left has seen a huge resurgence based on a radical hope.
#FarRight #Algorithms #RecommenderSystems #Hate
#FarRight #Algorithms #RecommenderSystems #Hate
I love it when recommender systems are so chronically off that it just confirms the coming automated dystopian future we have built will be 90% Brazil and 10% LOTF.
#recommendersystems #researchgate #academia #academicchatter
#recommendersystems #researchgate #academia #academicchatter
October 30, 2025 at 9:09 AM
I love it when recommender systems are so chronically off that it just confirms the coming automated dystopian future we have built will be 90% Brazil and 10% LOTF.
#recommendersystems #researchgate #academia #academicchatter
#recommendersystems #researchgate #academia #academicchatter
Scalable LinUCB: Low-Rank Design Matrix Updates for Recommenders with
Large Action Spaces
Evgenia Shustova, Evgeny Frolov et al.
Paper
Details
#ScalableLinUCB #RecommenderSystems #LargeActionSpaces
Large Action Spaces
Evgenia Shustova, Evgeny Frolov et al.
Paper
Details
#ScalableLinUCB #RecommenderSystems #LargeActionSpaces
October 23, 2025 at 6:44 PM
Scalable LinUCB: Low-Rank Design Matrix Updates for Recommenders with
Large Action Spaces
Evgenia Shustova, Evgeny Frolov et al.
Paper
Details
#ScalableLinUCB #RecommenderSystems #LargeActionSpaces
Large Action Spaces
Evgenia Shustova, Evgeny Frolov et al.
Paper
Details
#ScalableLinUCB #RecommenderSystems #LargeActionSpaces
📢 We're also now on LinkedIn!
Follow the Glasgow Information Retrieval Group for updates on IR research, @irglasgow.bsky.social activities, events, and collaborations:
🔗 linkedin.com/company/glasgow-information-retrieval-group
#InformationRetrieval #IR #AI #recsys #RecommenderSystems #Glasgow
Follow the Glasgow Information Retrieval Group for updates on IR research, @irglasgow.bsky.social activities, events, and collaborations:
🔗 linkedin.com/company/glasgow-information-retrieval-group
#InformationRetrieval #IR #AI #recsys #RecommenderSystems #Glasgow
Glasgow Information Retrieval Group | LinkedIn
Glasgow Information Retrieval Group | 298 followers on LinkedIn. Founded in 1986, the Glasgow IR Group has been at the forefront of Research & Development in search and recommendation.
linkedin.com
October 16, 2025 at 3:57 PM
📢 We're also now on LinkedIn!
Follow the Glasgow Information Retrieval Group for updates on IR research, @irglasgow.bsky.social activities, events, and collaborations:
🔗 linkedin.com/company/glasgow-information-retrieval-group
#InformationRetrieval #IR #AI #recsys #RecommenderSystems #Glasgow
Follow the Glasgow Information Retrieval Group for updates on IR research, @irglasgow.bsky.social activities, events, and collaborations:
🔗 linkedin.com/company/glasgow-information-retrieval-group
#InformationRetrieval #IR #AI #recsys #RecommenderSystems #Glasgow
In der Schweiz übrigends auch ein Problem, ich wollte nur mal dran erinnern. #recommendersystems #filterbubble
When I wrote the Filter Bubble in 2011, I portrayed an algorithmic tug of war between your impulsive, present-tense self and your more forward-thinking, aspirational self.
Now a big showdown between your long-term and short-term self is here. The question is, which side will your chatbot be on?
Now a big showdown between your long-term and short-term self is here. The question is, which side will your chatbot be on?
The era of hyperpersonalized content is here
Everyone needs to pay attention to the most recent AI products rolled out by OpenAI, Meta, and Google, because they tell us something important about the future of digital media. In the last week… Ope...
