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Paper Citation Record · LEDGER

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents

As of 15 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 1 inbound Pith citation observation for arXiv:2605.18882.

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

pith.paper-citation-record.v1
2605.18882 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-20T16:07:43.528608Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-30T20:47:41.031108Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

23 of 23 outbound references displayed

  • verified exact6
  • verified fuzzy15
  • unresolved0
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d921b53f-bf3a-45d3-bf0b-7bad0978ac5f · outbound

This paper cites OpenAI GPT-5 System Card.

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents OpenAI GPT-5 System Card

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-05-20T16:08:33.508171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:45bf9f99c0b6954f749d3405066caeb50aa9d526e86f2746dfa530c83c9f7915

Observation 6a1b3530-5557-4466-851f-a6d62cdd6a3e · outbound

This paper cites Claude opus 4.6 system card.

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents Claude opus 4.6 system card

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T16:08:33.771591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:dc8d0ce104d8d744156e18f11abe7815a03f7fb84fa3c30b06bffafbdb43bba8

Observation 5a185384-4537-4877-87f4-e73203053c7c · outbound

This paper cites Gemma 4 model card.

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents Gemma 4 model card

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T16:08:33.775188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:d81ec1e34695cbf35680c85b10f690426d4ae0e2b184cc44b1faa832ddd74afe

Observation 43b0c87f-5449-402e-a6b4-c603ce08da22 · outbound

This paper cites Qwen3.5: Accelerating productivity with native multimodal agents, February 2026.

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents Qwen3.5: Accelerating productivity with native multimodal agents, February 2026

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T16:08:33.767756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:c0b763bc86e4e4aacfb3c891dc1b56d7ef5c317ec805dc7cdfe63935fc4a84a0

Observation 4c8db2f8-ba6d-4f6e-83c8-54f34dd91cc6 · outbound

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

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents Toolformer: Language models can teach themselves to use tools

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T16:08:33.769747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:6d8e18d5702f62102e3d03a3d97d13920b912aea9c367a19d262a947483e2d48

Observation 684f90c4-a597-472c-819d-156289a82fa1 · outbound

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

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents Toolllm: Facilitating large language models to master 16000+ real-world APIs

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T16:08:33.773440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:3d310750cfd0d99595e6c2b924c9208a98f41bb44f5cb090e7b91da613d1827c

Observation c67fc59c-7419-4b8d-b05d-8e6e3c141b1d · outbound

This paper cites Gorilla: Large Language Model Connected with Massive APIs.

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents Gorilla: Large Language Model Connected with Massive APIs

Reference 7

Resolution
metadata mismatch
local_arxiv, observed 2026-05-20T16:08:33.505281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:70e048c74e3eb67443b68e9bd996d93064ed2b53cf99de705f8c92844d765354

Observation db14b60a-f078-4bef-acb8-6d1e8532f835 · outbound

This paper cites AFlow: Automating agentic workflow generation.

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents AFlow: Automating agentic workflow generation

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T16:08:33.759231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:9880fdae7e4f9ba952a5be60289e153a87901b72d24aabf441e7ce2fd29412d0

Observation 1597226d-03dd-4382-b9e0-a37bb249d553 · outbound

This paper cites Gemma 3 Technical Report.

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents Gemma 3 Technical Report

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-05-20T16:08:33.499401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:d89519bfb61903e977b6b6c17070d79ab66f3ef9b9e66bac6310359293da7e82

Observation e724c0f1-8fb1-45f2-bb59-73a22cd504d1 · outbound

This paper cites Ministral 3.

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents Ministral 3

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-05-20T16:08:33.496308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:ca1294008c03d2b979d658179eaa3684ed0f62900993fe8b41d49c8ba0e83e9b

Observation c4c96279-aab1-4a1f-bd8c-080c4aa91e75 · outbound

This paper cites When2call: When (not) to call tools.

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents When2call: When (not) to call tools

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T16:08:33.752586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:646b30453a77d8fc1538e7f5cc9cbcb4a8f9f544090de219b8cdd183ac5fc2c4

Observation baa9ec18-277d-42c9-a003-b5da9911b47d · outbound

This paper cites Sparse autoencoders find highly interpretable features in language models.

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents Sparse autoencoders find highly interpretable features in language models

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T16:08:33.754662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:2e1a0e9374e2cc1ec4b4a639341a63c7d6a3c6d0483c099d2d2eb259575097f3

Observation 00955fc6-024d-4716-84da-21f9b969be71 · outbound

This paper cites Scaling and evaluating sparse autoencoders.

