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Paper Citation Record · LEDGER

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents

As of 19 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2608.10037.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2608.10037 v1

Coverage vector

measured 60 of 60 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:18:16.184665Z

measured 60 of 60 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

60 of 60 outbound references displayed

  • verified exact2
  • verified fuzzy36
  • unresolved22
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 801c8bcd-c38e-484e-97ec-60232818d3ae · outbound

This paper cites (2026) Docschisel.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents (2026) Docschisel

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:20.976606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:14.220251Z digest=sha256:93b4aeee816ee52f6db46bf19887b183b02dfc90504ddcebbc154d17a0f393f8

Observation e73c4dce-8211-4f71-9417-ff1523eee4cc · outbound

This paper cites (2025) Claude code.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents (2025) Claude code

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-14T04:18:20.935570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:14.257375Z digest=sha256:c008f275e973de8eec39394786baa6c19440c6d52cfb5ae872a6d40421e25b43

Observation 302b2fcc-ac0f-46c5-a7c6-bb21767df003 · outbound

This paper cites (2025) Writing effective tools for agents — with agents.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents (2025) Writing effective tools for agents — with agents

Reference 3

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no resolver link, observed 2026-08-14T04:18:14.304753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:18:14.304753Z digest=sha256:68ac52d71586bfa91485aaf67f06c52287ac53184cadd892420377a0e3bea5f1

Observation fefaf750-e06a-4fb1-966b-58255794e905 · outbound

This paper cites (2024) Coze.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents (2024) Coze

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:20.843652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:14.338143Z digest=sha256:8d9354e22c23aa07e26215212360616929f094e49b6c2855a91a756f542c50d2

Observation 08bf60d3-9ca3-44d0-b3ef-dca3bbff5cfe · outbound

This paper cites Automatic evaluation of api usability using complexity metrics and visualizations,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Automatic evaluation of api usability using complexity metrics and visualizations,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:20.809950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:14.362902Z digest=sha256:b59bfb0bf7540030c60cc48a83fc3552ba169b9c7476efc660b6781968c0b487

Observation 2634c2de-e054-4294-a925-484208e95d05 · outbound

This paper cites Improving api documentation usability with knowledge pushing,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Improving api documentation usability with knowledge pushing,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:20.744735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:14.373190Z digest=sha256:6d0ca72673bb99a306603ec804d28364035a3843067c5c429b5aec217c227a8b

Observation b546d0cb-cb76-4ace-82af-8747f510df59 · outbound

This paper cites (2024) Dify.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents (2024) Dify

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:20.635067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:14.400813Z digest=sha256:061dff7042ffb1c090ea9d26add2f6a19ac01ad8d501b647e031759be18b38d7

Observation 43e4178c-302e-4952-860f-0396edafab89 · outbound

This paper cites Anytool: Self-reflective, hierarchical agents for large-scale api calls,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Anytool: Self-reflective, hierarchical agents for large-scale api calls,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:20.556389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:14.439890Z digest=sha256:fb798a09398c970b0f7687828b9d41d766a6fa7b960b233018811513cefdb1e4

Observation 06205ef2-a291-406a-ab88-42de75ecb3fc · outbound

This paper cites Play2prompt: Zero-shot tool instruction optimization for llm agents via tool play,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Play2prompt: Zero-shot tool instruction optimization for llm agents via tool play,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:20.496818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:14.485367Z digest=sha256:6fecb83a32233e4f67b14510f839cb136108b552b7e7a8f34a248ed8e6d069c1

Observation aec939af-4320-4676-8ae7-b350b6c41227 · outbound

This paper cites JTPRO: A Joint Tool-Prompt Reflective Optimization Framework for Language Agents.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents JTPRO: A Joint Tool-Prompt Reflective Optimization Framework for Language Agents

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-08-14T04:18:16.894683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:14.495820Z digest=sha256:cd5103efcf3dd6307bfecaac59771ea047c3cb2aeb4b76d2c45c77843d6a7243

