PolyCite / 基于多智能体协同、多源汇聚的论文引用元数据检索工具

需求分析

在学术写作过程中，参考文献质量直接影响论文可信度、审稿结果和学术诚信。当前痛点主要包括：

幻觉引用风险严重

使用大模型、搜索引擎或人工记忆整理参考文献时，可能出现不存在的论文、错误标题、错误作者、错误 DOI、错误年份等“幻觉引用”。这类问题可能导致：
- 审稿人无法检索到引用来源；
- 论文被质疑可靠性；
- 轻则返修、拒稿，重则涉及学术道德问题。
单一数据源不可靠

DBLP、Crossref、OpenAlex、arXiv、Semantic Scholar、DOI 内容协商等数据源各有优势和缺陷。例如：
- DBLP 在计算机领域质量较高，但覆盖面有限；
- Crossref DOI 信息权威，但有时字段不完整；
- arXiv 适合预印本，但不一定对应最终发表版本；
- Semantic Scholar 覆盖广，但可能存在限流或元数据差异。
因此需要多数据源交叉验证、优先级排序和冲突处理。
手工整理 BibTeX 成本高

高质量学术论文通常引用几十甚至上百篇文献。人工逐条搜索、复制 BibTeX、修正格式非常耗时，并且容易出现：
- BibTeX 类型不一致；
- citation key 风格混乱；
- 作者名格式不统一；
- 会议/期刊名称不统一；
- DOI、URL、arXiv ID 缺失或错误；
- 重复条目难以发现。

工具介绍

search-bibtex 是一个独立的论文 PDF 到 BibTeX 命令行工具。它从本地论文 PDF 中提取 DOI、arXiv ID、标题、作者和年份，查询 DBLP、arXiv、Crossref、OpenAlex、DOI 内容协商、Semantic Scholar 以及可选的自定义 HTTP JSON 来源，然后按配置的来源优先级和字段权重排序候选结果。用户可以在终端中交互选择 BibTeX，也可以用 --select-index 做非交互选择。

项目以多平台二进制分发，不走 npm 发布。运行时代码不依赖 Paperlib，也不接入 Grok search；Grok search 只可作为开发期资料检索辅助工具。

功能

从论文 PDF 前若干页提取可搜索元数据。
支持 PDF、论文标题字符串、stdin 标题输入和现有 .bib 文件更新。
检索内置书目信息源：DBLP、arXiv、Crossref、OpenAlex、DOI、Semantic Scholar。
支持声明式 config.toml，可配置来源顺序、排序权重、结果数量、并行搜索和自定义 HTTP JSON 来源。
交互选择器支持 Vim 风格键位和过滤；脚本场景可直接选择 0-based index。
更新 .bib 文件时保留原 citation key，只替换条目内容。
网络失败、解析失败、无候选和无效配置会显式报错或写入 sourceErrors。
多数据源交叉验证。
支持批量处理。

安装

下载二进制

二进制按平台和架构放在 dist-bin/：

dist-bin/<platform-arch>/search-bibtex
dist-bin/<platform-arch>/search-bibtex.exe

把对应平台目录加入 PATH，或直接用绝对路径运行。运行二进制不需要本机安装 Node.js。

从源码构建

pnpm install
pnpm build
pnpm build:binary

也可以使用 Makefile：

make install
make build
make binary
make build-binaries

make binary 生成当前平台二进制，make build-binaries 生成全部平台目标。

快速开始

查看帮助和默认配置：

search-bibtex --help
search-bibtex config-defaults
search-bibtex config-template

从 PDF 提取元数据：

search-bibtex metadata paper.pdf

搜索 PDF 并在 TTY 中选择候选；重定向或管道环境会输出 JSON：

search-bibtex search paper.pdf \
  --source-priority dblp,arxiv,crossref,openalex,doi \
  --limit 5 \
  --timeout 30

直接输出第 0 个候选的 BibTeX：

search-bibtex select paper.pdf --select-index 0 --format bibtex

从标题字符串搜索，多个标题默认用英文分号分隔：

search-bibtex search-title "Self-Instruct: Aligning Language Models with Self-Generated Instructions; DFlash: Block Diffusion for Flash Speculative Decoding"
printf 'Self-Instruct: Aligning Language Models with Self-Generated Instructions; DFlash: Block Diffusion for Flash Speculative Decoding' | search-bibtex search-title