www.linkedin.com
October 6, 2025 at 11:08 AM
In der Schweiz übrigends auch ein Problem, ich wollte nur mal dran erinnern. #recommendersystems #filterbubble
A study of 326 participants found large language models can turn matrix-factorization recommendations into clear explanations that boost perceived transparency and trust. Read more: https://getnews.me/llm-explanations-improve-transparency-in-recommender-systems/ #recommendersystems #llm
October 3, 2025 at 10:24 AM
A study of 326 participants found large language models can turn matrix-factorization recommendations into clear explanations that boost perceived transparency and trust. Read more: https://getnews.me/llm-explanations-improve-transparency-in-recommender-systems/ #recommendersystems #llm
SemanticShield uses a two-stage LLM detector that audits item descriptions in real-time. The paper was submitted in September 2025 and the code is on GitHub. https://getnews.me/semanticshield-llm-powered-audits-reveal-shilling-attacks-in-recommender-systems/ #semanticshield #recommendersystems
October 1, 2025 at 1:35 AM
SemanticShield uses a two-stage LLM detector that audits item descriptions in real-time. The paper was submitted in September 2025 and the code is on GitHub. https://getnews.me/semanticshield-llm-powered-audits-reveal-shilling-attacks-in-recommender-systems/ #semanticshield #recommendersystems
RecInter, an agent‑based simulation platform for recommender systems presented at EMNLP 2025, lets user actions instantly update item attributes; code is on GitHub. https://getnews.me/recinter-interaction-centric-agent-simulation-for-dynamic-recommenders/ #recommendersystems #recinter
September 29, 2025 at 9:34 PM
RecInter, an agent‑based simulation platform for recommender systems presented at EMNLP 2025, lets user actions instantly update item attributes; code is on GitHub. https://getnews.me/recinter-interaction-centric-agent-simulation-for-dynamic-recommenders/ #recommendersystems #recinter
ReGeS links retrieval and generation in a reciprocal loop to sharpen intent extraction and lower hallucinations in conversational recommender systems; its code is on GitHub. https://getnews.me/reciprocal-retrieval-generation-boosts-conversational-recommender-systems/ #recommendersystems #reges
September 29, 2025 at 4:40 AM
ReGeS links retrieval and generation in a reciprocal loop to sharpen intent extraction and lower hallucinations in conversational recommender systems; its code is on GitHub. https://getnews.me/reciprocal-retrieval-generation-boosts-conversational-recommender-systems/ #recommendersystems #reges
RSBench, a new benchmark for LLM‑driven evolutionary algorithms, evaluates prompts on accuracy, diversity and fairness, with three algorithms showing distinct Pareto fronts. https://getnews.me/benchmarking-llm-based-evolutionary-algorithms-for-recommender-systems/ #rsbench #recommendersystems #llm
September 27, 2025 at 12:26 AM
RSBench, a new benchmark for LLM‑driven evolutionary algorithms, evaluates prompts on accuracy, diversity and fairness, with three algorithms showing distinct Pareto fronts. https://getnews.me/benchmarking-llm-based-evolutionary-algorithms-for-recommender-systems/ #rsbench #recommendersystems #llm
Including algorithm descriptors raised the meta‑learner’s NDCG@10 to 0.143 (11.7% over the 0.128 baseline) and lifted Top‑1 selection accuracy by 16.1%. Read more: https://getnews.me/intelligent-algorithm-selection-boosts-recommender-system-accuracy/ #recommendersystems #meta‑learning
September 26, 2025 at 8:11 PM
Including algorithm descriptors raised the meta‑learner’s NDCG@10 to 0.143 (11.7% over the 0.128 baseline) and lifted Top‑1 selection accuracy by 16.1%. Read more: https://getnews.me/intelligent-algorithm-selection-boosts-recommender-system-accuracy/ #recommendersystems #meta‑learning
A new study extends Leg‑UP to generate side‑feature‑aware fake profiles, achieving stronger attack performance and low detection rates on benchmark recommender datasets. Read more: https://getnews.me/side-feature-aware-fake-profiles-threaten-recommender-systems/ #recommendersystems #shillingattack
September 25, 2025 at 4:09 AM
A new study extends Leg‑UP to generate side‑feature‑aware fake profiles, achieving stronger attack performance and low detection rates on benchmark recommender datasets. Read more: https://getnews.me/side-feature-aware-fake-profiles-threaten-recommender-systems/ #recommendersystems #shillingattack
New benchmark for recommender‑system unlearning shows a custom algorithm can delete data with latency of only a few seconds. Posted 18 September 2025. Read more: https://getnews.me/benchmark-aligns-recommender-system-unlearning-with-real-world-needs/ #recommendersystems #unlearning
September 20, 2025 at 12:58 PM
New benchmark for recommender‑system unlearning shows a custom algorithm can delete data with latency of only a few seconds. Posted 18 September 2025. Read more: https://getnews.me/benchmark-aligns-recommender-system-unlearning-with-real-world-needs/ #recommendersystems #unlearning
