A Comprehensive Survey on Long Context Language Modeling (2025 · 64 citations)
Language models that can read very long inputs, such as whole books, extended dialogues or large codebases, are now common.
SKIntern: Internalizing Symbolic Knowledge for Distilling Better CoT Capabilities into Small Language Models (2025 · 12 citations)
Small language models (SLMs) are cheaper and more private than LLMs, but they reason less well. Earlier CoT distillation methods such as KARD and CasCoD add retrieved documents or multi-step generation to help them. That extra input makes inference slower and can bring in irrelevant or misleading content. SKIntern…
Shuttle Between Symbolic Instructions and Neural Parameters of Large Language Models (2026)
Prompts and fine-tuned weights are usually treated as separate tools for steering an LLM. The authors argue that both are compact encodings of the same task data, so each should be predictable from the other. Their framework, SHIP, learns this translation in both directions. It has three parts:

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Updated 1 November 2026