Observation d5b37554-0fac-4ccf-9941-b776d9e9e518 · outbound

This paper cites ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools

Reference 11

Resolution
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no resolver link, observed 2026-08-14T04:18:14.540176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:18:14.540176Z digest=sha256:0169a6739d82572c2487df0f63a36d834cb88dc72bbdf61949c16d49ecf06364

Observation ef80f497-532b-480c-a1fb-3ecc3d073419 · outbound

This paper cites (2023) Google gemini.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents (2023) Google gemini

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:20.458143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:14.594745Z digest=sha256:432538cedb3f884a0c117e8233b7705bc1f7286d3880babc752f7c4893cba965

Observation 4c2e1306-50d2-4356-bc89-e87312c13d22 · outbound

This paper cites Gravitas.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Gravitas

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:20.359542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:14.613442Z digest=sha256:824346881cf476f1fe271a793b0451a015b34865e0589e48e2c100c349280e85

Observation c21a2884-8506-4900-adf4-2641ce1e29d1 · outbound

This paper cites Learning to Rewrite Tool Descriptions for Reliable LLM-Agent Tool Use.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Learning to Rewrite Tool Descriptions for Reliable LLM-Agent Tool Use

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-08-14T04:18:16.724738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:14.645599Z digest=sha256:13323f3e3d7fa2c8d254a2b0e52594ba11268446c41aeb91474d44de73c5ca20

Observation 7a9c855e-af44-474a-b7d5-452b3445ce26 · outbound

This paper cites Llm-based multi-agent systems for software engineering: Literature review, vision, and the road ahead,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Llm-based multi-agent systems for software engineering: Literature review, vision, and the road ahead,

Reference 15

Resolution
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no resolver link, observed 2026-08-14T04:18:14.664151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:18:14.664151Z digest=sha256:a6e906a3a58eb76142d1ae9224e42f8d3316f9d9b69b12a5d093445201e1b832

Observation c93a8f7b-0e92-4168-addc-4b7001622bc1 · outbound

This paper cites A simple sequentially rejective multiple test procedure,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents A simple sequentially rejective multiple test procedure,

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-14T04:18:14.668567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:18:14.668567Z digest=sha256:66255079286458cf0c90e3ace7b7ef884a53fd2472fa86ee16d4c23fe4082a05

Observation 8686a024-415f-4357-b651-b6317b001471 · outbound

This paper cites Metagpt: Meta programming for a multi- agent collaborative framework,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Metagpt: Meta programming for a multi- agent collaborative framework,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:20.144909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:14.672412Z digest=sha256:fe6f043fab47b5a83a2305639981eeddcfd70806ee25885f1d9db99608c142ed

Observation d1cd341f-1810-4714-9ecc-61b81172f09a · outbound

This paper cites Large language models for software engi- neering: A systematic literature review,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Large language models for software engi- neering: A systematic literature review,

Reference 18

Resolution
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no resolver link, observed 2026-08-14T04:18:14.686545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:18:14.686545Z digest=sha256:20138aad6275111acae1890f906f0a92f69197553224aaef14dc716ea953f8a3

Observation 85e97315-9b49-493a-be2a-541802c25a69 · outbound

This paper cites Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-14T04:18:14.690786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:18:14.690786Z digest=sha256:19a06015f7278f9566dc0ccb9babab908d3f103733ea1741df3d17173ff40243

Observation e0d887b5-586d-4c45-9f1d-b1a3c9a0999e · outbound

This paper cites Chatgpt for shaping the future of dentistry: the potential of multi-modal large language model,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Chatgpt for shaping the future of dentistry: the potential of multi-modal large language model,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:19.994848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:14.714753Z digest=sha256:8178562d078f5488368dd5a89b0765f9ac270acd2481b9722bc93ed9de851d5e

