… AI-generated summary The Model Context Protocol MCP has unified the interface between Large Language Models LLMs and external tools, yet a fundamental gap remains in how agents conceptualize the environments within which they operate. …
… The following papers were recommended by the Semantic Scholar API PRAISE: Prefix-Based Rollout Reuse in Agentic Search Training 2026 Train at Moving Edge: Online-Verified Prompt Selection for Efficient RL Training of Large Reasoning Model 2026 Accelerating RL Post-Training Rollouts via System-Integ… …
… AI-generated summary Recent advances in large language models have led to strong performance on reasoning and environment-interaction tasks, yet their ability for creative problem-solving remains underexplored. …
… On Pokemon Red and Emerald across frontier models , Continual Harness starting from scratch substantially reduces button-press cost relative to the minimalist baseline and recovers a majority of the gap to a hand-engineered expert harness, with capability-dependent gains, despite starting from the … …
… We study a 21-day deployment of 3,505 user-funded agents trading real ETH onchain. The system logged 7.5M agent invocations, ~300K onchain actions, ~$20M in volume, 70B inference tokens, and 99.9% settlement success for policy-valid transactions. …
… We present a systematic empirical study of HeavySkill across diverse domains. …
… AI-generated summary Long-context large language models LLMs -for example, Gemini-3.1-Pro and Qwen-3.5-are widely used to empower many real-world applications, such as retrieval-augmented generation, autonomous agents, and AI assistants. …
… Skill documentation is not available at the provided link - https://github.com/huggingface/skills/blob/main/hf-llm-trainer/SKILL.md · Ah, we moved a couple of bits around in the repo -- link for that is here: https://github.com/huggingface/skills/blob/main/hf-llm-trainer/skills/model-trainer/SKILL.… …
… Seeing Open Deep Research as an open-source, transparent alternative alongside a guide that helps with realistic cost estimation gives a really balanced view: you show how to build powerful AI tools and how to plan for their usage sustainably."