{
  "id": "2504.20835",
  "title": "Enhancing Non-Core Language Instruction-Following in Speech LLMs via Semi-Implicit Cross-Lingual CoT Reasoning",
  "first_public": "2025-04-29",
  "paper_url": "https://arxiv.org/abs/2504.20835",
  "authors": "Hongfei Xue, Yufeng Tang, Hexin Liu, Jun Zhang, Xuelong Geng, Lei Xie",
  "arxiv": "2504.20835",
  "added_at": "2026-11-09",
  "venue": "arXiv",
  "provenance": "Primary-source literature review, 2026-11-09",
  "html_url": "https://arxiv.org/html/2504.20835v1",
  "lens": [
    "internalized"
  ],
  "representation": [
    "text-latent-hybrid",
    "hidden-state"
  ],
  "computation": [
    "token-wise",
    "depth-wise"
  ],
  "training": [
    "supervised",
    "curriculum"
  ],
  "questions": [
    "capability",
    "efficiency"
  ],
  "evidence": [
    "empirical"
  ],
  "modality": [
    "language",
    "multimodal"
  ],
  "summary": "Trains speech language models to transcribe a question, translate it into English, form an English response, and answer in the original language. Progressively shortens the intermediate text while retaining sentence openings, reducing the amount of reasoning text generated.",
  "author_names": [
    "Hongfei Xue",
    "Yufeng Tang",
    "Hexin Liu",
    "Jun Zhang",
    "Xuelong Geng",
    "Lei Xie"
  ],
  "record_url": "https://latent-implicit-thinking.github.io/papers/2504.20835/",
  "legacy_record_url": "https://latent-implicit-thinking.github.io/papers/#paper-2504-20835",
  "citation_date": "2025-04-29",
  "json_url": "https://latent-implicit-thinking.github.io/papers/2504.20835/record.json",
  "markdown_url": "https://latent-implicit-thinking.github.io/papers/2504.20835/index.md",
  "bibtex_url": "https://latent-implicit-thinking.github.io/papers/2504.20835/citation.bib",
  "csl_url": "https://latent-implicit-thinking.github.io/papers/2504.20835/citation.csl.json",
  "pdf_url": "https://arxiv.org/pdf/2504.20835"
}