Observation 07ad7336-b29a-46e0-b63e-b215c01a9dfe · outbound

This paper cites Crmarena: Understanding the capacity of llm agents to perform professional crm tasks in realistic environments,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Crmarena: Understanding the capacity of llm agents to perform professional crm tasks in realistic environments,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:19.922709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:14.735540Z digest=sha256:c63c885fb5d635d3027f45279a5c722df3302065288b055b79bd1a72fc0d7971

Observation 92603ab7-9cd7-4fdc-ab26-22d34024fcb4 · outbound

This paper cites Metatool benchmark for large language models: Deciding whether to use tools and which to use,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Metatool benchmark for large language models: Deciding whether to use tools and which to use,

Reference 22

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verified fuzzy
raw_fallback, observed 2026-08-14T04:18:19.803445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:14.794749Z digest=sha256:1ba57ff25e85a3a6d65efde34bd37906e63cd465440960715272b1593488173f

Observation fadb12ea-68cd-4488-a560-ec01a6ae6063 · outbound

This paper cites Swe-bench: Can language models resolve real-world github issues?.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Swe-bench: Can language models resolve real-world github issues?

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:19.687385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:14.844752Z digest=sha256:d8c82052a3fc2013a01cc62cbc5050902012f258923185dc7ab585a4fec5428a

Observation 18565f4b-fdbd-4c23-b3e9-1598a75ee085 · outbound

This paper cites Automatic detection of five api documentation smells: Practitioners’ perspectives,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Automatic detection of five api documentation smells: Practitioners’ perspectives,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:19.564755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:14.877934Z digest=sha256:5972ffd14f99ebe57d78965c29e5f835a79acde6f7e748191475914bdb90bee5

Observation 9b55bbba-d2f5-4301-84b5-11998e904297 · outbound

This paper cites (2024) Langchain: Build agents faster, your way.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents (2024) Langchain: Build agents faster, your way

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:19.464829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:14.891686Z digest=sha256:db14d90eb5d7b5b8a5ae7af5e92abcfe16154d9d5f9b33c26ad2303552e0b032

Observation c69f7326-2c6d-44c0-8a09-b6f2a7723aa0 · outbound

This paper cites Verification-guided context optimization for tool calling via hierarchical llms-as-editors,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Verification-guided context optimization for tool calling via hierarchical llms-as-editors,

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-14T04:18:14.930622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:18:14.930622Z digest=sha256:09cc89b6e25b68f167a77e1ee3a5f0a7a4ed1a5c1184646007b6fc6d29e79ee2

Observation 30ad9b82-e658-4897-9776-9bb68b8888e5 · outbound

This paper cites Api-bank: A comprehensive benchmark for tool-augmented llms,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Api-bank: A comprehensive benchmark for tool-augmented llms,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:19.328460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:14.959420Z digest=sha256:5932a202b029126fb56efa8f59c447f8a53721274b5ff329a0eafa5c0ae8fb61

Observation b34249d3-5f79-4f07-8d5b-6462867b60f1 · outbound

This paper cites Soen-101: Code generation by emulating software process models using large language model agents,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Soen-101: Code generation by emulating software process models using large language model agents,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:19.244750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:14.987616Z digest=sha256:3abdcf9d171b7e545b8d2291af99099eecee3d98894478bc03707bd2c36387f0

Observation 7a4a2515-e69e-4e97-92ee-cd6c639e93b9 · outbound

This paper cites ToolScope: Enhancing LLM Agent Tool Use through Tool Merging and Context-Aware Filtering.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents ToolScope: Enhancing LLM Agent Tool Use through Tool Merging and Context-Aware Filtering

Reference 29

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unresolved
no resolver link, observed 2026-08-14T04:18:15.002633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:18:15.002633Z digest=sha256:5db3d072c17eb42ef1a95291581d800e35327b26c6095c8312ad73c2590b32a4

Observation 3d4b044c-595c-4813-bb89-395263abcf99 · outbound

This paper cites Patterns of knowledge in api reference documentation,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Patterns of knowledge in api reference documentation,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:19.094886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:15.017397Z digest=sha256:54b9e20d824a2238251562ec8e82738f388d4c15f6422147722d4b6c778a72e8

