Paper Citation Record · LEDGER

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory

As of 22 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2607.10608.

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

pith.paper-citation-record.v1
2607.10608 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-14T10:31:02.810248Z

measured 52 of 52 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 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

52 of 52 outbound references displayed

verified exact0
verified fuzzy0
unresolved51
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d343de12-e26f-4a57-86e8-ab7170028ea9 · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory Constitutional AI: Harmlessness from AI Feedback

Reference 1

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1c34473-2076-4317-a7de-634947aa33ad · outbound

This paper cites SeeClick: Harnessing GUI grounding for advanced visual GUI agents.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory SeeClick: Harnessing GUI grounding for advanced visual GUI agents

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16cd6749-89f8-4cb6-b66a-acbb1a8c6057 · outbound

This paper cites Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd22e900-b8c2-4598-9c4b-6313efa9ab07 · outbound

This paper cites Mind2Web: Towards a generalist agent for the web.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory Mind2Web: Towards a generalist agent for the web

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6989a99f-ddb0-4224-b236-80118a257691 · outbound

This paper cites The BrowserGym Ecosystem for Web Agent Research.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory The BrowserGym Ecosystem for Web Agent Research

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b5c108a-ea6d-4e0d-ae46-3973bcee984c · outbound

This paper cites WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks?.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks?

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 290d226f-7446-4518-aebb-011b8c716561 · outbound

This paper cites Gemma 3 Technical Report.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory Gemma 3 Technical Report

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e00c6d0e-25cf-4325-bb52-d476cdf17bad · outbound

This paper cites an unresolved cited work.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory Unresolved cited work

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01cd5a6c-5e93-4bc9-b68d-fd9da1497116 · outbound

This paper cites CUB: Benchmarking Context Utilisation Techniques for Language Models.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory CUB: Benchmarking Context Utilisation Techniques for Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ab43b90-f3b5-4b3d-b33a-b8b90045d086 · outbound

This paper cites WebV oyager: Building an end-to-end web agent with large multimodal models.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory WebV oyager: Building an end-to-end web agent with large multimodal models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca28ea42-f007-4c82-9101-7fd5dc8e1fe8 · outbound

This paper cites CogAgent: A visual language model for GUI agents.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory CogAgent: A visual language model for GUI agents

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17916939-9463-4894-89d4-3609336deeba · outbound

This paper cites Large language models cannot self-correct reasoning yet.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory Large language models cannot self-correct reasoning yet

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8fe5ef80-5cd6-4fde-b332-d02716503f2d · outbound

This paper cites RAP: Retrieval-Augmented Planning with Contextual Memory for Multimodal LLM Agents.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory RAP: Retrieval-Augmented Planning with Contextual Memory for Multimodal LLM Agents

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 980cb70c-1408-4fcd-93c5-d6f903e0b5fd · outbound

This paper cites When can LLMs actually correct their own mistakes? a critical survey of self-correction of LLMs.Transactions of the Association for Computational Linguistics, 12:1417–1440, 2024.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory When can LLMs actually correct their own mistakes? a critical survey of self-correction of LLMs.Transactions of the Association for Computational Linguistics, 12:1417–1440, 2024

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d0df050-bdb9-44a3-9c73-5e76f93ffc07 · outbound

This paper cites VisualWebArena: Evaluating multimodal agents on realistic visual web tasks.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory VisualWebArena: Evaluating multimodal agents on realistic visual web tasks

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3bfb633f-6b2f-4856-b168-8c1fd21eb558 · outbound

This paper cites Gonzalez, Hao Zhang, and Ion Stoica.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory Gonzalez, Hao Zhang, and Ion Stoica

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0d355c6-1928-46f8-9165-1b15ef404dfe · outbound

This paper cites Retrieval-augmented generation for knowledge-intensive NLP tasks.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory Retrieval-augmented generation for knowledge-intensive NLP tasks

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a547ca3-44b4-45ad-b46c-d33f1d21a619 · outbound

