Pith. sign in

Paper Citation Record · LEDGER

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

As of 22 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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:d2578698446790d8997166a08847fd15cf08e36aa2954828aaad179b69504f41

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:41dee7d76dd987da2e7fcc1501ef3d2ac87ad2e62ff6e8ecb42d2cad19534f31

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:6d5ba93d191081e069091fc32641fc9eb9cb9056bec2ed6ab79b79b6fd5fdaa7

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:69b96760254a1a7202de6bfa920afb65d96972356a4eaf73eb0ac81740876f42

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:906289447e59d0c00c5dd010f0b7d0ad8572966d62cc1aa05047d9638941d456

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:235159a3d564ecfe5acf8fae1625c0a4717e69179925c2fe7e605d3fb95e84e1

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:75bce8fb4b448761ef7f8ea4266380c27e9a77afd8d1b4d56f43192b665cbb24

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:3f9bd8534941aa55e244404762f4d37f436070cb0f7ff0d8aaa33ad675400abb

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:36ac5f9e2fb209be2874154dbc9e089885a133e15aff3b8f925b2d349745b403

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:d9d0c1693f03cdce59313a9af2d750d53769444a62c2279e2e4d5aff79a0dbf3

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:d0166d731be382a4c2a954b38bc355637e638b3d262a75cbb6d474705a48f253

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:1bcd881bcc99a631bdb618307d582694d878dbc5517e2ba1c2e586d4a3a98f63

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:99ff7c4ae359f06ef749d5dbacbb7865db15032643c44271f9bf64ebdf628311

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:6a0c2fc06cd953a022a9a5f26a8bbcce8640011670052259cf11f8deaecd98d9

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:2fac68689674215298302a0ff4cad5d87eb54f216995121856f71640437bc632

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:eb83513357a26e6c170fa0b1d7479015db19c011cf88c093750e73a1d9d4a927

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:91765a8074815ba9b503648f28200295393a7938a692fe627c6fb426b70cd68d

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:f15f732d6aa346c8043ca15605966c570a0c6c2359bf912f919f7a630e19ea75

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:74c1546ee74b94d7400ba39c9498786b4c49bd81a594b263bbdd4d214b1680f8

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:830022b8d23205a62c6c6be84b4a9c51c5e17a43984f60f09b5a7f8649ff256a

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:a890d5702a660601f7ad895913a38278c17351a42c1bae0e3503f18015649611

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:13d2af98dabb64834af849a3490d5f778881889ad3a65041abb686b9f84a2d75

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T16:07:43.528608Z digest=sha256:f3ea6faf6b98749d416a9bb6359f11cb724ab510e65ba8adcd74e351c12c368c

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:e655fc7f37e83618b18a543426bf7bdd55039d9bb3c3344e5680428ecb47b0b9