A Comprehensive Study of Implementation Bugs in Multi-modal Agents | Paper Citation Record

Observation 8f0f7e36-4143-4acb-a312-b134b64a09b4 · outbound

This paper cites MARS: toward more eﬀicient multi-agent collaboration for LLM reasoning,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents MARS: toward more eﬀicient multi-agent collaboration for LLM reasoning,

Reference 1

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Observation e3a3f973-2cdd-43a7-8c98-408ab8cbdce7 · outbound

This paper cites Agentic reasoning: A streamlined framework for enhancing LLM reasoning with agentic tools,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Agentic reasoning: A streamlined framework for enhancing LLM reasoning with agentic tools,

Reference 2

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Observation f9670a87-8967-49b8-9959-47f6a599400c · outbound

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

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Agentless: Demystifying LLM-based Software Engineering Agents

Reference 3

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Observation 66712ed1-fce7-427d-b942-dcd4e8bc84eb · outbound

This paper cites Au- tocoderover: Autonomous program improvement,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Au- tocoderover: Autonomous program improvement,

Reference 4

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Observation b35d3def-a816-4c9f-9dbb-5dd4aa0adabe · outbound

This paper cites Openhands: An open platform for AI software developers as generalist agents,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Openhands: An open platform for AI software developers as generalist agents,

Reference 5

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Observation a2b5a9bc-c48b-4c68-9ece-16febb62b916 · outbound

This paper cites Interactive Agents: Simulating Counselor-Client Psychological Counseling via Role-Playing LLM-to-LLM Interactions.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Interactive Agents: Simulating Counselor-Client Psychological Counseling via Role-Playing LLM-to-LLM Interactions

Reference 6

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Observation 31fd7824-496d-4a0f-9e24-636907d9aede · outbound

This paper cites GPT-Driver: Learning to Drive with GPT.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents GPT-Driver: Learning to Drive with GPT

Reference 7

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Observation 506810c6-068d-4d4d-ac28-56ff195573b5 · outbound

This paper cites Drive like a human: Rethinking autonomous driving with large language models,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Drive like a human: Rethinking autonomous driving with large language models,

Reference 8

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Observation 7f97823f-4bd8-48f0-aaec-9b1c21057eed · outbound

This paper cites On the Road with GPT-4V(ision): Early Explorations of Visual-Language Model on Autonomous Driving.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents On the Road with GPT-4V(ision): Early Explorations of Visual-Language Model on Autonomous Driving

Reference 9

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Observation 52155cf8-2c7c-4e20-a125-1cb2b1977808 · outbound

This paper cites MP5: A multi-modal open-ended embodied system in minecraft via active perception,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents MP5: A multi-modal open-ended embodied system in minecraft via active perception,

Reference 10

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Observation 5405b8b9-5861-4451-9ab7-984d176c8a76 · outbound

This paper cites JAR VIS-1: open- world multi-task agents with memory-augmented multimodal language models,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents JAR VIS-1: open- world multi-task agents with memory-augmented multimodal language models,

Reference 11

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Observation 1335a719-6ab0-4712-8b26-e5690532dd0f · outbound

This paper cites Embodied multi-modal agent trained by an LLM from a parallel textworld,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Embodied multi-modal agent trained by an LLM from a parallel textworld,

Reference 12

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Observation 67fd4373-11be-46ef-aa67-fa188f970de0 · outbound

This paper cites Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task Agents.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task Agents

Reference 13

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Observation 12c60fe1-691c-444c-9c38-7c5c9c2b3e6f · outbound

This paper cites Webwise: Unlocking web interface control for llms via sequential exploration,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Webwise: Unlocking web interface control for llms via sequential exploration,

Reference 14

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Observation 62e69a25-5de6-4379-a507-7bac69b372f8 · outbound

This paper cites AutoDroid: LLM-powered Task Automation in Android.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents AutoDroid: LLM-powered Task Automation in Android

Reference 15

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Observation 371fd33c-1012-40a5-9904-19bbd25c4142 · outbound

This paper cites GPT-4V in Wonderland: Large Multimodal Models for Zero-Shot Smartphone GUI Navigation.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents GPT-4V in Wonderland: Large Multimodal Models for Zero-Shot Smartphone GUI Navigation

Reference 16

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Observation 9331f783-6026-475a-85e8-f4b4c52aea9c · outbound

This paper cites You only look at screens: Multimodal chain-of-action agents,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents You only look at screens: Multimodal chain-of-action agents,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-11T10:41:33.954036Z

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Observation bf6d669d-1fbd-48ec-9da3-8c41612349b6 · outbound

