arXiv:2608. 16620v1 Announce Type: cross Abstract: Palmyra x6 is a large language model optimized for use with enterprise-oriented agentic tasks.
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arXiv:2602. 12670v4 Announce Type: replace Abstract: Agent Skills are structured packages of procedural knowledge that augment large language model (LLM) agents at inference time.
arXiv:2608. 20314v1 Announce Type: new Abstract: Mid-training is increasingly recognized as a critical stage for shaping the capabilities of large language models.
MOSCOPT is a parameter‑free algorithm that jointly optimizes a pool of N skills and a gating skill G, which dynamically selects K skills at each step for LLM agents. It introduces EditAdam, a dual‑state optimizer, and a three‑phase interleaved update scheme that monotonically improves performance without gradient or parameter tuning. Experiments on five benchmarks and three target LLMs show MOSCOPT consistently outperforms baselines, highlighting the importance of mixture‑of‑skills architecture and collective evolution.
arXiv:2609.40303v1 Announce Type: new Abstract: Recent autonomous machine learning engineering (MLE) agents have made significant progress on public leaderboards. Often motivated by progress stagnati...
arXiv:2606. 01993v1 Announce Type: cross Abstract: Abundant procedural knowledge on the Web holds great potential for helping agents solve long-horizon tasks.
arXiv:2606. 17819v1 Announce Type: cross Abstract: Agent skills -- structured, reusable knowledge artifacts that augment LLM agent capabilities -- have been rapidly adopted in industry, yet their cross-domain impact and use across commercial and open-source models remain under-studied, and no reusable methodology exists for evaluating an individual skill.