·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Jonathan Kanter is using AI to take on Big Tech1h◆Automattic debuts a platform to deploy vibe coding apps amid a changing internet1h◆Innovating with AI in the special chemicals industry2h◆Your Experts Have Partners. There's HOPE for Keeping Them Together2h◆Is Jensen Huang’s job on the line? Yale’s Jeffrey Sonnenfeld estimates it’s “about a 50-50”10h◆Phantom Consensus: Measuring Social Reasoning in Multi-Agent LLM Decision-Making10h◆ROSE: Risk-Aware Orthogonal Subspace Navigation for Lifelong Knowledge Editing in Multimodal Large Language Models10h◆Measuring and Mitigating the Distributional Gap Between Real and Simulated User Behaviors10h◆Prompt Lottery in LLM-as-a-Judge: Measuring and Mitigating Sensitivity to Syntactic Rephrasing10h◆FindLink: Learning to Assess Scientific Connections from Source-Grounded Premises10h◆FinEvolveKG: Controlled and Attributable Prompt Evolution for Financial Knowledge Graph Construction10h◆Contextuality and Contradictions: Exploring Real-World Identifications of AI-Generated Writing10h◆RL-ATTACK: A Generalized Black-Box Adversarial Attack on Language Models via Reinforcement Learning10h◆Semantic Conditional Similarity (SCS): A Formal Mathematical Framework10h◆Guardrail Erosion in Domain Fine-Tuned Large Language Models: A Paired Audit of Knowledge-Centric Abstention in Biomedical LLMs10h◆From Procedures to Permissions: Learning Precise Subagent Authorization from Agent Skills10h◆On the Incompleteness of do-calculus for Universal Identifiability10h◆Using an LLM to Tackle Difficult Cases in NER for Nepali Tweets10h◆Language, Not Code Abstraction: Natural-language Training Shapes Brain-aligned Geometry10h◆Failure Profiling and Reachable Trajectory Selection for Reasoning Distillation10h◆Jonathan Kanter is using AI to take on Big Tech1h◆Automattic debuts a platform to deploy vibe coding apps amid a changing internet1h◆Innovating with AI in the special chemicals industry2h◆Your Experts Have Partners. There's HOPE for Keeping Them Together2h◆Is Jensen Huang’s job on the line? Yale’s Jeffrey Sonnenfeld estimates it’s “about a 50-50”10h◆Phantom Consensus: Measuring Social Reasoning in Multi-Agent LLM Decision-Making10h◆ROSE: Risk-Aware Orthogonal Subspace Navigation for Lifelong Knowledge Editing in Multimodal Large Language Models10h◆Measuring and Mitigating the Distributional Gap Between Real and Simulated User Behaviors10h◆Prompt Lottery in LLM-as-a-Judge: Measuring and Mitigating Sensitivity to Syntactic Rephrasing10h◆FindLink: Learning to Assess Scientific Connections from Source-Grounded Premises10h◆FinEvolveKG: Controlled and Attributable Prompt Evolution for Financial Knowledge Graph Construction10h◆Contextuality and Contradictions: Exploring Real-World Identifications of AI-Generated Writing10h◆RL-ATTACK: A Generalized Black-Box Adversarial Attack on Language Models via Reinforcement Learning10h◆Semantic Conditional Similarity (SCS): A Formal Mathematical Framework10h◆Guardrail Erosion in Domain Fine-Tuned Large Language Models: A Paired Audit of Knowledge-Centric Abstention in Biomedical LLMs10h◆From Procedures to Permissions: Learning Precise Subagent Authorization from Agent Skills10h◆On the Incompleteness of do-calculus for Universal Identifiability10h◆Using an LLM to Tackle Difficult Cases in NER for Nepali Tweets10h◆Language, Not Code Abstraction: Natural-language Training Shapes Brain-aligned Geometry10h◆Failure Profiling and Reachable Trajectory Selection for Reasoning Distillation10h◆
News/Khmer PFGen-Bench: Building a Judge-Free Benchmark for Open-Ended Generation in a Low-Resource Language
arxiv
PublishedNovember 9, 2026 at 5:00 AM

Khmer PFGen-Bench: Building a Judge-Free Benchmark for Open-Ended Generation in a Low-Resource Language

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

arXiv:2611.09222v1 Announce Type: new Abstract: Benchmarks for open-ended generation often rely on large language model (LLM) judges, whose reliability in low-resource languages is uncertain. We introduce Khmer PFGen-Bench, to our knowledge the first judge-free benchmark for multi-sentence answers t

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 →

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →

Related coverage

More from ARXIV
arxivPhantom Consensus: Measuring Social Reasoning in Multi-Agent LLM Decision-Making10harxivROSE: Risk-Aware Orthogonal Subspace Navigation for Lifelong Knowledge Editing in Multimodal Large Language Models10harxivMeasuring and Mitigating the Distributional Gap Between Real and Simulated User Behaviors10harxivPrompt Lottery in LLM-as-a-Judge: Measuring and Mitigating Sensitivity to Syntactic Rephrasing10h
The Bubble Brief
MON · WED · FRI

Read AI 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