更新现有 BibTeX 文件并保留引用名：

search-bibtex update references.bib --in-place
search-bibtex update references.bib --output updated.bib

配置

默认配置文件路径是 ~/.config/search-bibtex/config.toml。缺省路径文件不存在时会直接使用内置默认值；显式传入 --config <path> 且文件不存在时会报错。命令行参数优先于配置文件。

最小配置：

[search]
limit = 10
timeout_seconds = 30
parallel = true
source_priority = ["dblp", "arxiv", "crossref", "openalex", "doi", "semantic-scholar"]

[search.weights]
title = 0.45
author = 0.20
year = 0.10
identifier = 0.20
source = 0.05

完整配置说明见中文配置文档和 English configuration docs。

CLI 命令

Command	用途
`config-defaults`	输出默认搜索和排序配置 JSON。
`config-template`	输出可修改的 TOML 配置样板。
`metadata <pdf>`	从 PDF 提取元数据和查询候选。
`search <pdf>`	搜索并排序候选；TTY 中进入交互选择器，非 TTY 输出 JSON。
`select <pdf>`	搜索后交互选择，或用 `--select-index` 输出指定候选。
`search-title [titles...]`	从标题字符串或 stdin 搜索候选。
`update <bibtex>`	刷新现有 `.bib` 文件条目并保留 citation key。

交互选择器键位：

j / Down     向下移动
k / Up       向上移动
g            跳到第一项
G            跳到最后一项
/            进入过滤模式
Enter        确认过滤或选择当前候选
Esc          退出过滤或取消选择
q            取消选择
Ctrl-C       取消选择

典型使用场景

场景 A：论文作者整理参考文献

用户已经有若干 PDF，希望快速生成 BibTeX。

流程：

输入论文 PDF；
工具提取标题、作者、年份、DOI；
查询多个数据源；
返回候选 BibTeX；
用户选择最可信条目；
输出 BibTeX。

价值：

减少手动搜索；
降低复制错误；
优先获取权威 BibTeX。

场景 B：校验 AI 生成的参考文献

用户有一批 LLM 生成的参考文献标题，担心存在幻觉引用。

流程：

用户输入标题列表；
工具逐条检索；
能找到可靠来源的条目生成 BibTeX；
找不到的条目标记为高风险；
用户人工复核高风险项。

价值：

发现不存在或错误引用；
避免将幻觉引用写入论文；
降低学术诚信风险。

场景 C：刷新已有 BibTeX 文件

用户已有 .bib 文件，但条目格式混乱或字段缺失。

流程：

输入 references.bib；
工具解析每个条目标题；
检索多个来源；
替换条目内容；
保留原 citation key；
输出更新后的 .bib。

价值：

统一引用元数据；
保留正文中的引用键；
降低大规模手动修正成本。

场景 D：团队或 CI 检查引用质量

团队希望在提交论文前检查 .bib 文件是否包含可疑条目。

流程：

CI 运行工具；
对 .bib 中每个条目检索验证；
对找不到可靠来源的条目给出错误或警告；
阻止明显可疑引用进入最终版本。

价值：

提前发现问题；
建立论文引用质量门禁；
适合团队协作。

测试 / 例子

配置bibtex源

> ./search-bibtex config-defaults
{
  "sourcePriority": [
    "dblp",
    "arxiv",
    "crossref",
    "openalex",
    "doi",
    "semantic-scholar"
  ],
  "weights": {
    "title": 0.45,
    "author": 0.2,
    "year": 0.1,
    "identifier": 0.2,
    "source": 0.05
  },
  "limit": 10
}