Observation 7d82f430-c1c2-41ee-9098-d825cd2a463d · outbound

This paper cites Mann-whitney u test,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Mann-whitney u test,

Reference 31

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unresolved
no resolver link, observed 2026-08-14T04:18:15.042525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:18:15.042525Z digest=sha256:6bb7f6d3f7a25bf6a4f726cfe8672d661d1425525a4332826a88d3779185de72

Observation 5ed6ca35-b21c-4965-9833-b095f10dbd60 · outbound

This paper cites Collaboration challenges in building ml-enabled systems: Communication, documentation, engi- neering, and process,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Collaboration challenges in building ml-enabled systems: Communication, documentation, engi- neering, and process,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:18.884855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:15.074746Z digest=sha256:284f9863cad8b6a64908f02555340f8cbdb1a9dc8bffeb9e7b204b27402d5a85

Observation fbfee106-cdf6-4410-858d-aceadde670a1 · outbound

This paper cites A systematic mapping study on api documentation generation approaches,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents A systematic mapping study on api documentation generation approaches,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:18.764759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:15.114749Z digest=sha256:9b59f2a3a0102c536ced4cc8ae2cad660d3100ae2f7719ebe87631e65fa00722

Observation 04c20019-0ad6-4566-8bfa-2bd90c89f084 · outbound

This paper cites (2023) Introducing chatgpt.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents (2023) Introducing chatgpt

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:18.655844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:15.150060Z digest=sha256:739edb5f5354e83d4bf64e18d36d042b2d96f9338148c8d28cedb62c64b4f4fd

Observation e01e9db7-66be-4f08-af9c-fc8d7d05c3b3 · outbound

This paper cites (2024) Gpt-4o.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents (2024) Gpt-4o

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:18.574760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:15.176820Z digest=sha256:05dc906d00514eab2dfc5375190ffa82db8f097690bbf8ad9e7e5b190b44c594

Observation 1f0fd8e2-cfaf-422d-830e-f16ef394c532 · outbound

This paper cites (2025) Introducing codex.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents (2025) Introducing codex

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:18.394206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:15.214749Z digest=sha256:f88567ff86f0505aa83a1d7d811cc840b824bde07f66c9a35f5ae4780da5eb9e

Observation 68b7b448-ce0a-49c6-b4f9-9fb3cf18d939 · outbound

This paper cites (2024) Openapihub.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents (2024) Openapihub

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:18.287148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:15.265153Z digest=sha256:730a806da6af3a4e39e0afb65068a9baa711924492ebe0abd571c3ebb1f15acf

Observation 1beccd1e-8922-4df8-88fb-28153526d47d · outbound

This paper cites Gorilla: Large language model connected with massive apis,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Gorilla: Large language model connected with massive apis,

Reference 38

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unresolved
no resolver link, observed 2026-08-14T04:18:15.314832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:18:15.314832Z digest=sha256:e8a3766c414e7f0746c00a9a4058a6ca23f8334eb5ab2ec7fc93749ef581634b

Observation 1c12a672-a1e7-423f-a5bd-30975098b457 · outbound

This paper cites An empirical study of api usability,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents An empirical study of api usability,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:18.140050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:15.364752Z digest=sha256:82d5cd1a7bb13ea1824facd22e3f322298daab4a21206ee82a0a1b7ecd2cf885

Observation e1209883-57ce-473c-a839-c291c80030bf · outbound

This paper cites Toolllm: Facilitating large language models to master 16000+ real-world apis,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Toolllm: Facilitating large language models to master 16000+ real-world apis,

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-14T04:18:15.414750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:18:15.414750Z digest=sha256:3eb56a7ee979bbb1051e2ffcc34931039037223247df063dd18607fd9457d81c

