Paper Citation Record · LEDGER

Who&When Pro: Can LLMs Really Attribute Failures in AI Agents?

As of 9 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2607.09996.

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

pith.paper-citation-record.v1
2607.09996 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-14T01:10:44.920887Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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 exact0
verified fuzzy0
unresolved21
parse uncertain1
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2b17e421-f1b4-479e-bfa8-841c28b61996 · outbound

This paper cites ChemCrow: Augmenting large-language models with chemistry tools.

Who&When Pro: Can LLMs Really Attribute Failures in AI Agents? ChemCrow: Augmenting large-language models with chemistry tools

Reference 1

Resolution: unresolved; no resolver link, observed 2026-07-14T01:10:44.920887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f0e8b78-4ac2-430d-9a14-703f46878401 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Who&When Pro: Can LLMs Really Attribute Failures in AI Agents? Evaluating Large Language Models Trained on Code

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-14T01:10:44.920887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78dc2f59-7080-432a-b23e-42728447b864 · outbound

This paper cites emnlp-main.839/.

Who&When Pro: Can LLMs Really Attribute Failures in AI Agents? emnlp-main.839/

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-14T01:10:44.920887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed00be21-6056-4c7c-b030-1166c32d17f8 · outbound

This paper cites com/deepmind-media/Model-Cards/ Gemini-3-Flash-Model-Card.pdf.

Who&When Pro: Can LLMs Really Attribute Failures in AI Agents? com/deepmind-media/Model-Cards/ Gemini-3-Flash-Model-Card.pdf

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-14T01:10:44.920887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4455c564-06b2-442b-baa2-7df072181319 · outbound

This paper cites Embodied LLM Agents Learn to Cooperate in Organized Teams.

Who&When Pro: Can LLMs Really Attribute Failures in AI Agents? Embodied LLM Agents Learn to Cooperate in Organized Teams

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-14T01:10:44.920887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae8e2de7-947d-4731-9e6d-bede38093dff · outbound

This paper cites On the Resilience of LLM-Based Multi-Agent Collaboration with Faulty Agents.

Who&When Pro: Can LLMs Really Attribute Failures in AI Agents? On the Resilience of LLM-Based Multi-Agent Collaboration with Faulty Agents

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-14T01:10:44.920887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da449bee-e884-4fdd-b707-e378acb3a688 · outbound

This paper cites Meta-Harness: End-to-End Optimization of Model Harnesses.

Who&When Pro: Can LLMs Really Attribute Failures in AI Agents? Meta-Harness: End-to-End Optimization of Model Harnesses

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-14T01:10:44.920887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd95cdbd-83c2-431b-ade3-7686424afffd · outbound

This paper cites findings-emnlp.1034/.

Who&When Pro: Can LLMs Really Attribute Failures in AI Agents? findings-emnlp.1034/

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-14T01:10:44.920887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35c31bb6-3fc3-480d-8752-3271df6cf8c6 · outbound

This paper cites Lou, X., Lázaro-Gredilla, M., Dedieu, A., Wendelken, C., Lehrach, W., and Murphy, K.

Who&When Pro: Can LLMs Really Attribute Failures in AI Agents? Lou, X., Lázaro-Gredilla, M., Dedieu, A., Wendelken, C., Lehrach, W., and Murphy, K

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-14T01:10:44.920887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 61a90cac-ed41-46fc-aa9b-5af9f3628494 · outbound

This paper cites Madaan, A., Tandon, N., Gupta, P., Hallinan, S., Gao, L., Wiegreffe, S., Alon, U., Dziri, N., Prabhumoye, S., Yang, Y ., Gupta, S., Majumder, B.

Who&When Pro: Can LLMs Really Attribute Failures in AI Agents? Madaan, A., Tandon, N., Gupta, P., Hallinan, S., Gao, L., Wiegreffe, S., Alon, U., Dziri, N., Prabhumoye, S., Yang, Y ., Gupta, S., Majumder, B

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-14T01:10:44.920887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d47402d-b834-44af-ab7c-aef703465648 · outbound

This paper cites Majgaonkar, O., Fei, Z., Li, X., Sarro, F., and Ye, H.

