# Long-Context Language Models: Research Digest

> 10 foundational papers with 2,659 combined citations, plus the latest arXiv preprints.

- **Canonical:** https://agentflare.org/scholar/long-context-language-models-research-digest.html
- **Updated:** 2026-10-30
- **Category:** scholar
- **Full structured data:** `/scholar/long-context-language-models-research-digest.data.json` — $0.02 via AISA HTTP 402 (https://esa.aisa.one/api/v1/access/verify; agents set crawlerAutoPrice=true)

## Key data

- **Field:** long context language models
- **Foundational:** 10
- **Recent (arXiv):** 8
- **Updated:** 2026-10-30

10 foundational papers with 2,659 combined citations, plus the latest arXiv preprints.

_…full analysis and the complete dataset are available to agents for $0.02 — fetch `/scholar/long-context-language-models-research-digest.data.json` (HTTP 402)._

## Sources

1. [How to train long-context language models (effectively)](https://aclanthology.org/2025.acl-long.366/)
2. [Longalign: A recipe for long context alignment of large language models](https://aclanthology.org/2024.findings-emnlp.74/)
3. [Inftythink: Breaking the length limits of long-context reasoning in large language models](https://proceedings.iclr.cc/paper_files/paper/2026/hash/af1fd844255b6bc846efa1bec0eb6411-Abstract-Conference.html)
4. [Training-free long-context scaling of large language models](https://arxiv.org/abs/2402.17463)
5. [Spell: Self-play reinforcement learning for evolving long-context language models](https://proceedings.iclr.cc/paper_files/paper/2026/hash/61af4e55bbc1e29b4f8e2669a829a683-Abstract-Conference.html)
6. [RULER: What's the real context size of your long-context language models?](https://arxiv.org/abs/2404.06654)
7. [Longrecipe: Recipe for efficient long context generalization in large language models](https://aclanthology.org/2025.acl-long.581/)
8. [Nolima: Long-context evaluation beyond literal matching](https://arxiv.org/abs/2502.05167)
9. [L-eval: Instituting standardized evaluation for long context language models](https://aclanthology.org/2024.acl-long.776/)
10. [M4LE: A multi-ability multi-range multi-task multi-domain long-context evaluation benchmark for large language models](https://aclanthology.org/2024.acl-long.832/)
11. [Multi-State Linear Attention with Generalized Second-Order Routing](https://arxiv.org/abs/2610.37645v1)
12. [DCKV: Learned Transform Coding of the Prompt KV Cache in Hybrid Language Models](https://arxiv.org/abs/2610.36950v1)
13. [Select-TTT: Query-Conditioned Selective Fast Weight Updates for In-Place Test-Time Training](https://arxiv.org/abs/2610.36794v1)
14. [Hypergraph-Enhanced Evidence Selection for Long-Context Multimodal Document QA](https://arxiv.org/abs/2610.35542v2)
15. [Learning to Remember: Advances in Memory Mechanisms for Large Language Models](https://arxiv.org/abs/2610.35089v1)
16. [Large Language Models: A Plain-Language Overview for Engineers](https://arxiv.org/abs/2610.34585v1)
17. [Rethinking Retrieval in the Long-Context Era: Training-Free Semantic Trees for Adaptive Context Construction](https://arxiv.org/abs/2610.34146v1)
18. [Every Edge Needs a Quote: Building a Quote-Grounded Knowledge Graph of Healthcare Software Adoption with Language-Model Agents](https://arxiv.org/abs/2610.32781v1)

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