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Bringing Value Models Back: Generative Critics for Value Modeling in LLM Reinforcement Learning6h◆Subagents vs Agent Skills: Executing Reusable Knowledge for Long-Horizon Agentic Tasks6h◆Distribution-Consistent Inference for Dynamic Sparse Mixture-of-Experts6h◆In RAG We Trust? Measuring Robustness of Retrieval-Augmented Generation Under Document Poisoning6h◆FrontierChallenge: Evaluating Scientific Workflow Completion6h◆IBIB: A Protocol for Measuring Enterprise AI Systems by Serving Route, Not Model Identifier6h◆AgenticGen: Reward-Guided Agentic Video Generation for Advertising6h◆Strangers to Themselves: What Language Models Say About Themselves Is Generic6h◆Omni Interaction Agent Technical Report6h◆CoGReV: A Confidence-Gated Post-Hoc Non-Monotonic Belief Revision Framework for Phishing Website Classification6h◆Bit-Flip Attacks on Vision-Language-Action Models: Action-Decoding Architecture Shapes the Vulnerability6h◆Can Foundation Models Moderate Online Content? Evaluating Instruction- vs. Example-Driven Policy Operationalization6h◆RiLM: Parameter-Efficient Language Modeling via Geodesic Decoding6h◆Tracing Computation Density in LLMs6h◆Cultural Binding Heads in Language Models6h◆Direct Diversity Optimization for Diverse Successful Trajectories in Preference Post-Training6h◆Left-Branching Transformers Excel at Right-Branching Languages: Data Shapes Word Order Preferences in Language Models6h◆Palmyra x6 Technical Report: An Agentic, Tool-Use Model Post-Trained via Anchored Supervised Fine-Tuning6h◆'Ghaib in Translation' aka Unseen Harm: Measuring Cross-Script Safety Inconsistency with 'Missed-in-Urdu' Scores in LLM Hate Speech Detection6h◆DexterSQL: Deep Schema Exploration and Rule-based Correction for Text-to-SQL Generation6h◆Bringing Value Models Back: Generative Critics for Value Modeling in LLM Reinforcement Learning6h◆Subagents vs Agent Skills: Executing Reusable Knowledge for Long-Horizon Agentic Tasks6h◆Distribution-Consistent Inference for Dynamic Sparse Mixture-of-Experts6h◆In RAG We Trust? Measuring Robustness of Retrieval-Augmented Generation Under Document Poisoning6h◆FrontierChallenge: Evaluating Scientific Workflow Completion6h◆IBIB: A Protocol for Measuring Enterprise AI Systems by Serving Route, Not Model Identifier6h◆AgenticGen: Reward-Guided Agentic Video Generation for Advertising6h◆Strangers to Themselves: What Language Models Say About Themselves Is Generic6h◆Omni Interaction Agent Technical Report6h◆CoGReV: A Confidence-Gated Post-Hoc Non-Monotonic Belief Revision Framework for Phishing Website Classification6h◆Bit-Flip Attacks on Vision-Language-Action Models: Action-Decoding Architecture Shapes the Vulnerability6h◆Can Foundation Models Moderate Online Content? Evaluating Instruction- vs. Example-Driven Policy Operationalization6h◆RiLM: Parameter-Efficient Language Modeling via Geodesic Decoding6h◆Tracing Computation Density in LLMs6h◆Cultural Binding Heads in Language Models6h◆Direct Diversity Optimization for Diverse Successful Trajectories in Preference Post-Training6h◆Left-Branching Transformers Excel at Right-Branching Languages: Data Shapes Word Order Preferences in Language Models6h◆Palmyra x6 Technical Report: An Agentic, Tool-Use Model Post-Trained via Anchored Supervised Fine-Tuning6h◆'Ghaib in Translation' aka Unseen Harm: Measuring Cross-Script Safety Inconsistency with 'Missed-in-Urdu' Scores in LLM Hate Speech Detection6h◆DexterSQL: Deep Schema Exploration and Rule-based Correction for Text-to-SQL Generation6h◆
News/Now everyone can put data to work
openai
PublishedSeptember 10, 2026 at 3:00 PM

Now everyone can put data to work

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