RecXplore, a modular LLM‑feature framework, boosted sequential recommendation performance by up to 18.7% in NDCG@5 and 12.7% in HR@5 on four public benchmarks. Read more: https://getnews.me/key-factors-in-using-llms-for-recommender-feature-extraction/ #recommendersystems #llm #featureextraction
September 20, 2025 at 1:18 AM
RecXplore, a modular LLM‑feature framework, boosted sequential recommendation performance by up to 18.7% in NDCG@5 and 12.7% in HR@5 on four public benchmarks. Read more: https://getnews.me/key-factors-in-using-llms-for-recommender-feature-extraction/ #recommendersystems #llm #featureextraction
Deletion diagnostics measures influence by comparing performance with and without observation. It was applied to Neural Collaborative Filtering on the MovieLens dataset. https://getnews.me/model-agnostic-post-hoc-explainability-improves-recommender-systems/ #recommendersystems #explainability
September 17, 2025 at 5:05 AM
Deletion diagnostics measures influence by comparing performance with and without observation. It was applied to Neural Collaborative Filtering on the MovieLens dataset. https://getnews.me/model-agnostic-post-hoc-explainability-improves-recommender-systems/ #recommendersystems #explainability
Researchers use low‑rank adapters to fine‑tune small language models as user simulators, handling millions of personas with far less compute than large LLMs. Read more: https://getnews.me/low-rank-adapter-fine-tuning-of-small-language-models-for-user-behavior/ #recommendersystems #lowrankadapters
September 16, 2025 at 9:51 PM
Researchers use low‑rank adapters to fine‑tune small language models as user simulators, handling millions of personas with far less compute than large LLMs. Read more: https://getnews.me/low-rank-adapter-fine-tuning-of-small-language-models-for-user-behavior/ #recommendersystems #lowrankadapters
Your next obsession?
AI already picked it. 🎯🤖
Multimodal LMs now predict what you’ll want — and when.
📌 https://glcnd.io/harnessing-multimodal-language-models-for-sequential-recommendations/
#AI #RecommenderSystems #GLCND_IO
AI already picked it. 🎯🤖
Multimodal LMs now predict what you’ll want — and when.
📌 https://glcnd.io/harnessing-multimodal-language-models-for-sequential-recommendations/
#AI #RecommenderSystems #GLCND_IO
August 9, 2025 at 3:25 AM
Your next obsession?
AI already picked it. 🎯🤖
Multimodal LMs now predict what you’ll want — and when.
📌 https://glcnd.io/harnessing-multimodal-language-models-for-sequential-recommendations/
#AI #RecommenderSystems #GLCND_IO
AI already picked it. 🎯🤖
Multimodal LMs now predict what you’ll want — and when.
📌 https://glcnd.io/harnessing-multimodal-language-models-for-sequential-recommendations/
#AI #RecommenderSystems #GLCND_IO
Offline metrics vs. real-world impact for recommender systems? 🤔 Part 3 dives into bridging the gap with A/B testing, business value, & fairness! It's more than just accuracy. Learn how to truly evaluate. 👇 fanyangmeng.blog/recommender-... #RecommenderSystems #MLEvaluation
Recommender System Evaluation (Part 3): Real-World Deployment - When Rubber Meets the Road
Go beyond offline accuracy to truly evaluate your recommender system. This guide covers A/B testing, conversion funnels, fairness, and the business metrics that drive real-world success and retention.
fanyangmeng.blog
June 16, 2025 at 6:00 AM
Offline metrics vs. real-world impact for recommender systems? 🤔 Part 3 dives into bridging the gap with A/B testing, business value, & fairness! It's more than just accuracy. Learn how to truly evaluate. 👇 fanyangmeng.blog/recommender-... #RecommenderSystems #MLEvaluation
Is your recommender system *just* accurate? 🤔 True value lies in UX metrics! Explore diversity, coverage, & serendipity to build systems users truly love. Learn more: 👇
https://fanyangmeng.blog/recommender-system-evaluation-part-2/ #RecommenderSystems #UX
https://fanyangmeng.blog/recommender-system-evaluation-part-2/ #RecommenderSystems #UX
Recommender System Evaluation (Part 2): Beyond Accuracy - The User Experience Dimension
Go beyond accuracy. Learn to evaluate recommender systems with key UX metrics like diversity, novelty, and serendipity to build systems users truly love.
fanyangmeng.blog
June 13, 2025 at 5:18 AM
Is your recommender system *just* accurate? 🤔 True value lies in UX metrics! Explore diversity, coverage, & serendipity to build systems users truly love. Learn more: 👇
https://fanyangmeng.blog/recommender-system-evaluation-part-2/ #RecommenderSystems #UX
https://fanyangmeng.blog/recommender-system-evaluation-part-2/ #RecommenderSystems #UX
Recommender systems: Is your model just "accurate" or truly useful? 🤔 Part 1 explores why MAE/RMSE aren't enough. Discover crucial ranking metrics like NDCG for better user experience! 👇 https://fanyangmeng.blog/recommender-system-evaluation-part-1/ #RecommenderSystems #MachineLearning #DataScience
Recommender System Evaluation (Part 1): The Foundation - Accuracy and Ranking Metrics
Learn essential recommender system evaluation metrics beyond accuracy: NDCG, Precision@K, MAP, and RMSE. Master ranking quality measurement to build recommendation systems users actually love.