This paper cites Collision between vehicle controlled by developmental automated driving system and pedestrian,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Collision between vehicle controlled by developmental automated driving system and pedestrian,

Reference 18

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Observation 24606737-970d-4939-93e7-deb25a7c63d5 · outbound

This paper cites Microsoft’s ai agent spends 100% of its testing funds on online fraud—lessons for msft and ai-secured transactions.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Microsoft’s ai agent spends 100% of its testing funds on online fraud—lessons for msft and ai-secured transactions

Reference 19

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Observation 1c69e99b-e31b-434d-8bd6-c09b6f61d355 · outbound

This paper cites Chatgpt agent exposes vulnerability, potentially al- lowing “shadow leak.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Chatgpt agent exposes vulnerability, potentially al- lowing “shadow leak

Reference 20

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Observation 63595d95-1cf0-4faf-a3eb-c00e785de562 · outbound

This paper cites Security debt in llm agent applications: A measurement study of vulnerabilities andmitigation trade-offs,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Security debt in llm agent applications: A measurement study of vulnerabilities andmitigation trade-offs,

Reference 21

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Observation c52e18e5-89d6-4526-8a8e-2a058555a8da · outbound

This paper cites Eu- agent-bench: Measuring illegal behavior of LLM agents under EU law,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Eu- agent-bench: Measuring illegal behavior of LLM agents under EU law,

Reference 22

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Observation 044fb42a-54c3-4439-bd51-8977817b350c · outbound

This paper cites Can agents fix agent issues?.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Can agents fix agent issues?

Reference 23

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Observation a960a2a7-f90e-4b6b-b11f-bb6802eebbf8 · outbound

This paper cites Where LLM agents fail and how they can learn from failures,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Where LLM agents fail and how they can learn from failures,

Reference 24

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Observation 4c98062c-cc03-4ee8-b1cf-f2cb4e182a60 · outbound

This paper cites Understanding software engineering agents: A study of thought-action-result trajectories,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Understanding software engineering agents: A study of thought-action-result trajectories,

Reference 25

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Observation 48cdf4ec-d62c-4dd6-be74-3d4a8525d164 · outbound

This paper cites Understanding Automated Program Repair Agents Through the Lens of Traceability: An Empirical Study.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Understanding Automated Program Repair Agents Through the Lens of Traceability: An Empirical Study

Reference 26

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Observation bdf7d7dd-97bd-4548-9add-ce33fcfe22eb · outbound

This paper cites Exploring autonomous agents: A closer look at why they fail when completing tasks,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Exploring autonomous agents: A closer look at why they fail when completing tasks,

Reference 27

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Observation 11b33f00-f64a-4468-921b-1f02e64faa29 · outbound

This paper cites SafeSearch: Automated Red-Teaming of LLM-Based Search Agents.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents SafeSearch: Automated Red-Teaming of LLM-Based Search Agents

Reference 28

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Observation a56b285e-e048-45c7-9830-be3c609ef3bd · outbound

This paper cites Why Do Multi-Agent LLM Systems Fail?.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Why Do Multi-Agent LLM Systems Fail?

Reference 29

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Observation 50752fba-2576-49da-bfd3-52c6c730a3b0 · outbound

This paper cites Diagnosing failure root causes in platform-orchestrated agentic systems: Dataset, taxonomy, and benchmark,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Diagnosing failure root causes in platform-orchestrated agentic systems: Dataset, taxonomy, and benchmark,

Reference 30

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Observation 260ad4bc-e197-4cd7-86f6-40fdef60b238 · outbound

This paper cites Large Multimodal Agents: A Survey.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Large Multimodal Agents: A Survey

Reference 31

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Observation d42ca417-eb0e-405d-a573-bb70d2c78327 · outbound

This paper cites Large language model for verilog code generation: Literature review and the road ahead,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Large language model for verilog code generation: Literature review and the road ahead,

Reference 32

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Observation 263a4b34-d26c-49a6-8a71-fd826b4c62ee · outbound

This paper cites Identifying relevant studies in software engineering,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Identifying relevant studies in software engineering,

Reference 33

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Observation 5254d7b8-b47e-49ec-8ddb-0f350eadfec6 · outbound

This paper cites Guidelines for snowballing in systematic literature studies and a replication in software engineering,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Guidelines for snowballing in systematic literature studies and a replication in software engineering,

Reference 34

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Observation 1ffd2ac0-2a66-43ed-ab1d-42d79d2c8bac · outbound

This paper cites A comprehensive study of autonomous vehicle bugs,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents A comprehensive study of autonomous vehicle bugs,

