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China vetoes Meta’s $2B Manus deal after months-long probe1h◆OpenAI could be making a phone with AI agents replacing apps1h◆Rebuilding the data stack for AI1h◆Join the new AI Agents Vibe Coding Course from Google and Kaggle1h◆The AI-designed car is taking shape3h◆Meta inks deal for solar power at night, beamed from space4h◆The next phase of the Microsoft OpenAI partnership8h◆From Local to Cluster: A Unified Framework for Causal Discovery with Latent Variables10h◆Consequentialist Objectives and Catastrophe10h◆EgoMAGIC- An Egocentric Video Field Medicine Dataset for Training Perception Algorithms10h◆A general optimization solver based on OP-to-MaxSAT reduction10h◆ReCast: Recasting Learning Signals for Reinforcement Learning in Generative Recommendation10h◆A Probabilistic Framework for Hierarchical Goal Recognition10h◆CNSL-bench: Benchmarking the Sign Language Understanding Capabilities of MLLMs on Chinese National Sign Language10h◆The Shape of Adversarial Influence: Characterizing LLM Latent Spaces with Persistent Homology10h◆Toward Principled LLM Safety Testing: Solving the Jailbreak Oracle Problem10h◆Learning from Natural Language Feedback for Personalized Question Answering10h◆TS-Arena -- A Live Forecast Pre-Registration Platform10h◆Report for NSF Workshop on AI for Electronic Design Automation10h◆Initial results of the Digital Consciousness Model10h◆China vetoes Meta’s $2B Manus deal after months-long probe1h◆OpenAI could be making a phone with AI agents replacing apps1h◆Rebuilding the data stack for AI1h◆Join the new AI Agents Vibe Coding Course from Google and Kaggle1h◆The AI-designed car is taking shape3h◆Meta inks deal for solar power at night, beamed from space4h◆The next phase of the Microsoft OpenAI partnership8h◆From Local to Cluster: A Unified Framework for Causal Discovery with Latent Variables10h◆Consequentialist Objectives and Catastrophe10h◆EgoMAGIC- An Egocentric Video Field Medicine Dataset for Training Perception Algorithms10h◆A general optimization solver based on OP-to-MaxSAT reduction10h◆ReCast: Recasting Learning Signals for Reinforcement Learning in Generative Recommendation10h◆A Probabilistic Framework for Hierarchical Goal Recognition10h◆CNSL-bench: Benchmarking the Sign Language Understanding Capabilities of MLLMs on Chinese National Sign Language10h◆The Shape of Adversarial Influence: Characterizing LLM Latent Spaces with Persistent Homology10h◆Toward Principled LLM Safety Testing: Solving the Jailbreak Oracle Problem10h◆Learning from Natural Language Feedback for Personalized Question Answering10h◆TS-Arena -- A Live Forecast Pre-Registration Platform10h◆Report for NSF Workshop on AI for Electronic Design Automation10h◆Initial results of the Digital Consciousness Model10h◆

News/model/Qwen2.5-7B-Instruct

Qwen2.5-7B-Instruct news

1 articles mentioning Qwen2.5-7B-Instruct

arxivApr 14

Tuning Qwen2.5-VL to Improve Its Web Interaction Skills

arXiv:2604.09571v1 Announce Type: cross Abstract: Recent advances in vision-language models (VLMs) have sparked growing interest in using them to automate web tasks, yet their feasibility as independent agents that reason and act purely from visual input remains underexplored. We investigate this se

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