Observation f29ac493-23d3-44c7-bd3b-e94e86a1f63b · outbound

This paper cites Towards completeness-oriented tool retrieval for large language models,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Towards completeness-oriented tool retrieval for large language models,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:17.965274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:15.464751Z digest=sha256:5b4bd08b05ef38c3b297b8e2e5c7ab9e4ada1de79a7b0084c6df770b3137f385

Observation 33f204ef-80a2-4f27-9ce8-74ba7b083c4e · outbound

This paper cites From exploration to mastery: Enabling llms to master tools via self-driven interactions,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents From exploration to mastery: Enabling llms to master tools via self-driven interactions,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:17.804752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:15.504743Z digest=sha256:736c6603a6dd87e0530dc8d634a9107705e84d227f48479411b143f89d467c37

Observation 8656b44d-3936-40ff-b4db-af37529d65d6 · outbound

This paper cites (2024) Rapidapi.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents (2024) Rapidapi

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:17.677357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:15.544749Z digest=sha256:54a144771080a5288ba8c1a6e185b326b1e62824aa4db848363a120df410b21a

Observation 07d0b46f-4f0d-49ba-8086-84569525a171 · outbound

This paper cites Toolformer: Language models can teach themselves to use tools,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Toolformer: Language models can teach themselves to use tools,

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-14T04:18:15.583325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:18:15.583325Z digest=sha256:23a0690dd5f7c151235804653fa2ad81c4725d730ef773c66c991272cd0d62ad

Observation 04bff4c0-4070-412a-ae7d-8b0a6aaf5c1c · outbound

This paper cites Shortcutsbench: A large-scale real-world benchmark for api-based agents,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Shortcutsbench: A large-scale real-world benchmark for api-based agents,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:17.489901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:15.621273Z digest=sha256:4f13d6f23bfe0a6fd3bc616f943e7b50ba30e6b8cb62f71f67776d33ca646b24

Observation 764327a4-e065-4e14-8127-1c33e40a1e9a · outbound

This paper cites An empirical study on evolution of api documentation,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents An empirical study on evolution of api documentation,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:17.415525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:15.664737Z digest=sha256:5d3a7b43a5c4ce15b10b7bdfde02035aaf7cd3969826ca1c5a1a43ca2e5654ae

Observation 58f4ac56-7e77-43d4-9ca6-5dcaedab92f6 · outbound

This paper cites Tool learning in the wild: Empowering language models as automatic tool agents,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Tool learning in the wild: Empowering language models as automatic tool agents,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:17.274750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:15.704743Z digest=sha256:e3dc3ffad9ecbd303d620c1268aa5d82371d2f05e8089e5a5c6707f4f13051bd

Observation fa50b145-dd5e-4fd8-8cea-c566a5445187 · outbound

This paper cites WorkBench: a Benchmark Dataset for Agents in a Realistic Workplace Setting.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents WorkBench: a Benchmark Dataset for Agents in a Realistic Workplace Setting

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-14T04:18:15.752600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:18:15.752600Z digest=sha256:3d058c4487b88c733e6270c71f19677e4c5d92270ada6e2fa7e20b9a6407edfb

Observation fc53e66b-e793-4931-89ca-1c90e35f662a · outbound

This paper cites Live api documenta- tion,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Live api documenta- tion,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:17.153000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:15.793109Z digest=sha256:a3d4e02cb011481bbcf74a2d2437643445dafdb7456556fe7918dddb1e2cee3a

Observation 5e80a77b-0f74-4db2-90c0-707c18d66ca9 · outbound

This paper cites ToolAlpaca: Generalized Tool Learning for Language Models with 3000 Simulated Cases.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents ToolAlpaca: Generalized Tool Learning for Language Models with 3000 Simulated Cases

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-14T04:18:15.844874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:18:15.844874Z digest=sha256:6ab257dfa197a219709ee63a26a3d2e760eafb544eaae90d47576bccca315ab1

