{
  "id": 14089,
  "url": "https://arxiv.org/abs/2607.25091",
  "title": "Towards Robust Reinforcement Learning for Small-Scale Language Model Agents",
  "summary": "The alignment of Small Language Models (SLMs) in the 70--500M parameter range using reinforcement learning is often considered unstable, though the underlying failure mechanisms have not been systematically investigated. In the State-of-the-Art (SOTA) research, fifteen (model, corpus) configurations were trained using Proximal Policy Optimization (PPO). The experiments included Pythia-70M, 160M, 410M and SmolLM2-135M, 360M on the TinyStories, CNN/DailyMail, and Wikitext-103 corpora. Three reprod",
  "authors": "Md Rezwanul Haque, Md. Milon Islam, Fakhri Karray",
  "category": "research",
  "topics": "regulation,safety-alignment,agents-autonomy,finance-investment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-26T20:00:00.000Z",
  "fetched_at": "2026-07-29T05:10:12.205Z",
  "source_slug": "hf-daily",
  "source_name": "HuggingFace Daily Papers",
  "source_homepage": "https://huggingface.co/papers",
  "ethics_ai_record_url": "https://ethics.ai/record/14089",
  "original_url": "https://arxiv.org/abs/2607.25091",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}