指定单个论文标题进行搜索。

> ./search-bibtex search-title "Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling"
search-title: searching 6 source channels...
search-title: 1/6 source channels completed [doi]
search-title: 2/6 source channels completed [doi] failed [semantic-scholar]
search-title: 3/6 source channels completed [doi] failed [arxiv, semantic-scholar]
search-title: 4/6 source channels completed [crossref, doi] failed [arxiv, semantic-scholar]
search-title: 5/6 source channels completed [crossref, openalex, doi] failed [arxiv, semantic-scholar]
search-title: 6/6 source channels completed [crossref, openalex, doi] failed [dblp, arxiv, semantic-scholar]
search-bibtex candidate selection
Source issues:
  dblp 500 HTTP 500 from https://dblp.org/search/publ/ap..., arxiv 429 HTTP 429 from
  https://export.arxiv.org/api/qu..., semantic-scholar 429 HTTP 429 from
  https://api.semanticscholar.org...
Filter: 
Keys: j/k move, g/G jump, / filter, Ctrl+O preview, Enter select, q cancel

> [0] crossref         0.480 Tackling System and Statistical Heterogeneity for Federated Learning wi...
  [1] openalex         0.470 Tackling System and Statistical Heterogeneity for Federated Learning wi...
  [2] openalex         0.470 Tackling System and Statistical Heterogeneity for Federated Learning wi...
  [3] crossref         0.210 FedCSGA: Evolutionary client selection with joint statistical and syste...
  [4] crossref         0.207 FedDiverse: Tackling Data Heterogeneity in Federated Learning with Dive...
  [5] crossref         0.202 Adaptive Heterogeneous Client Sampling for Federated Learning Over Wire...
  [6] openalex         0.192 Adaptive Heterogeneous Client Sampling for Federated Learning Over Wire...
  [7] crossref         0.182 Tackling Privacy Heterogeneity in Federated Learning
  [8] crossref         0.180 FedClust: Tackling Data Heterogeneity in Federated Learning through Wei...
  [9] crossref         0.178 RingSFL: An Adaptive Split Federated Learning Towards Taming Client Het...

Title: Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling
Authors: Bing Luo and Wenli Xiao and Shiqiang Wang and ... (+2 more)
Year: 2022  Venue: IEEE INFOCOM 2022 - IEEE Conference on Computer Communications
IDs: DOI 10.1109/infocom48880.2022.9796935

BibTeX preview: compact
@inproceedings{Luo_2022, title={Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling}, url={http://dx.doi.org/10.1109/infocom48880.2022.9796935}, DOI={10.1109/infocom48880.2022.9796935}, booktitle={IEEE INFOCOM 2022 - IEEE Conference on Computer Communications}, publisher={IEEE}, author={Luo, Bing and Xiao, Wenli and Wang, Shiqiang and Huang, Jianwei and Tassiulas, Leandros}, year={2022}, month=May, pages={1739–1748} }
  title = {Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Cl...}
  author = {Bing Luo and Wenli Xiao and Shiqiang Wang and Jianwei Huang and ... (+1 more)}
  year = {2022}
  booktitle = {IEEE INFOCOM 2022 - IEEE Conference on Computer Communications}
  doi = {10.1109/infocom48880.2022.9796935}
  url = {https://doi.org/10.1109/infocom48880.2022.9796935}
}
search-bibtex selection confirmed
Title: Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling
Source: crossref  Score: 0.480
Clipboard: clipboard unavailable

@inproceedings{Luo_2022,
  title = {Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling},
  url = {http://dx.doi.org/10.1109/infocom48880.2022.9796935},
  doi = {10.1109/infocom48880.2022.9796935},
  booktitle = {IEEE INFOCOM 2022 - IEEE Conference on Computer Communications},
  publisher = {IEEE},
  author = {Luo, Bing and Xiao, Wenli and Wang, Shiqiang and Huang, Jianwei and Tassiulas, Leandros},
  year = {2022},
  month = May,
  pages = {1739–1748},
}

