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Category: AI Shorts

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This AI Paper Investigates Test-Time Scaling of English-Centric RLMs for Enhanced Multilingual Reasoning and Domain Generalization
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This AI Paper Investigates Test-Time Scaling of English-Centric RLMs for Enhanced Multilingual Reasoning and Domain Generalization

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Reasoning language models, or RLMs, are increasingly used to simulate step-by-step problem-solving by generating long, structured reasoning chains. These models […]

Rethinking Toxic Data in LLM Pretraining: A Co-Design Approach for Improved Steerability and Detoxification
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Rethinking Toxic Data in LLM Pretraining: A Co-Design Approach for Improved Steerability and Detoxification

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In the pretraining of LLMs, the quality of training data is crucial in determining model performance. A common strategy involves […]

Reinforcement Learning, Not Fine-Tuning: Nemotron-Tool-N1 Trains LLMs to Use Tools with Minimal Supervision and Maximum Generalization
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Reinforcement Learning, Not Fine-Tuning: Nemotron-Tool-N1 Trains LLMs to Use Tools with Minimal Supervision and Maximum Generalization

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Equipping LLMs with external tools or functions has become popular, showing great performance across diverse domains. Existing research depends on […]

RL^V: Unifying Reasoning and Verification in Language Models through Value-Free Reinforcement Learning
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RL^V: Unifying Reasoning and Verification in Language Models through Value-Free Reinforcement Learning

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LLMs have gained outstanding reasoning capabilities through reinforcement learning (RL) on correctness rewards. Modern RL algorithms for LLMs, including GRPO, […]

OpenAI Releases HealthBench: An Open-Source Benchmark for Measuring the Performance and Safety of Large Language Models in Healthcare
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OpenAI Releases HealthBench: An Open-Source Benchmark for Measuring the Performance and Safety of Large Language Models in Healthcare

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OpenAI has released HealthBench, an open-source evaluation framework designed to measure the performance and safety of large language models (LLMs) […]

Multimodal AI Needs More Than Modality Support: Researchers Propose General-Level and General-Bench to Evaluate True Synergy in Generalist Models
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Multimodal AI Needs More Than Modality Support: Researchers Propose General-Level and General-Bench to Evaluate True Synergy in Generalist Models

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Artificial intelligence has grown beyond language-focused systems, evolving into models capable of processing multiple input types, such as text, images, […]

Offline Video-LLMs Can Now Understand Real-Time Streams: Apple Researchers Introduce StreamBridge to Enable Multi-Turn and Proactive Video Understanding
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Offline Video-LLMs Can Now Understand Real-Time Streams: Apple Researchers Introduce StreamBridge to Enable Multi-Turn and Proactive Video Understanding

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Video-LLMs process whole pre-recorded videos at once. However, applications like robotics and autonomous driving need causal perception and interpretation of […]

PrimeIntellect Releases INTELLECT-2: A 32B Reasoning Model Trained via Distributed Asynchronous Reinforcement Learning
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PrimeIntellect Releases INTELLECT-2: A 32B Reasoning Model Trained via Distributed Asynchronous Reinforcement Learning

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As language models scale in parameter count and reasoning complexity, traditional centralized training pipelines face increasing constraints. High-performance model training […]

AG-UI (Agent-User Interaction Protocol): An Open, Lightweight, Event-based Protocol that Standardizes How AI Agents Connect to Front-End Applications
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AG-UI (Agent-User Interaction Protocol): An Open, Lightweight, Event-based Protocol that Standardizes How AI Agents Connect to Front-End Applications

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The current generation of AI agents has made significant progress in automating backend tasks such as summarization, data migration, and […]

This AI Paper Introduces Effective State-Size (ESS): A Metric to Quantify Memory Utilization in Sequence Models for Performance Optimization
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This AI Paper Introduces Effective State-Size (ESS): A Metric to Quantify Memory Utilization in Sequence Models for Performance Optimization

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In machine learning, sequence models are designed to process data with temporal structure, such as language, time series, or signals. […]

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