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents Scaling and evaluating sparse autoencoders

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T16:08:33.757005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:7558aab63d304f1fee5831eea00c4853b1cc57a043748ad585d54eea3640e326

Observation c5daa985-6fc4-404b-b295-7a3f7601d3d4 · outbound

This paper cites Daniel Freeman, Theodore R.

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents Daniel Freeman, Theodore R

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T16:08:33.761411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:aa2064e467bcb88fda7f397c82dd7d68acd682c5cb80490bbccf09494f46eda4

Observation f8041432-c8c9-4637-a961-42f3a0bdb675 · outbound

This paper cites MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning.

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-05-20T16:08:33.490050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:d712ded64261f221fa395600e4aa046233e1e7f10069fc4aefbbf33d61ef8338

Observation c801592e-9562-4ad0-983e-d264963a0778 · outbound

This paper cites Narasimhan, and Yuan Cao.

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents Narasimhan, and Yuan Cao

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T16:08:33.748347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:56df080710b91733f23c2c15b098fcfae57509999adfe7cdde5f8878f80934a1

Observation f25e3e7f-6857-4333-95be-8295ce093fa2 · outbound

This paper cites Agentbench: Evaluating llms as agents.

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents Agentbench: Evaluating llms as agents

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T16:08:33.765341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:3a082b06d9d987d8137140ef29e0b2deedba5b9afdd97b17a2fed1f136b27422

Observation b592b5ba-50d9-42fe-bb3a-eaa412b11a82 · outbound

This paper cites Patil, Huanzhi Mao, Fanjia Yan, Charlie Cheng-Jie Ji, Vishnu Suresh, Ion Stoica, and Joseph E.

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents Patil, Huanzhi Mao, Fanjia Yan, Charlie Cheng-Jie Ji, Vishnu Suresh, Ion Stoica, and Joseph E

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T16:08:33.746414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:0c55712f89d44cdfd426677e72e627f6bf544a9986e0dc15b7f7125966b83202

Observation e45c8cc3-02ac-4ad7-bb77-c34ccc5abefa · outbound

This paper cites Michaud, Stephen Casper, Max Tegmark, David Bau, Eric Todd, Atticus Geiger, Mor Geva, Jesse Hoogland, Daniel Murfet, and Tom McGrath.

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents Michaud, Stephen Casper, Max Tegmark, David Bau, Eric Todd, Atticus Geiger, Mor Geva, Jesse Hoogland, Daniel Murfet, and Tom McGrath

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T16:08:33.744433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:940f6b817eafebffbca8605d401427fcc56f5fbc53a3a79e234d40943fb93409

Observation b62257e4-3ace-4be4-84d6-90ba8cef42ac · outbound

This paper cites Towards monosemanticity: Decomposing language models with dictionary learning.Transformer Circuits Thread.

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents Towards monosemanticity: Decomposing language models with dictionary learning.Transformer Circuits Thread

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T16:08:33.750529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:4c5b6a2e774b424c275ee73a4d3ca5b9874ca8c2e16d35732eb587640c0eb6ba

Observation 40369072-b782-4c3e-832c-05e852df4b37 · outbound

This paper cites Jumping Ahead: Improving Reconstruction Fidelity with JumpReLU Sparse Autoencoders.

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents Jumping Ahead: Improving Reconstruction Fidelity with JumpReLU Sparse Autoencoders

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-05-20T16:08:33.493338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:22711c21858181105af8329e1cc5f0dbadff6cdb28d4cef372db475479d84f0d

Observation 1151a622-023f-45f5-af30-1c7efcc6847f · outbound

This paper cites The Pile: An 800GB Dataset of Diverse Text for Language Modeling.

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents The Pile: An 800GB Dataset of Diverse Text for Language Modeling

Reference 22

Resolution
verified exact
local_arxiv, observed 2026-05-20T16:08:33.502236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:481573fe277327914976b53087a9bf7188f887bdd108a77ca578e43d56e55d72

Observation c7c18536-15b2-42de-91cf-eba9b63f844f · outbound

This paper cites classification.

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents classification

Reference 23

Resolution
malformed identifier
raw_fallback, observed 2026-05-20T16:08:33.763415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:5327bd5b1c703b08dfb958b6a472f2b884c57716379c348ba5e5e5e501b6c54f

Pith citing papers

Observation e261a5e2-b4cf-49a9-90cb-084e58e5188f · inbound

Do LLMs Know Their Vulnerable Scenarios? cites this paper.

Do LLMs Know Their Vulnerable Scenarios? To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents

Reference 29

Resolution
unresolved
no resolver link, observed 2026-07-30T20:47:41.031108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T20:47:41.031108Z digest=sha256:2c12d2c000cc4c4a0ca42200697b9dca6a405326804535e1b74245fa33458d70