指定多个论文标题进行搜索。

> ./search-bibtex search-title "Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling" "Dp-forward: Fine-tuning and inference on language models with differential privacy in forward pass"
search-title[1]: searching 6 source channels...
search-title[1]: 1/6 source channels completed [doi]
search-title[1]: 2/6 source channels completed [doi] failed [dblp]
search-title[1]: 3/6 source channels completed [doi] failed [dblp, arxiv]
search-title[1]: 4/6 source channels completed [doi] failed [dblp, arxiv, crossref]
search-title[1]: 5/6 source channels completed [doi] failed [dblp, arxiv, crossref, semantic-scholar]
search-title[1]: 6/6 source channels completed [openalex, doi] failed [dblp, arxiv, crossref, semantic-scholar]
search-bibtex candidate selection
Source issues:
  dblp fetch failed, arxiv fetch failed, crossref fetch failed, semantic-scholar 429 HTTP
  429 from https://api.semanticscholar.org...
Filter: 
Keys: j/k move, g/G jump, / filter, Ctrl+O preview, Enter select, q cancel

> [0] openalex         0.470 Tackling System and Statistical Heterogeneity for Federated Learning wi...
  [1] openalex         0.470 Tackling System and Statistical Heterogeneity for Federated Learning wi...
  [2] openalex         0.192 Adaptive Heterogeneous Client Sampling for Federated Learning Over Wire...
  [3] openalex         0.133 FedPARL: Client Activity and Resource-Oriented Lightweight Federated Le...
  [4] openalex         0.123 Advances and Open Problems in Federated Learning
  [5] openalex         0.103 Federated Learning: A Survey on Enabling Technologies, Protocols, and A...
  [6] openalex         0.102 Towards Personalized Federated Learning
  [7] openalex         0.093 FedProto: Federated Prototype Learning across Heterogeneous Clients
  [8] openalex         0.093 Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and...
  [9] openalex         0.072 Pushing AI to wireless network edge: an overview on integrated sensing,...

Title: Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling
Authors: Bing Luo and Wenli Xiao and Shiqiang Wang and ... (+2 more)
Year: 2022  Venue: IEEE INFOCOM 2022 - IEEE Conference on Computer Communications
IDs: DOI https://doi.org/10.1109/infocom48880.2022.9796935

BibTeX preview: compact
@inproceedings{Luo_2022, title={Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling}, url={http://dx.doi.org/10.1109/infocom48880.2022.9796935}, DOI={10.1109/infocom48880.2022.9796935}, booktitle={IEEE INFOCOM 2022 - IEEE Conference on Computer Communications}, publisher={IEEE}, author={Luo, Bing and Xiao, Wenli and Wang, Shiqiang and Huang, Jianwei and Tassiulas, Leandros}, year={2022}, month=May, pages={1739–1748} }
  title = {Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Cl...}
  author = {Bing Luo and Wenli Xiao and Shiqiang Wang and Jianwei Huang and ... (+1 more)}
  year = {2022}
  booktitle = {IEEE INFOCOM 2022 - IEEE Conference on Computer Communications}
  doi = {https://doi.org/10.1109/infocom48880.2022.9796935}
  url = {https://openalex.org/W4226183928}
}
search-bibtex selection confirmed
Title: Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling
Source: openalex  Score: 0.470
Clipboard: clipboard unavailable

@inproceedings{Luo_2022,
  title = {Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling},
  url = {http://dx.doi.org/10.1109/infocom48880.2022.9796935},
  doi = {10.1109/infocom48880.2022.9796935},
  booktitle = {IEEE INFOCOM 2022 - IEEE Conference on Computer Communications},
  publisher = {IEEE},
  author = {Luo, Bing and Xiao, Wenli and Wang, Shiqiang and Huang, Jianwei and Tassiulas, Leandros},
  year = {2022},
  month = May,
  pages = {1739–1748},
}search-title[2]: searching 6 source channels...
search-title[2]: 1/6 source channels completed [doi]
search-title[2]: 2/6 source channels completed [doi] failed [arxiv]
search-title[2]: 3/6 source channels completed [doi] failed [arxiv, semantic-scholar]
search-title[2]: 4/6 source channels completed [doi] failed [dblp, arxiv, semantic-scholar]
search-title[2]: 5/6 source channels completed [crossref, doi] failed [dblp, arxiv, semantic-scholar]
search-title[2]: 6/6 source channels completed [crossref, openalex, doi] failed [dblp, arxiv, semantic-scholar]
search-bibtex candidate selection
Source issues:
  dblp 500 HTTP 500 from https://dblp.org/search/publ/ap..., arxiv 429 HTTP 429 from
  https://export.arxiv.org/api/qu..., semantic-scholar 429 HTTP 429 from
  https://api.semanticscholar.org...
Filter: 
Keys: j/k move, g/G jump, / filter, Ctrl+O preview, Enter select, q cancel

