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An AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response33m◆Navalia: Advancing Cowork Agents through Verifiable Task Synthesis and Long-Horizon Post-Training33m◆Large language model and reinforcement learning based autonomous construction and progress updates33m◆Pareto-Optimal RTL Code Generation via Multi-Objective Reinforcement Learning with Large Language Models33m◆MedPAO-Assist: Edge-Deployable, Modality-Aware Agentic AI for Radiology Report Structuring33m◆DataPraxis: Scaling Analytics Tasks via Verified Workspace Evolution33m◆Industrial Agentic AI: LLM-Driven New-Generation Agents for Smart Manufacturing33m◆Fix, Not Just Resample: Bounded Compiler-Guided Repair in Lean 433m◆MAMath-Bench: Process-Aware and Robust Evaluation of Multimodal Multi-Agent Mathematical Reasoning33m◆LightCRS: Lightweight Multi-Domain Conversational Recommendation System33m◆When Planning Problems Become Hard for LLMs: Separating Structural Complexity from Semantic Interpretability33m◆SPEM: Structure-Aware Procedural Memory for Efficient Skill Use in LLM Agents33m◆Does Multi-Agent Collaboration Reduce Hallucination in Clinical Tasks?33m◆Teaching AI Agent to Play Poker Strategically Through Preference Optimization33m◆M-Plan: Comprehensive Planning For LLM Agents with Memory Arrangement33m◆Physical AI: Concepts, Techniques, and Challenges33m◆ReuF2F: Benchmarking Coding Agents on Formalized Undergraduate Research Problems33m◆A general-purpose System One decision model for clinical records33m◆Omni-Woodpecker: Hallucination Correction via Evidence-Prior Rebalancing for Omni LLMs33m◆PROVISO: Provenance-Informed Action Selection for Secure LLM Agents33m◆An AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response33m◆Navalia: Advancing Cowork Agents through Verifiable Task Synthesis and Long-Horizon Post-Training33m◆Large language model and reinforcement learning based autonomous construction and progress updates33m◆Pareto-Optimal RTL Code Generation via Multi-Objective Reinforcement Learning with Large Language Models33m◆MedPAO-Assist: Edge-Deployable, Modality-Aware Agentic AI for Radiology Report Structuring33m◆DataPraxis: Scaling Analytics Tasks via Verified Workspace Evolution33m◆Industrial Agentic AI: LLM-Driven New-Generation Agents for Smart Manufacturing33m◆Fix, Not Just Resample: Bounded Compiler-Guided Repair in Lean 433m◆MAMath-Bench: Process-Aware and Robust Evaluation of Multimodal Multi-Agent Mathematical Reasoning33m◆LightCRS: Lightweight Multi-Domain Conversational Recommendation System33m◆When Planning Problems Become Hard for LLMs: Separating Structural Complexity from Semantic Interpretability33m◆SPEM: Structure-Aware Procedural Memory for Efficient Skill Use in LLM Agents33m◆Does Multi-Agent Collaboration Reduce Hallucination in Clinical Tasks?33m◆Teaching AI Agent to Play Poker Strategically Through Preference Optimization33m◆M-Plan: Comprehensive Planning For LLM Agents with Memory Arrangement33m◆Physical AI: Concepts, Techniques, and Challenges33m◆ReuF2F: Benchmarking Coding Agents on Formalized Undergraduate Research Problems33m◆A general-purpose System One decision model for clinical records33m◆Omni-Woodpecker: Hallucination Correction via Evidence-Prior Rebalancing for Omni LLMs33m◆PROVISO: Provenance-Informed Action Selection for Secure LLM Agents33m◆
News/Google is about to remove free access to Gemini Flash and Pro
theverge
PublishedOctober 6, 2026 at 1:19 PM
—neutral

Google is about to remove free access to Gemini Flash and Pro

Google is about to remove free access to Gemini Flash and Pro
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Starting on October 9th, anyone using Google Gemini on a free plan will be limited to the Flash Lite model. Free users can currently choose from Gemini Flash Lite, Flash, and Pro, but now you'll need a $4.99/month Google AI Plus subscription to access the standard Flash model. However, that subscrip

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