·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Cursor makes its biggest India push yet ahead of SpaceX acquisition with localized pricing4h◆Reverso: Efficient Time Series Foundation Models for Zero-shot Forecasting5h◆Multinex: Lightweight Low-light Image Enhancement via Multi-prior Retinex5h◆Market Design for AI: Beyond the Copyright Binary5h◆Who Pays the Price? Stakeholder-Centric Prompt Injection Benchmarking for Real-world Web Agents5h◆TextRich: A Multi-Domain Benchmark for Detecting AI-Generated Text-Rich Images from GPT-Image-25h◆DiscoLoop: Looping Discrete Embeddings and Continuous Hidden States for Multi-hop Reasoning5h◆From World Models to World Action Models: A Concise Tutorial for Robotics5h◆QuantFlow: A Federated Mamba-Based Post-Transformer Foundation Model for Time-Series Forecasting5h◆Multi-Turn On-Policy Distillation with Prefix Replay5h◆Operational Proto-Introspection in Looped Language Models: Process-Quality Taps, Executable Branching, and the Readout-Control Boundary5h◆Skillware: A Software Ontology and Engineering Lifecycle for Persistent Behavioral Artifacts5h◆MedDDC-Eval: Diagnosis-Decoupled Evaluation of Multi-Turn Medical Consultation Agents5h◆PhantomFill: When the Form Demands an Answer, Language Models Invent One5h◆Error Certificates for KV-Cache Eviction via Randomized Design5h◆Explaining GAND: A Resource on Gender-Ambiguous Natural Data & Contrastive Attribution5h◆MioFFAn: an Annotation Software for Formula Formalization with LLM Automation Capabilities5h◆LA-RL: Label-Aware Self-Reflection for Reinforcement Learning in Information Extraction5h◆Mwando: Leveraging AI to Preserve and Teach shiKomori5h◆The JEPA Paradox in Language: The Geometry of Linguistic Alternatives5h◆Cursor makes its biggest India push yet ahead of SpaceX acquisition with localized pricing4h◆Reverso: Efficient Time Series Foundation Models for Zero-shot Forecasting5h◆Multinex: Lightweight Low-light Image Enhancement via Multi-prior Retinex5h◆Market Design for AI: Beyond the Copyright Binary5h◆Who Pays the Price? Stakeholder-Centric Prompt Injection Benchmarking for Real-world Web Agents5h◆TextRich: A Multi-Domain Benchmark for Detecting AI-Generated Text-Rich Images from GPT-Image-25h◆DiscoLoop: Looping Discrete Embeddings and Continuous Hidden States for Multi-hop Reasoning5h◆From World Models to World Action Models: A Concise Tutorial for Robotics5h◆QuantFlow: A Federated Mamba-Based Post-Transformer Foundation Model for Time-Series Forecasting5h◆Multi-Turn On-Policy Distillation with Prefix Replay5h◆Operational Proto-Introspection in Looped Language Models: Process-Quality Taps, Executable Branching, and the Readout-Control Boundary5h◆Skillware: A Software Ontology and Engineering Lifecycle for Persistent Behavioral Artifacts5h◆MedDDC-Eval: Diagnosis-Decoupled Evaluation of Multi-Turn Medical Consultation Agents5h◆PhantomFill: When the Form Demands an Answer, Language Models Invent One5h◆Error Certificates for KV-Cache Eviction via Randomized Design5h◆Explaining GAND: A Resource on Gender-Ambiguous Natural Data & Contrastive Attribution5h◆MioFFAn: an Annotation Software for Formula Formalization with LLM Automation Capabilities5h◆LA-RL: Label-Aware Self-Reflection for Reinforcement Learning in Information Extraction5h◆Mwando: Leveraging AI to Preserve and Teach shiKomori5h◆The JEPA Paradox in Language: The Geometry of Linguistic Alternatives5h◆
Tag

#knowledge-graph

3 articles tagged #knowledge-graph

arxiv5d agobullish

Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning

arXiv:2607.19845v1 Announce Type: cross Abstract: This paper introduces Sentence Splitter, a self-supervised framework built upon a T5-based encoder--decoder architecture for uncovering the latent factual structure of natural language sentences. The proposed method identifies the semantic boundary b

T51 model#nlp#self-supervised#knowledge-graphRead on arxiv →
HomeModelsNews
arxivJun 6bullish

Executable Schema Contracts: From Automatic Ingestion to Multi-Source Retrieval

arXiv:2606.05415v1 Announce Type: cross Abstract: Real-world data spans tables, documents, and semi-structured files with implicit semantics. Querying this data requires integrating evidence across inconsistent schemas and formats, yet existing approaches either demand costly manual engineering or b

LL1 model#querying#knowledge-graph#schema-discoveryRead on arxiv →
arxivApr 24bullish

GS-Quant: Granular Semantic and Generative Structural Quantization for Knowledge Graph Completion

arXiv:2604.21649v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown immense potential in Knowledge Graph Completion (KGC), yet bridging the modality gap between continuous graph embeddings and discrete LLM tokens remains a critical challenge. While recent quantization-based appro

#knowledge-graph#natural-language-processing#quantizationRead on arxiv →