This paper cites WebSuite: Systematically evaluating why web agents fail.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory WebSuite: Systematically evaluating why web agents fail

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce9688a3-f76f-47e4-a421-224c3723eaf5 · outbound

This paper cites WebCoach: Self-evolving web agents with cross-session memory guidance.arXiv preprint arXiv:2511.12997, 2025.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory WebCoach: Self-evolving web agents with cross-session memory guidance.arXiv preprint arXiv:2511.12997, 2025

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 366c8ebf-c278-420b-8d79-a919500f78ce · outbound

This paper cites Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04642ce9-492a-4d93-a7d7-724be24a63d3 · outbound

This paper cites AgentBench: Evaluating LLMs as agents.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory AgentBench: Evaluating LLMs as agents

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f497035c-de75-4b9a-8d68-3772191e0eb9 · outbound

This paper cites AgentBoard: An analytical evaluation board of multi-turn LLM agents.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory AgentBoard: An analytical evaluation board of multi-turn LLM agents

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 922b3360-d7a7-4147-b4d6-cafb13a1a47d · outbound

This paper cites Self- refine: Iterative refinement with self-feedback.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory Self- refine: Iterative refinement with self-feedback

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8a147c1-335e-4f0e-a586-3b13e8173a93 · outbound

This paper cites WebGPT: Browser-assisted question-answering with human feedback.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory WebGPT: Browser-assisted question-answering with human feedback

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe36e07d-abf0-4a2f-a731-e821900355d2 · outbound

This paper cites an unresolved cited work.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory Unresolved cited work

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95dfaee9-89a8-4728-87df-2d7668456a2c · outbound

This paper cites Patil, Ion Stoica, and Joseph E.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory Patil, Ion Stoica, and Joseph E

Reference 26

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 809b9c33-ee84-4f71-b5ef-f314420fbf8d · outbound

This paper cites O’Brien, Carrie J.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory O’Brien, Carrie J

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e73e2cc7-779c-414b-b7c1-7b9f3884738a · outbound

This paper cites Bowman, Amanda Askell, Roger Grosse, Danny Hernandez, Deep Ganguli, Evan Hubinger, Nicholas Schiefer, and Jared Kaplan.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory Bowman, Amanda Askell, Roger Grosse, Danny Hernandez, Deep Ganguli, Evan Hubinger, Nicholas Schiefer, and Jared Kaplan

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f409016-a6dc-4347-a768-5d2139ed27fc · outbound

This paper cites Bowman, Esin Durmus, Zac Hatfield-Dodds, Scott R.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory Bowman, Esin Durmus, Zac Hatfield-Dodds, Scott R

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 944e7d9d-7fda-4fbc-8336-5467ab0cb499 · outbound

This paper cites World of bits: An open-domain platform for web-based agents.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory World of bits: An open-domain platform for web-based agents

Reference 30

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0fd08884-5c6b-42c5-95aa-3e242dfb46b8 · outbound

This paper cites Reflexion: Language agents with verbal reinforcement learning.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory Reflexion: Language agents with verbal reinforcement learning

Reference 31

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36902401-4b39-4615-b738-7ea41b090cf2 · outbound

This paper cites Voyager: An Open-Ended Embodied Agent with Large Language Models.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory Voyager: An Open-Ended Embodied Agent with Large Language Models

Reference 32

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 483827ad-f307-404b-86aa-1e2cb87cbcf2 · outbound

This paper cites A survey on large language model based autonomous agents.Frontiers of Computer Science, 18(6), 2024.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory A survey on large language model based autonomous agents.Frontiers of Computer Science, 18(6), 2024

Reference 33

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bddda448-c45f-40f7-8ea5-b3988d7f3637 · outbound

This paper cites Le, Ed H.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory Le, Ed H

Reference 34

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 607cc7f9-8c69-429b-bbb5-57f2ff3b5ec7 · outbound

This paper cites Agent workflow memory.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory Agent workflow memory