Who&When Pro: Can LLMs Really Attribute Failures in AI Agents? Majgaonkar, O., Fei, Z., Li, X., Sarro, F., and Ye, H

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-14T01:10:44.920887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08b80f5d-42ce-4348-abbd-00fe849af7a1 · outbound

This paper cites Natural-Language Agent Harnesses.

Who&When Pro: Can LLMs Really Attribute Failures in AI Agents? Natural-Language Agent Harnesses

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-14T01:10:44.920887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16606b07-0faa-4607-a731-87aa5bd425a8 · outbound

This paper cites Adaptive In-conversation Team Building for Language Model Agents.

Who&When Pro: Can LLMs Really Attribute Failures in AI Agents? Adaptive In-conversation Team Building for Language Model Agents

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-14T01:10:44.920887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3848d9e0-501c-4d2c-9f73-946567e3b4e9 · outbound

This paper cites MathChat: Converse to Tackle Challenging Math Problems with LLM Agents.

Who&When Pro: Can LLMs Really Attribute Failures in AI Agents? MathChat: Converse to Tackle Challenging Math Problems with LLM Agents

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-14T01:10:44.920887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7765b077-bc27-4d35-bdc9-3db324f928ee · outbound

This paper cites Agentless: Demystifying LLM-based Software Engineering Agents.

Who&When Pro: Can LLMs Really Attribute Failures in AI Agents? Agentless: Demystifying LLM-based Software Engineering Agents

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-14T01:10:44.920887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b528198-cced-4cf0-9480-ec9bea17795a · outbound

This paper cites EmbodiedBench: Comprehensive Benchmarking Multi-modal Large Language Models for Vision-Driven Embodied Agents.

Who&When Pro: Can LLMs Really Attribute Failures in AI Agents? EmbodiedBench: Comprehensive Benchmarking Multi-modal Large Language Models for Vision-Driven Embodied Agents

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-14T01:10:44.920887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dfac289d-1975-4303-99b5-65a3f383bfdf · outbound

This paper cites ISBN 979-8-89176-251-0.

Who&When Pro: Can LLMs Really Attribute Failures in AI Agents? ISBN 979-8-89176-251-0

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-14T01:10:44.920887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation abbeee77-7f52-4789-bd8a-9db2600b312b · outbound

This paper cites CoEvoSkills: Self-Evolving Agent Skills via Co-Evolutionary Verification.

Who&When Pro: Can LLMs Really Attribute Failures in AI Agents? CoEvoSkills: Self-Evolving Agent Skills via Co-Evolutionary Verification

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-14T01:10:44.920887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86439ae0-89bc-400f-a082-5517cc5cdccc · outbound

This paper cites /tcg-pocket-october-2025-producer-letter) Obs:Official Release Date: October 30, 2024.Platform: iOS and Android.

Who&When Pro: Can LLMs Really Attribute Failures in AI Agents? /tcg-pocket-october-2025-producer-letter) Obs:Official Release Date: October 30, 2024.Platform: iOS and Android

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-14T01:10:44.920887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 21175121-e2bd-4590-87f9-df9ed6b26e6b · outbound

This paper cites Late October 2025.

Who&When Pro: Can LLMs Really Attribute Failures in AI Agents? Late October 2025

Reference 20

Resolution: malformed identifier; no resolver link, observed 2026-07-14T01:10:44.920887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f70f12f4-011a-4cb6-9108-2cccf59beaf9 · outbound

This paper cites Binary Search Protocol The binary search protocol bisects the transcript to narrow down the error location.

Who&When Pro: Can LLMs Really Attribute Failures in AI Agents? Binary Search Protocol The binary search protocol bisects the transcript to narrow down the error location

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-14T01:10:44.920887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2fcd05ef-1d24-444f-8ac6-e1a9f800a3ae · outbound

This paper cites an unresolved cited work.

Who&When Pro: Can LLMs Really Attribute Failures in AI Agents? Unresolved cited work

Reference 22

Resolution: parse uncertain; no resolver link, observed 2026-07-14T01:10:44.920887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad1936f8-10f3-4d0b-890e-a4e70ec9bf24 · outbound

This paper cites {{ query }}.

Who&When Pro: Can LLMs Really Attribute Failures in AI Agents? {{ query }}

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-14T01:10:44.920887Z

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Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.