人工智能2023 · 分享于 Hacker News

Lost in the Middle: How Language Models Use Long Contexts (2023)

探索《Lost in the Middle: How Language Models Use Long Contexts (2023)》的原文与 Hacker News 社区讨论,查看来源并加入阅读清单。

阅读原文

看看社区如何讨论这个想法。

来自 Hacker News 的原始讨论。不同的视角、疑问,以及值得继续思考的线索。

最多展示 100 条相关讨论。论文可能出现在评论中,并非原帖投稿内容。

在讨论中发现的引用

按 HN 条目顺序展示最近的 50 条引用来源。

Ytosh ·

Codestral Mamba

485 赞同138 评论
Yaraghuvanshi ·

LLMs and the Harry Potter problem

65 赞同61 评论
Ygzer0 ·

GPT-4 Update: 32K Context Window Now for All Users

53 赞同26 评论
YspIrr ·

Handbook.md shows that long policy documents do not reliably govern agents

45 赞同19 评论
Yxinweihe ·

Show HN: TraceRoot – Open-source agentic debugging for distributed services

40 赞同22 评论
Ygk1 ·

You probably don’t need to fine-tune LLMs

16 赞同0 评论
Ydavidbarker ·

Introducing ChatGPT Enterprise

10 赞同5 评论
Ywilliamzeng0 ·

Launch HN: Sweep (YC S23) – A bot to create simple PRs in your codebase

9 赞同1 评论
Yja3k ·

Benchmarking GPT-4 Turbo – A Cautionary Tale

9 赞同0 评论
Yshishirpatil ·

MemGPT – LLMs with self-editing memory for unbounded context

6 赞同0 评论
Ybobvanluijt ·

Explainer Video – Lost in the Middle: How Language Models Use Long Context

4 赞同3 评论
Yaverylamp ·

Llama 32K Context Released by Together AI

3 赞同0 评论
Ykevin_hu ·

New models and developer products announced at OpenAI DevDay

3 赞同0 评论
Yrobertnishihara ·

A Comprehensive Guide for Building Rag-Based LLM Applications

2 赞同0 评论
YHeidaradar ·

Microsoft says GPT 3.5 has 20B parameters?

2 赞同0 评论
Ystuhlmueller ·

Build a search engine, not a vector DB

2 赞同0 评论
Ywslh ·

Lost in the Middle: How Language Models Use Long Contexts (2023)

2 赞同0 评论
Ygk1 ·

Lost in the Middle: How Language Models Use Long Contexts

1 赞同0 评论
Yjojodoi ·

Language models use long contexts

1 赞同0 评论
Yandrewon ·

What's new in Llama 2 and how to run it locally

1 赞同0 评论
YAmazingTurtle ·

OpenAI reduces Codex Model Context Size from 372k to 272k

1 赞同0 评论

一个想法,引向另一个。

发现更多论文