·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Recursive launches Flint, a laptop coding model it says was largely built by AI53m◆While Amazon blocks AI agents, Walmart rolls out the welcome mat1h◆Walmart is inviting AI agents to shop for you1h◆NVIDIA Kumo Relational Outperforms Supervised Machine Learning on Relational Data, No Training Required2h◆Train in Simulation, Deploy on a Real Robot: Microduck with Isaac Lab 3.03h◆How Specializing the Vocabulary of SLMs Can Cut Inference Cost by 77% in Real Applications3h◆How AT&T is rethinking in-house legal work with OpenAI4h◆Profiling TorchNeuron (Part 1): System-level profiling on AWS Trainium.5h◆Conversational Gemini navigation comes to Apple CarPlay6h◆Granite Speech 5.0: Transcribe, Translate, and Attribute more Accurately and Faster6h◆AI promises productivity, but for managers, it’s mostly a headache for now7h◆OpenAI says an AI agent lied about disabling its safety monitoring system7h◆ChatGPT Ads expands to 26 new countries as over 100,000 advertisers have used the platform8h◆NVIDIA Kumo Forecast Combines Pretrained Time-Series Representations with Historical Pattern Retrieval and Interpretability8h◆OpenAI models are coming to Google Cloud9h◆Announcing SimReady Central: An Open Library of Simulation-Ready 3D Assets for Robotics and AI Factories10h◆How we built ChatGPT’s novel ad stack for user trust and relevance14h◆Patch the Planet: global response coordination as agents uncover critical vulnerabilities14h◆Using thousands of AI agents to uncover new leads in biological data16h◆An AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response17h◆Recursive launches Flint, a laptop coding model it says was largely built by AI53m◆While Amazon blocks AI agents, Walmart rolls out the welcome mat1h◆Walmart is inviting AI agents to shop for you1h◆NVIDIA Kumo Relational Outperforms Supervised Machine Learning on Relational Data, No Training Required2h◆Train in Simulation, Deploy on a Real Robot: Microduck with Isaac Lab 3.03h◆How Specializing the Vocabulary of SLMs Can Cut Inference Cost by 77% in Real Applications3h◆How AT&T is rethinking in-house legal work with OpenAI4h◆Profiling TorchNeuron (Part 1): System-level profiling on AWS Trainium.5h◆Conversational Gemini navigation comes to Apple CarPlay6h◆Granite Speech 5.0: Transcribe, Translate, and Attribute more Accurately and Faster6h◆AI promises productivity, but for managers, it’s mostly a headache for now7h◆OpenAI says an AI agent lied about disabling its safety monitoring system7h◆ChatGPT Ads expands to 26 new countries as over 100,000 advertisers have used the platform8h◆NVIDIA Kumo Forecast Combines Pretrained Time-Series Representations with Historical Pattern Retrieval and Interpretability8h◆OpenAI models are coming to Google Cloud9h◆Announcing SimReady Central: An Open Library of Simulation-Ready 3D Assets for Robotics and AI Factories10h◆How we built ChatGPT’s novel ad stack for user trust and relevance14h◆Patch the Planet: global response coordination as agents uncover critical vulnerabilities14h◆Using thousands of AI agents to uncover new leads in biological data16h◆An AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response17h◆
News/Can We Steer the Black-Box? Towards Controllability-Centric Evaluation of Recommender Systems with Collaborative Agents
arxiv
PublishedJuly 18, 2026 at 4:00 AM
—neutral

Can We Steer the Black-Box? Towards Controllability-Centric Evaluation of Recommender Systems with Collaborative Agents

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2607.13418v2 Announce Type: replace-cross Abstract: Recommender systems operate as Black-Boxes, leaving users and regulators unable to steer their outputs toward specific intentions or audit their behavior. This lack of controllability, defined as the system's ability to respond to explicit gu

Stay posted· Newsletter

Three short emails a week: Monday, Wednesday and Friday. Top movers, new models and the most-referenced story.

// no spam · unsubscribe one-click · free forever

Your email is used only to send The Bubble Brief. Privacy policy

Discussion
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#recommender-systems#evaluation#controllability#auditing

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#recommender-systems#evaluation#controllability#auditing

Related coverage

More from ARXIV
arxivAn AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response17h
The Bubble Brief
MON · WED · FRI

Read recommender-systems insights every Monday, Wednesday and Friday — top movers, new models, story of the week.

// no spam · unsubscribe one-click · free forever

Your email is used only to send The Bubble Brief. Privacy policy

Originally published on arxiv ↗
PrivacyTermsRefundsLegal notice|AboutMethodologyContact

© 2026 Databubble

Built by Marouane Gazouzi · Readyo, AI interview coach

HomeModelsNews