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Paper Citation Record · LEDGER

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

As of 23 July 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations 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 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-07-23T06:31:01.910684+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

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 2026-07-23T06:31:01.910684+00:00.

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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 2026-07-23T06:31:01.910684+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:cda581b5a1ff05fdf2ad6c061f56e7276369360e182049f3f6f023d3050ba806

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 2026-07-23T06:31:01.910684+00:00.

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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 2026-07-23T06:31:01.910684+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:1ca218299749b58cbd7a47330ed4631b9b399da965c8c0716024d926883220de

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 2026-07-23T06:31:01.910684+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:671073ea722f255dd32a8b2fae18c5fdeefc54eeac72ce4a7fe1c3a8cead3121

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 2026-07-23T06:31:01.910684+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:3673493202fb98f763b60c6e466eca7c2c049f5a7378121bcc5be27be008b8e1

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 2026-07-23T06:31:01.910684+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:744703d24ead6877b0bea6f7001b0f555ca1b9810f444b67ab2ac98a4e12ffaa

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 2026-07-23T06:31:01.910684+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:76d6ee996e1dbb6916faad298d1c1228ba3ad836a5e9fb86cfb2e8bd0482d4b0

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 2026-07-23T06:31:01.910684+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:1c0dd5c85ab830f0c7819b8034a91ced8f3879ba9a0532f7bc82a55a19cb92d8

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 2026-07-23T06:31:01.910684+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:ab9c82725e11b3a577386f8e1f4cab6266c2e830708ff104daf48f0e6300193b

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 2026-07-23T06:31:01.910684+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:22600e57b1e8119dd4d02dfe1f16a75a42b68b040a8eca1684c7f9b99795034d

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 2026-07-23T06:31:01.910684+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:7d8b7b9106ebb1a4c9d25d4204d85719f0c4ce68a0f392d68a4e9b5fbdf0b123

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 2026-07-23T06:31:01.910684+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:7bbde59a5c26737ebda66b5a653888201fc353f3731eac7ab5c3db6894a3e0b1

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 2026-07-23T06:31:01.910684+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:cb60dc75f37286c5a8a277224ec43ad0217edcf878b2a4aefb6ceaf7a6d77b0f

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 2026-07-23T06:31:01.910684+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:0dea859bd8f3473efeb4b8aa58b976b5fed1f735d9fef26ee0e5a80f854defe5

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 2026-07-23T06:31:01.910684+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:9146a81a73ee1036691f05b97e02a279617067b22c5bc120638f6b6f1a6069e0

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 2026-07-23T06:31:01.910684+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:71c4c0592e7301381aab4826e507a3ea269af5f909b82b5284d1406600e8d56f

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 2026-07-23T06:31:01.910684+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:19e4470fd063ebf3640e8c16f95cf26446551940fd9851424e54f0d6a99e2bf4

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 2026-07-23T06:31:01.910684+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:83c8f646758c1f8f7e957cfd33dcee94dca139464943a67a9e9e03c3f1ad6f36

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 2026-07-23T06:31:01.910684+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:d12dfb0e36b60da5f2418fba6e4165b73b1d760983702ae96b37cd4d53fdd0eb

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 2026-07-23T06:31:01.910684+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:089243880f249e3f7db5da35ccfccb5c4c2adb0d216447b9fe8083dede21e6ca

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 2026-07-23T06:31:01.910684+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:f4c833e3250b93c9b4725490dc5eecf9c0b26469a98abe8dd23054d6d9bf5218

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 2026-07-23T06:31:01.910684+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:468c19453ed4cb44d7b3fa3a82247cfe475cce6a277be4ec0416033cae8f3513

Pith citing papers

No inbound Pith citation observations are available.