> [0] crossref         0.480 DP-Forward: Fine-tuning and Inference on Language Models with Different...
  [1] openalex         0.470 DP-Forward: Fine-tuning and Inference on Language Models with Different...
  [2] crossref         0.211 Fine-Tuning Language Models with Just Forward Passes
  [3] crossref         0.210 Fine-Tuning Language Models with Differential Privacy through Adaptive ...
  [4] crossref         0.207 Towards Fine-tuning Pre-trained Language Models with Integer Forward an...
  [5] crossref         0.197 EW-Tune: A Framework for Privately Fine-Tuning Large Language Models wi...
  [6] crossref         0.175 DP-FedLoRA: Privacy-Enhanced Federated Fine-Tuning for On-Device Large ...
  [7] crossref         0.158 Privacy-Aware Federated Fine-Tuning of Large Pretrained Models With Jus...
  [8] crossref         0.150 Is Differential Privacy-Enhanced Parameter-Efficient Fine-Tuning Effect...
  [9] crossref         0.145 Extractive Fact Decomposition for Interpretable Natural Language Infere...

Title: DP-Forward: Fine-tuning and Inference on Language Models with Differential Privacy in Forward Pass
Authors: Minxin Du and Xiang Yue and Sherman S. M. Chow and ... (+3 more)
Year: 2023  Venue: Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security
IDs: DOI 10.1145/3576915.3616592

BibTeX preview: compact
@inproceedings{Du_2023, series={CCS ’23}, title={DP-Forward: Fine-tuning and Inference on Language Models with Differential Privacy in Forward Pass}, url={http://dx.doi.org/10.1145/3576915.3616592}, DOI={10.1145/3576915.3616592}, booktitle={Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security}, publisher={ACM}, author={Du, Minxin and Yue, Xiang and Chow, Sherman S. M. and Wang, Tianhao and Huang, Chenyu and Sun, Huan}, year={2023}, month=Nov, pages={2665–2679}, collection={CCS ’23} }
  title = {DP-Forward: Fine-tuning and Inference on Language Models with Differential Privacy in...}
  author = {Minxin Du and Xiang Yue and Sherman S. M. Chow and Tianhao Wang and ... (+2 more)}
  year = {2023}
  booktitle = {Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security}
  doi = {10.1145/3576915.3616592}
  url = {https://doi.org/10.1145/3576915.3616592}
}
search-bibtex selection confirmed
Title: DP-Forward: Fine-tuning and Inference on Language Models with Differential Privacy in Forward Pass
Source: crossref  Score: 0.480
Clipboard: clipboard unavailable

@inproceedings{Du_2023,
  series = {CCS ’23},
  title = {DP-Forward: Fine-tuning and Inference on Language Models with Differential Privacy in Forward Pass},
  url = {http://dx.doi.org/10.1145/3576915.3616592},
  doi = {10.1145/3576915.3616592},
  booktitle = {Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security},
  publisher = {ACM},
  author = {Du, Minxin and Yue, Xiang and Chow, Sherman S. M. and Wang, Tianhao and Huang, Chenyu and Sun, Huan},
  year = {2023},
  month = Nov,
  pages = {2665–2679},
  collection = {CCS ’23},
}@inproceedings{Luo_2022,
  title = {Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling},
  url = {http://dx.doi.org/10.1109/infocom48880.2022.9796935},
  doi = {10.1109/infocom48880.2022.9796935},
  booktitle = {IEEE INFOCOM 2022 - IEEE Conference on Computer Communications},
  publisher = {IEEE},
  author = {Luo, Bing and Xiao, Wenli and Wang, Shiqiang and Huang, Jianwei and Tassiulas, Leandros},
  year = {2022},
  month = May,
  pages = {1739–1748},
}