fanyangmeng.blog
June 12, 2025 at 5:18 AM
Recommender systems: Is your model just "accurate" or truly useful? 🤔 Part 1 explores why MAE/RMSE aren't enough. Discover crucial ranking metrics like NDCG for better user experience! 👇 https://fanyangmeng.blog/recommender-system-evaluation-part-1/ #RecommenderSystems #MachineLearning #DataScience
New video is out! In this one, we cover anomaly detection on time series, on top of TimescaleDB, and we also play around with recommender systems doing RAG on top of pgai. youtu.be/yW8ruQ9KIcc #postgres #database #timeseries #anomalydetection #AI #RAG #recommendersystems
PostgreSQL Maximalism - Extensions for Every Use Case - Part 3
YouTube video by Data Lab Tech
youtu.be
June 10, 2025 at 6:05 PM
New video is out! In this one, we cover anomaly detection on time series, on top of TimescaleDB, and we also play around with recommender systems doing RAG on top of pgai. youtu.be/yW8ruQ9KIcc #postgres #database #timeseries #anomalydetection #AI #RAG #recommendersystems
8/8
🗓️ I’ll be at the KDD Workshop on Online and Adaptive Recommender Systems (OARS) — happy to chat about this work, online and in person in Toronto!
#GLoSS #KDD2025 #OARS #LLM #RecommenderSystems #SemanticSearch #DenseRetrieval #LoRA #LLaMA3
🗓️ I’ll be at the KDD Workshop on Online and Adaptive Recommender Systems (OARS) — happy to chat about this work, online and in person in Toronto!
#GLoSS #KDD2025 #OARS #LLM #RecommenderSystems #SemanticSearch #DenseRetrieval #LoRA #LLaMA3
June 9, 2025 at 9:18 PM
8/8
🗓️ I’ll be at the KDD Workshop on Online and Adaptive Recommender Systems (OARS) — happy to chat about this work, online and in person in Toronto!
#GLoSS #KDD2025 #OARS #LLM #RecommenderSystems #SemanticSearch #DenseRetrieval #LoRA #LLaMA3
🗓️ I’ll be at the KDD Workshop on Online and Adaptive Recommender Systems (OARS) — happy to chat about this work, online and in person in Toronto!
#GLoSS #KDD2025 #OARS #LLM #RecommenderSystems #SemanticSearch #DenseRetrieval #LoRA #LLaMA3
2/8
GLoSS is a generative recommendation framework that integrates LLMs with semantic search (aka dense retrieval) for sequential recommendation.
#LLM #RecommenderSystems #DenseRetrieval
GLoSS is a generative recommendation framework that integrates LLMs with semantic search (aka dense retrieval) for sequential recommendation.
#LLM #RecommenderSystems #DenseRetrieval
June 9, 2025 at 9:18 PM
2/8
GLoSS is a generative recommendation framework that integrates LLMs with semantic search (aka dense retrieval) for sequential recommendation.
#LLM #RecommenderSystems #DenseRetrieval
GLoSS is a generative recommendation framework that integrates LLMs with semantic search (aka dense retrieval) for sequential recommendation.
#LLM #RecommenderSystems #DenseRetrieval
🚀 Never miss a beat in science again!
📬 Scholar Inbox is your personal assistant for staying up to date with your literature. It includes: visual summaries, collections, search and a conference planner.
Check out our white paper: arxiv.org/abs/2504.08385
#OpenScience #AI #RecommenderSystems
📬 Scholar Inbox is your personal assistant for staying up to date with your literature. It includes: visual summaries, collections, search and a conference planner.
Check out our white paper: arxiv.org/abs/2504.08385
#OpenScience #AI #RecommenderSystems
April 14, 2025 at 11:04 AM
🚀 Never miss a beat in science again!
📬 Scholar Inbox is your personal assistant for staying up to date with your literature. It includes: visual summaries, collections, search and a conference planner.
Check out our white paper: arxiv.org/abs/2504.08385
#OpenScience #AI #RecommenderSystems
📬 Scholar Inbox is your personal assistant for staying up to date with your literature. It includes: visual summaries, collections, search and a conference planner.
Check out our white paper: arxiv.org/abs/2504.08385
#OpenScience #AI #RecommenderSystems