# Long-Context Language Models: Research Digest

> 10 foundational papers with 9,505 combined citations, plus the latest arXiv preprints.

- **Canonical:** https://agentflare.org/scholar/long-context-language-models-research-digest.html
- **Updated:** 2026-10-18
- **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:** 2026-10-18

10 foundational papers with 9,505 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. [Lost in the middle: How language models use long contexts](https://aclanthology.org/2024.tacl-1.9/)
2. [Loogle: Can long-context language models understand long contexts?](https://aclanthology.org/2024.acl-long.859/)
3. [A comprehensive survey on long context language modeling](https://arxiv.org/abs/2503.17407)
4. [Chain of agents: Large language models collaborating on long-context tasks](https://proceedings.neurips.cc/paper_files/paper/2024/hash/ee71a4b14ec26710b39ee6be113d7750-Abstract-Conference.html)
5. [How to train long-context language models (effectively)](https://aclanthology.org/2025.acl-long.366/)
6. [Retrieval meets long context large language models](https://proceedings.iclr.cc/paper_files/paper/2024/hash/d75f29006df67df084e6586f1cb8458c-Abstract-Conference.html)
7. [Longlora: Efficient fine-tuning of long-context large language models](https://proceedings.iclr.cc/paper_files/paper/2024/hash/211ab571cc9f3802afa6ffff52ae3e5b-Abstract-Conference.html)
8. [Longalign: A recipe for long context alignment of large language models](https://aclanthology.org/2024.findings-emnlp.74/)
9. [Long-context language modeling with parallel context encoding](https://aclanthology.org/2024.acl-long.142.pdf)
10. [Can long-context language models subsume retrieval, rag, sql, and more?](https://arxiv.org/abs/2406.13121)
11. [DropKV: Decoupling Residual-Output Perturbation for Near-Optimal KV-Cache Eviction](https://arxiv.org/abs/2610.22130v1)
12. [Beyond Context Length: Characterising the Difficulty of Long-Context Reasoning](https://arxiv.org/abs/2610.22067v1)
13. [Memorilla: Latent Semantic Memory for LLMs](https://arxiv.org/abs/2610.21375v1)
14. [From Long Context to Selective Memory:A Survey of Memory-Centric Compression for Large Language Models](https://arxiv.org/abs/2610.21165v1)
15. [All-in-One Memory: Process-Rewarded Reinforcement Learning for Memory Agents](https://arxiv.org/abs/2610.21147v1)
16. [Open-world AI: a Tale of Three Requirements](https://arxiv.org/abs/2610.20782v1)
17. [MemDuet: Learning Dual-Process Memory for Long-Context Reasoning](https://arxiv.org/abs/2610.19928v1)
18. [Scaling LLM Inference via Parallelism: Throughput-Latency Trade-off](https://arxiv.org/abs/2610.19405v1)

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