@inproceedings{Du_2023,
  series = {CCS ’23},
  title = {DP-Forward: Fine-tuning and Inference on Language Models with Differential Privacy in Forward Pass},
  url = {http://dx.doi.org/10.1145/3576915.3616592},
  doi = {10.1145/3576915.3616592},
  booktitle = {Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security},
  publisher = {ACM},
  author = {Du, Minxin and Yue, Xiang and Chow, Sherman S. M. and Wang, Tianhao and Huang, Chenyu and Sun, Huan},
  year = {2023},
  month = Nov,
  pages = {2665–2679},
  collection = {CCS ’23},
}

提取论文元数据

> ./search-bibtex metadata ../../tests/pdf/"RollPacker Taming Long-Tail Rollouts for RL Post-Training with Tail Batching.pdf"        
{
  "metadata": {
    "filePath": "/home/whr/projects/search-bibtex/tests/pdf/RollPacker Taming Long-Tail Rollouts for RL Post-Training with Tail Batching.pdf",
    "pageCount": 18,
    "title": "RollPacker: Taming Long-Tail Rollouts for RL Post-Training with Tail Batching Wei Gao",
    "authors": [
      "Yuheng Zhao",
      "Dakai An",
      "Tianyuan Wu",
      "Lunxi Cao",
      "Shaopan Xiong",
      "Ju Huang",
      "Weixun Wang",
      "Siran Yang",
      "Wenbo Su",
      "Jiamang Wang",
      "Lin Qu",
      "Bo Zheng"
    ],
    "textSample": "RollPacker: Taming Long-Tail Rollouts for RL Post-Training with Tail Batching Wei Gao †∗ , Yuheng Zhao †∗ , Dakai An † , Tianyuan Wu † , Lunxi Cao † , Shaopan Xiong ‡ , Ju Huang ‡ , Weixun Wang ‡ , Siran Yang ‡ , Wenbo Su ‡ , Jiamang Wang ‡ , Lin Qu ‡ , Bo Zheng ‡ , Wei Wang † † HKUST ‡ Alibaba Group Abstract Reinforcement Learning (RL) is a pivotal post-training technique for enhancing the reasoning capabilities of Large Language Models (LLMs). However, synchronous RL post-training frequently suffers from significant GPU underutilization—often referred to as pipeline “bubbles”— caused by imbalanced response lengths within rollout steps. Many RL systems attempt to alleviate this problem by relax- ing synchronization, but this can compromise training accu- racy. In this paper, we introduce tail batching, a novel roll- out scheduling strategy for synchronous RL. Tail batching systematically consolidates prompts leading to long-tail re- sponses into a few designated “long rounds”, ensuring that the majority of rollout steps (“short rounds”) contain only balanced, short responses. By strategically reordering exe- cution, this approach dramatically reduces GPU idle time and accelerates "
  },
  "queries": [
    {
      "kind": "title",
      "value": "RollPacker: Taming Long-Tail Rollouts for RL Post-Training with Tail Batching Wei Gao",
      "confidence": 0.78
    },
    {
      "kind": "title-author",
      "value": "RollPacker: Taming Long-Tail Rollouts for RL Post-Training with Tail Batching Wei Gao Yuheng Zhao",
      "confidence": 0.72
    }
  ]
}

检索指定pdf论文的bibtex

> ./search-bibtex search ../../tests/pdf/"DP-Forward Fine-tuning and Inference on Language Models with.pdf"
search: searching 6 source channels...
search: 1/6 source channels completed [doi]
search: 2/6 source channels completed [arxiv, doi]
search: 3/6 source channels completed [arxiv, doi, semantic-scholar]
search: 4/6 source channels completed [dblp, arxiv, doi, semantic-scholar]
search: 5/6 source channels completed [dblp, arxiv, crossref, doi, semantic-scholar]
search: 6/6 source channels completed [dblp, arxiv, crossref, openalex, doi, semantic-scholar]
search-bibtex candidate selection
Filter: 
Keys: j/k move, g/G jump, / filter, Ctrl+O preview, Enter select, q cancel

> [0] arxiv            0.990 DP-Forward: Fine-tuning and Inference on Language Models with Different...
  [1] crossref         0.980 DP-Forward: Fine-tuning and Inference on Language Models with Different...
  [2] openalex         0.970 DP-Forward: Fine-tuning and Inference on Language Models with Different...
  [3] doi              0.960 DP-Forward: Fine-tuning and Inference on Language Models with Different...
  [4] semantic-scholar 0.950 DP-Forward: Fine-tuning and Inference on Language Models with Different...