Reference 35

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 050145c0-3401-425c-89aa-9046c9007aea · outbound

This paper cites Chi, Quoc V.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory Chi, Quoc V

Reference 36

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03929c5a-94c3-4eae-bf21-ed17a9159d44 · outbound

This paper cites Simple synthetic data reduces sycophancy in large language models.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory Simple synthetic data reduces sycophancy in large language models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd2530dc-e705-429b-b84e-35291df854a0 · outbound

This paper cites The Rise and Potential of Large Language Model Based Agents: A Survey.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory The Rise and Potential of Large Language Model Based Agents: A Survey

Reference 38

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fbe40255-65b5-409d-b6ad-f72330fce4ee · outbound

This paper cites OSWorld: Benchmarking multimodal agents for open-ended tasks in real computer environments.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory OSWorld: Benchmarking multimodal agents for open-ended tasks in real computer environments

Reference 39

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75ffb17e-2eb6-4dc7-b57b-3f1d547450fc · outbound

This paper cites How memory management impacts LLM agents: An empirical study of experience-following behavior.arXiv preprint arXiv:2505.16067, 2025.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory How memory management impacts LLM agents: An empirical study of experience-following behavior.arXiv preprint arXiv:2505.16067, 2025

Reference 40

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba1d8b89-cec9-4c7e-b951-2cb12bf77938 · outbound

This paper cites TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks

Reference 41

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d95cd46-61dd-4b93-a43c-64a1f6388982 · outbound

This paper cites Knowledge conflicts for LLMs: A survey.Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory Knowledge conflicts for LLMs: A survey.Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024

Reference 42

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2685a08d-7d8b-48ba-8dbb-e44b7c4247c7 · outbound

This paper cites A-MEM: Agentic Memory for LLM Agents.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory A-MEM: Agentic Memory for LLM Agents

Reference 43

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc0e0e60-d4a2-4721-8bc7-64e7c2dfa392 · outbound

This paper cites Qwen3 Technical Report.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory Qwen3 Technical Report

Reference 44

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65c4266c-94fb-4f9d-9606-2b18336ce7ce · outbound

This paper cites Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V

Reference 45

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6eebf245-82df-40b4-98a0-fea4b861226a · outbound

This paper cites WebShop: Towards scalable real-world web interaction with grounded language agents.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory WebShop: Towards scalable real-world web interaction with grounded language agents

Reference 46

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5a8fd4e-cd5e-4f8b-997e-31b95bdf9a94 · outbound

This paper cites Griffiths, Yuan Cao, and Karthik Narasimhan.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory Griffiths, Yuan Cao, and Karthik Narasimhan

Reference 47

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98db593c-804c-4985-bd48-78bb804b4c9f · outbound

This paper cites ReAct: Synergizing reasoning and acting in language models.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory ReAct: Synergizing reasoning and acting in language models

Reference 48

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f533dc0-59db-42b5-a021-31272967988c · outbound

This paper cites ExpeL: LLM agents are experiential learners.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory ExpeL: LLM agents are experiential learners

Reference 49

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f1fb9c24-83f5-4cbc-be41-b2f7a4b5c93a · outbound

This paper cites GPT-4V(ision) is a generalist web agent, if grounded.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory GPT-4V(ision) is a generalist web agent, if grounded

Reference 50

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 119106ee-04c8-438c-a19f-6ef5b21bd9a7 · outbound

This paper cites MemoryBank: Enhancing large language models with long-term memory.Proceedings of the AAAI Conference on Artificial Intelligence, 2024.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory MemoryBank: Enhancing large language models with long-term memory.Proceedings of the AAAI Conference on Artificial Intelligence, 2024

Reference 51

Resolution: unresolved; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f24e2ebd-80ae-4727-bbe7-e28b6f254667 · outbound

This paper cites Write a Review.

The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory Write a Review

Reference 52

Resolution: malformed identifier; no resolver link, observed 2026-07-14T10:31:02.810248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.