🔥 COLLEAGUE.SKILL: Automated AI Skill Generation via Expert Knowledge Distillation

💡 The paper introduces COLLEAGUE SKILL, a system for automatically generating person-grounded AI skills from heterogeneous traces of expert knowledge. The problem addressed is that current methods for creating AI agents that mimic human expertise and judgment are limited, as they rely on fragmented evidence and lack a comprehensive workflow for distilling this knowledge into usable skills.

The method presented involves an automated trace-to-skill distillation process that takes materials from a target person or role and produces a versioned skill package with two tracks: a capability track for practices, mental models, and decision heuristics, and a bounded behavior track for communication style, interaction rules, and correction history. This package can be inspected, updated through natural-language feedback, and deployed across agent hosts.

The results of the system are significant, with the open-source repository having approximately 18.5k GitHub stars, 215 skills from 165 contributors, and over 100k cumulative stars across listed skill cards. The system demonstrates how person-grounded skills can be represented as portable, correctable packages, rather than opaque prompts or hidden memories, and provides a comprehensive workflow for generating and deploying these skills. The paper presents the artifact contract, generation workflow, correction lifecycle, deployment surface, and domain presets implemented in the system, showcasing its potential for creating more human-like AI agents.

📅 Published on May 29

🔗 Links:
• GitHub: https://github.com/huggingface
• arXiv: https://arxiv.org/abs/2605.31264
• PDF: https://arxiv.org/pdf/2605.31264

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📢 By: https://xn--r1a.website/PaperNexus

#ArtificialIntelligence #ExpertKnowledgeDistillation #AI_skill_generation #HumanCenteredAI #KnowledgeGraphEmbedding

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Shock: A Chinese laboratory has put half of the paid video generation industry in an awkward position. 😲

You upload a photo and an audio recording — and you get a talking avatar with lip synchronization, which can maintain quality for several minutes. And all this with open source code. 🤖

What used to require a camera and editing now increasingly resembles a GitHub repository. 💻
It's called LongCat-Avatar. 🐱

GitHub - https://github.com/meituan-longcat/LongCat-Video
Weights - https://huggingface.co/meituan-longcat/LongCat-Video-Avatar-1.5

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🔥 Can We Defend Against AI-Generated Video Attacks on Real-World Crisis Events? A Systematic Evaluation of Detectors, Generators and Social Dissemination

💡 A new benchmark for AI-generated video detection reveals that current detectors fail to generalize across realistic crisis-related videos and become less reliable as content spreads socially. Generate...

📅 Published on Aug 14

🔗 Links:
• GitHub: https://github.com/huggingface
• arXiv: https://arxiv.org/abs/2608.14391
• PDF: https://arxiv.org/pdf/2608.14391
• Project Page: https://ra-bench-crisis-video.yxgma811120.chatgpt.site/

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📢 By: https://xn--r1a.website/PaperNexus

#AI #MachineLearning #DataScience #Research #HuggingFace

🔥 Latent On-Policy Self-Distillation

💡 Latent On-Policy Self-Distillation learns privileged teaching context end-to-end from experience to provide dense token-level supervision, improving agent performance and efficiency. Generated by thin...

📅 Published on Aug 13

🔗 Links:
• GitHub: https://github.com/huggingface
• arXiv: https://arxiv.org/abs/2608.13040
• PDF: https://arxiv.org/pdf/2608.13040

🤖 Models citing this paper:
• https://huggingface.co/liunanfu1992/Qwen3-8B-LOPD
• https://huggingface.co/liunanfu1992/OLMo-3-7B-Think-LOPD

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📢 By: https://xn--r1a.website/PaperNexus

#AI #MachineLearning #DataScience #Research #HuggingFace

🔥 LLM-as-a-Verifier: A General-Purpose Verification Framework

💡 LLM-as-a-Verifier introduces a probabilistic verification framework that scales across multiple dimensions to improve solution correctness assessment and agent performance across various benchmarks. G...

📅 Published on Jul 6

🔗 Links:
• GitHub: https://github.com/huggingface
• arXiv: https://arxiv.org/abs/2607.05391
• PDF: https://arxiv.org/pdf/2607.05391
• Project Page: https://llm-as-a-verifier.com/

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📢 By: https://xn--r1a.website/PaperNexus

#AI #MachineLearning #DataScience #Research #HuggingFace

🔥 VibeWorlding: Can Multimodal Agents Construct 3D Open Worlds End-to-End?

💡 A unified framework benchmarks and trains multimodal agents that infer intent, plan 3D scenes, invoke tools, and reflect on feedback, revealing that reinforcement learning improves open-source models ...

📅 Published on Aug 15

🔗 Links:
• GitHub: https://github.com/huggingface
• arXiv: https://arxiv.org/abs/2608.15265
• PDF: https://arxiv.org/pdf/2608.15265
• Project Page: https://huggingface.co/collections/usail-hkust/vibeworlder

🤖 Models citing this paper:
• https://huggingface.co/usail-hkust/VibeWorlder-8B
• https://huggingface.co/usail-hkust/VibeWorlder-30B-A3B
• https://huggingface.co/usail-hkust/VibeWorlder-Embedding-4B

📊 Datasets citing this paper:
• https://huggingface.co/datasets/usail-hkust/VWE-Bench

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📢 By: https://xn--r1a.website/PaperNexus

#AI #MachineLearning #DataScience #Research #HuggingFace

🔥 HarnessEval-W: Agentifying the Evaluation of Visual Worlds

💡 HarnessEval-W uses hierarchical sub-agents to decompose world-model evaluations into verifiable reasoning chains that justify scores with transparent evidence. Generated by thinkingmachines/Inkling-Sm...

📅 Published on Aug 17

🔗 Links:
• GitHub: https://github.com/huggingface
• arXiv: https://arxiv.org/abs/2608.16859
• PDF: https://arxiv.org/pdf/2608.16859
• Project Page: https://mirros-lab.github.io/HarnessEval-W

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📢 By: https://xn--r1a.website/PaperNexus

#AI #MachineLearning #DataScience #Research #HuggingFace