·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Fine-tune video and image models at scale with NVIDIA NeMo Automodel and 🤗 Diffusers9m◆Patreon stops asking AI bots not to scrape — and starts blocking them46m◆Why the first GPU financiers are turning to inference chips in a $400 million deal4h◆A scorecard for the AI age6h◆The risk of weather data sabotage is rising7h◆The Steering Budget: Examples beat Knobs12h◆Polestar: Drift-Aware Cache Calibration and Token Commitment for Efficient Inference of Diffusion LLMs12h◆RxBrain: Embodied Cognition Foundation Model with Joint Language-Visual Reasoning and Imagination12h◆When a Verified World Model Still Loses: Play-Adequacy vs Prediction-Accuracy in LLM-Synthesized Code World Models12h◆SAGA: Schema-Aware Grounding for Agentic Text-to-SPARQL Generation12h◆Capability from Access Structure, Not Scale: Lower Bounds and Pre-Registered Tests for Hybrid Sequence Models12h◆ReasFlow: Assisting Reasoning-Centric Scientific Discovery in Applied Mathematics via a Knowledge-Based Multi-Agent System12h◆How Artificial Intelligence LLM Engines Shape the Global Conflict Information Environment12h◆Automatic Hard Example Synthesis with Multi-Level Agentic Data Curation12h◆Tracing LLM Behavior to the Training Data with Empirical Next-Token Distributions12h◆Instrument Effects in Language-Model Honesty Evaluation: An Auditable Single-System Demonstration12h◆Tactile: Giving Computer-Using Agents Hands and Feet12h◆Contextualized Evaluation of Vision Language Models through Dynamic, Multi-turn Interactions12h◆LBA: Textual Hard-Label Adversarial Attack under Low Query Budgets12h◆Eta Given Delta: Defining LLM Tool Efficiency With Marginal Tool Utility12h◆Fine-tune video and image models at scale with NVIDIA NeMo Automodel and 🤗 Diffusers9m◆Patreon stops asking AI bots not to scrape — and starts blocking them46m◆Why the first GPU financiers are turning to inference chips in a $400 million deal4h◆A scorecard for the AI age6h◆The risk of weather data sabotage is rising7h◆The Steering Budget: Examples beat Knobs12h◆Polestar: Drift-Aware Cache Calibration and Token Commitment for Efficient Inference of Diffusion LLMs12h◆RxBrain: Embodied Cognition Foundation Model with Joint Language-Visual Reasoning and Imagination12h◆When a Verified World Model Still Loses: Play-Adequacy vs Prediction-Accuracy in LLM-Synthesized Code World Models12h◆SAGA: Schema-Aware Grounding for Agentic Text-to-SPARQL Generation12h◆Capability from Access Structure, Not Scale: Lower Bounds and Pre-Registered Tests for Hybrid Sequence Models12h◆ReasFlow: Assisting Reasoning-Centric Scientific Discovery in Applied Mathematics via a Knowledge-Based Multi-Agent System12h◆How Artificial Intelligence LLM Engines Shape the Global Conflict Information Environment12h◆Automatic Hard Example Synthesis with Multi-Level Agentic Data Curation12h◆Tracing LLM Behavior to the Training Data with Empirical Next-Token Distributions12h◆Instrument Effects in Language-Model Honesty Evaluation: An Auditable Single-System Demonstration12h◆Tactile: Giving Computer-Using Agents Hands and Feet12h◆Contextualized Evaluation of Vision Language Models through Dynamic, Multi-turn Interactions12h◆LBA: Textual Hard-Label Adversarial Attack under Low Query Budgets12h◆Eta Given Delta: Defining LLM Tool Efficiency With Marginal Tool Utility12h◆
News/Reducing Maintenance Burden in Behaviour-Driven Development: A Paraphrase-Robust Duplicate-Step Detector with a 1.1M-Step Open Benchmark
arxiv
PublishedApril 28, 2026 at 4:00 AM

Reducing Maintenance Burden in Behaviour-Driven Development: A Paraphrase-Robust Duplicate-Step Detector with a 1.1M-Step Open Benchmark

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

arXiv:2604.20462v2 Announce Type: replace-cross Abstract: Context. Behaviour-Driven Development (BDD) suites in Gherkin accumulate step-text duplication with documented maintenance cost. Prior detectors either require runnable tests or are single-organisation, leaving a gap: a static, paraphrase-rob

Stay posted· Newsletter

A 5-min weekly brief — top movers, price watch, story of the week.

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

Discussion
Source
↗
arxiv
Read original ↗All from arxiv →

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →

Related coverage

More from ARXIV
arxivThe Steering Budget: Examples beat Knobs12harxivPolestar: Drift-Aware Cache Calibration and Token Commitment for Efficient Inference of Diffusion LLMs12harxivRxBrain: Embodied Cognition Foundation Model with Joint Language-Visual Reasoning and Imagination12harxivWhen a Verified World Model Still Loses: Play-Adequacy vs Prediction-Accuracy in LLM-Synthesized Code World Models12h
The Bubble Brief
WEEKLY

Read AI insights every Tuesday — top movers, new releases, story of the week.

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

Originally published on arxiv ↗
HomeModelsNews