ML applications

Alibaba Qwen Team Releases Qwen3-Embedding and Qwen3-Reranker Series – Redefining Multilingual Embedding and Ranking Standards

ML applications

4 Min Read

Alibaba Qwen Team Releases Qwen3-Embedding and Qwen3-Reranker Series – Redefining Multilingual Embedding and Ranking Standards

By Editorial Team

June 6, 2025

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NVIDIA AI Releases Llama Nemotron Nano VL: A Compact Vision-Language Model Optimized for Document Understanding

ML applications

3 Min Read

NVIDIA AI Releases Llama Nemotron Nano VL: A Compact Vision-Language Model Optimized for Document Understanding

By Editorial Team

June 4, 2025

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Hugging Face Releases SmolVLA: A Compact Vision-Language-Action Model for Affordable and Efficient Robotics

ML applications

4 Min Read

Hugging Face Releases SmolVLA: A Compact Vision-Language-Action Model for Affordable and Efficient Robotics

By Editorial Team

June 4, 2025

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From Exploration Collapse to Predictable Limits: Shanghai AI Lab Proposes Entropy-Based Scaling Laws for Reinforcement Learning in LLMs

ML applications

4 Min Read

From Exploration Collapse to Predictable Limits: Shanghai AI Lab Proposes Entropy-Based Scaling Laws for Reinforcement Learning in LLMs

By Editorial Team

June 3, 2025

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This AI Paper Introduces LLaDA-V: A Purely Diffusion-Based Multimodal Large Language Model for Visual Instruction Tuning and Multimodal Reasoning

ML applications

4 Min Read

This AI Paper Introduces LLaDA-V: A Purely Diffusion-Based Multimodal Large Language Model for Visual Instruction Tuning and Multimodal Reasoning

By Editorial Team

June 3, 2025

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Off-Policy Reinforcement Learning RL with KL Divergence Yields Superior Reasoning in Large Language Models

ML applications

4 Min Read

Off-Policy Reinforcement Learning RL with KL Divergence Yields Superior Reasoning in Large Language Models

By Editorial Team

June 2, 2025

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This AI Paper from Microsoft Introduces WINA: A Training-Free Sparse Activation Framework for Efficient Large Language Model Inference

ML applications

4 Min Read

This AI Paper from Microsoft Introduces WINA: A Training-Free Sparse Activation Framework for Efficient Large Language Model Inference

By Editorial Team

June 1, 2025

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Apple and Duke Researchers Present a Reinforcement Learning Approach That Enables LLMs to Provide Intermediate Answers, Enhancing Speed and Accuracy

ML applications

4 Min Read

Apple and Duke Researchers Present a Reinforcement Learning Approach That Enables LLMs to Provide Intermediate Answers, Enhancing Speed and Accuracy

By Editorial Team

May 30, 2025

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This AI Paper Introduces WEB-SHEPHERD: A Process Reward Model for Web Agents with 40K Dataset and 10× Cost Efficiency

ML applications

4 Min Read

This AI Paper Introduces WEB-SHEPHERD: A Process Reward Model for Web Agents with 40K Dataset and 10× Cost Efficiency

By Editorial Team

May 29, 2025

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LLMs Can Now Reason Beyond Language: Researchers Introduce Soft Thinking to Replace Discrete Tokens with Continuous Concept Embeddings

ML applications

4 Min Read

LLMs Can Now Reason Beyond Language: Researchers Introduce Soft Thinking to Replace Discrete Tokens with Continuous Concept Embeddings

By Editorial Team

May 28, 2025

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ML applications

Alibaba Qwen Team Releases Qwen3-Embedding and Qwen3-Reranker Series – Redefining Multilingual Embedding and Ranking Standards

NVIDIA AI Releases Llama Nemotron Nano VL: A Compact Vision-Language Model Optimized for Document Understanding

Hugging Face Releases SmolVLA: A Compact Vision-Language-Action Model for Affordable and Efficient Robotics

From Exploration Collapse to Predictable Limits: Shanghai AI Lab Proposes Entropy-Based Scaling Laws for Reinforcement Learning in LLMs

This AI Paper Introduces LLaDA-V: A Purely Diffusion-Based Multimodal Large Language Model for Visual Instruction Tuning and Multimodal Reasoning

Off-Policy Reinforcement Learning RL with KL Divergence Yields Superior Reasoning in Large Language Models

This AI Paper from Microsoft Introduces WINA: A Training-Free Sparse Activation Framework for Efficient Large Language Model Inference

Apple and Duke Researchers Present a Reinforcement Learning Approach That Enables LLMs to Provide Intermediate Answers, Enhancing Speed and Accuracy

This AI Paper Introduces WEB-SHEPHERD: A Process Reward Model for Web Agents with 40K Dataset and 10× Cost Efficiency

LLMs Can Now Reason Beyond Language: Researchers Introduce Soft Thinking to Replace Discrete Tokens with Continuous Concept Embeddings

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