Observation 4c763b22-4d7e-4288-a0dd-dc197d4fbe3a · outbound

This paper cites Autogen: Enabling next-gen llm applications via multi-agent conversations,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Autogen: Enabling next-gen llm applications via multi-agent conversations,

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-14T04:18:15.886677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:18:15.886677Z digest=sha256:dc5185ee2df72fac5bec97300da31f575b661981fe77418ccb1fcf555d521f3a

Observation e11a8cdb-29d4-4bb8-9e33-ccc2e19f864e · outbound

This paper cites Demystifying llm-based software engineering agents,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Demystifying llm-based software engineering agents,

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-14T04:18:15.914748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:18:15.914748Z digest=sha256:f9792d00232555b8f98b2bdecf7c61dc916ad4bc9030823a6c6b9a0799ceeb48

Observation fd84d87b-b936-4306-b40e-00b2d0c2948e · outbound

This paper cites On the Tool Manipulation Capability of Open-source Large Language Models.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents On the Tool Manipulation Capability of Open-source Large Language Models

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-14T04:18:15.951161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:18:15.951161Z digest=sha256:af079bde9ab7a0794c07b1ccbfb26fa3d3072ed938001babbed432fd8d69cfcb

Observation 00382caa-6ec1-48a4-ab05-77255561d65d · outbound

This paper cites Swe-agent: Agent-computer interfaces enable automated software engineering,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Swe-agent: Agent-computer interfaces enable automated software engineering,

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-14T04:18:15.989113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:18:15.989113Z digest=sha256:6cf810fc084c37cdb792ec7968a735106ba3d296a18780f56652563e42945322

Observation f1c8f869-8ec3-4d40-a557-3a9c4cb712b9 · outbound

This paper cites $\tau$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents $\tau$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-14T04:18:16.024825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:18:16.024825Z digest=sha256:f58b57b7a1c52b25f0c3706e8dfadd1bfcd965e7e295bd052f97d9180e6ae282

Observation 99810f11-3699-49b4-97d2-01aad0807cf9 · outbound

This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents ReAct: Synergizing Reasoning and Acting in Language Models

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-14T04:18:16.064737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:18:16.064737Z digest=sha256:3b98c087e33af20f9ad7ae7af9f2e2b5f26faa68edbf708253c01e7db9086da9

Observation 67a20eb4-adfe-4e7b-bd91-f806a7f16333 · outbound

This paper cites Benchmarking LLM Tool-Use in the Wild.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Benchmarking LLM Tool-Use in the Wild

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-14T04:18:16.108110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:18:16.108110Z digest=sha256:0c3b71fc0d6a36055411dd52f3bad81ebb6954d8e34571c90e919aa5d6338d7c

Observation d8894cb7-583d-4248-9ef7-9292f06e57db · outbound

This paper cites Easytool: Enhancing llm-based agents with concise tool instruction,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Easytool: Enhancing llm-based agents with concise tool instruction,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:16.990134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:16.148234Z digest=sha256:9d2d0393d3cc4080a34b5dede83318340f54e8ad5ae29efbfbd44464b58b954d

Observation cbf75684-8be0-4f9f-9219-0494acbaa31d · outbound

This paper cites GLM-5: from Vibe Coding to Agentic Engineering.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents GLM-5: from Vibe Coding to Agentic Engineering

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-14T04:18:16.162145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:18:16.162145Z digest=sha256:c87149e8bfff81d2ccf1f357c7e7402ff4cd3866f3004702f5cd61cb3290caa0

Observation 5d5da286-da30-4808-b6eb-c6e939cf0c5b · outbound

This paper cites Losemb: Logic- guided semantic bridging for inductive tool retrieval,.

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents Losemb: Logic- guided semantic bridging for inductive tool retrieval,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:18:16.949021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T04:18:16.184665Z digest=sha256:2c37fbec5da77d11e62a896c719f597a0e0477af18722f76adcb040bdbdd4bc4

Pith citing papers

No inbound Pith citation observations are available.