Title: DP-Forward: Fine-tuning and Inference on Language Models with Differential Privacy in Forward Pass
Authors: Minxin Du and Xiang Yue and Sherman S. M. Chow and ... (+3 more)
Year: 2023  Venue: arXiv
IDs: DOI 10.1145/3576915.3616592  arXiv 2309.06746v2

BibTeX preview: compact
@inproceedings{Du_2023, series={CCS ’23}, title={DP-Forward: Fine-tuning and Inference on Language Models with Differential Privacy in Forward Pass}, url={http://dx.doi.org/10.1145/3576915.3616592}, DOI={10.1145/3576915.3616592}, booktitle={Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security}, publisher={ACM}, author={Du, Minxin and Yue, Xiang and Chow, Sherman S. M. and Wang, Tianhao and Huang, Chenyu and Sun, Huan}, year={2023}, month=Nov, pages={2665–2679}, collection={CCS ’23} }
  title = {DP-Forward: Fine-tuning and Inference on Language Models with Differential Privacy in...}
  author = {Minxin Du and Xiang Yue and Sherman S. M. Chow and Tianhao Wang and ... (+2 more)}
  year = {2023}
  booktitle = {arXiv}
  doi = {10.1145/3576915.3616592}
  eprint = {2309.06746v2}
  url = {https://arxiv.org/abs/2309.06746v2}
}
search-bibtex selection confirmed
Title: DP-Forward: Fine-tuning and Inference on Language Models with Differential Privacy in Forward Pass
Source: arxiv  Score: 0.990
Clipboard: clipboard unavailable

@inproceedings{Du_2023,
  series = {CCS ’23},
  title = {DP-Forward: Fine-tuning and Inference on Language Models with Differential Privacy in Forward Pass},
  url = {http://dx.doi.org/10.1145/3576915.3616592},
  doi = {10.1145/3576915.3616592},
  booktitle = {Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security},
  publisher = {ACM},
  author = {Du, Minxin and Yue, Xiang and Chow, Sherman S. M. and Wang, Tianhao and Huang, Chenyu and Sun, Huan},
  year = {2023},
  month = Nov,
  pages = {2665–2679},
  collection = {CCS ’23},
}

开发文档

限制

PDF 文本抽取依赖文件本身的可抽取文本质量；扫描版 PDF 需要先做 OCR。Semantic Scholar 匿名访问可能触发限流，限流会显示为源错误。外部书目信息源的 BibTeX 风格不完全一致，本工具保留源返回的 BibTeX，只做必要的首尾空白规范化。

许可证

MIT，见 LICENSE。

Name		Name	Last commit message	Last commit date
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.github/workflows		.github/workflows
agents		agents
docs		docs
scripts		scripts
src		src
tests		tests
zotero-plugin		zotero-plugin
.gitignore		.gitignore
CHANGELOG.md		CHANGELOG.md
CHANGELOG.zh-CN.md		CHANGELOG.zh-CN.md
CONTRIBUTING.md		CONTRIBUTING.md
CONTRIBUTING.zh-CN.md		CONTRIBUTING.zh-CN.md
LICENSE		LICENSE
Makefile		Makefile
README.en.md		README.en.md
README.md		README.md
RELEASING.md		RELEASING.md
RELEASING.zh-CN.md		RELEASING.zh-CN.md
SKILL.md		SKILL.md
package.json		package.json
pnpm-lock.yaml		pnpm-lock.yaml
pnpm-workspace.yaml		pnpm-workspace.yaml
tsconfig.json		tsconfig.json
tsconfig.scripts.json		tsconfig.scripts.json
vitest.config.ts		vitest.config.ts

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