Reference 35

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Observation f5769b8c-703f-4d2e-bb40-a07a0ab6daad · outbound

This paper cites Faults in deep reinforcement learning programs: a taxonomy and a detection approach,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Faults in deep reinforcement learning programs: a taxonomy and a detection approach,

Reference 36

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Observation ff2ff986-9d13-4c51-8f10-0075bad99bb4 · outbound

This paper cites A comprehensive study of deep learning compiler bugs,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents A comprehensive study of deep learning compiler bugs,

Reference 37

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Observation ce0376f0-5f4b-454a-8795-5a569f6d2d19 · outbound

This paper cites Catiss: An intelligent tool for categorizing issues re- ports using transformers,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Catiss: An intelligent tool for categorizing issues re- ports using transformers,

Reference 38

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Observation 246ea148-9c06-4ed0-85bd-eece2e8590ce · outbound

This paper cites Analysis and detection of information types of open source software issue discussions,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Analysis and detection of information types of open source software issue discussions,

Reference 39

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Observation 076ab9e2-2bb4-4632-b967-38d3694e84e5 · outbound

This paper cites Bug characteristics in open source software,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Bug characteristics in open source software,

Reference 40

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Observation 35868528-347e-4fea-9e07-82a1132f5a57 · outbound

This paper cites Cohen’s kappa coeﬀicient as a performance measure for feature selection,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Cohen’s kappa coeﬀicient as a performance measure for feature selection,

Reference 41

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Observation d09dab8a-1887-4426-94d6-6055c417098c · outbound

This paper cites CCFQA: A benchmark for cross-lingual and cross- modal speech and text factuality evaluation,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents CCFQA: A benchmark for cross-lingual and cross- modal speech and text factuality evaluation,

Reference 42

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Observation 6609a772-7c84-41f6-bd89-673a498deee9 · outbound

This paper cites Matester.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Matester

Reference 43

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Observation cac71897-47e6-46f2-a389-fefc34f488ad · outbound

This paper cites Appagent: Multimodal agents as smartphone users,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Appagent: Multimodal agents as smartphone users,

Reference 44

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Observation 31d1f995-d905-4cbf-800b-3ede6564f241 · outbound

This paper cites DroidBot-GPT: GPT-powered UI Automation for Android.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents DroidBot-GPT: GPT-powered UI Automation for Android

Reference 45

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Observation f28a6a95-cc69-48b8-9aa0-3d3338680798 · outbound

This paper cites Mobilegpt: Augmenting LLM with human-like app memory for mobile task automation,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Mobilegpt: Augmenting LLM with human-like app memory for mobile task automation,

Reference 46

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Observation 79c35e9d-a35e-423d-bc09-1b69f2c796ff · outbound

This paper cites ASSISTGUI: Task-Oriented Desktop Graphical User Interface Automation.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents ASSISTGUI: Task-Oriented Desktop Graphical User Interface Automation

Reference 47

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Observation 5f66734e-2b27-495c-9cfe-fb6d953a10d1 · outbound

This paper cites Browsing like human: A multimodal web agent with experien- tial fast-and-slow thinking,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Browsing like human: A multimodal web agent with experien- tial fast-and-slow thinking,

Reference 48

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Observation ecf703b3-f86f-4838-9456-4f428aae7cdd · outbound

This paper cites Octopus: Embodied vision-language programmer from environmental feedback,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Octopus: Embodied vision-language programmer from environmental feedback,

Reference 49

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Observation 3e492c2d-bdfd-43d5-96ef-53f709d77063 · outbound

This paper cites See and think: Embodied agent in virtual environment,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents See and think: Embodied agent in virtual environment,

Reference 50

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Observation 8b49a3cc-2217-40e7-8226-e6e2e79ffc8c · outbound

This paper cites Open-world planning via lifted regression with llm-inferred affordances for embodied agents,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Open-world planning via lifted regression with llm-inferred affordances for embodied agents,

Reference 51

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Observation 22576506-450a-448f-94dc-d2ae73cef06d · outbound

This paper cites Citynavagent: Aerial vision-and- language navigation with hierarchical semantic planning and global memory,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Citynavagent: Aerial vision-and- language navigation with hierarchical semantic planning and global memory,

Reference 52

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Observation 49d177c1-d310-4a85-a1c9-03cfcff5b6f4 · outbound

This paper cites RILA: reflective and imaginative language agent for zero-shot semantic audio-visual navigation,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents RILA: reflective and imaginative language agent for zero-shot semantic audio-visual navigation,

Reference 53

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Observation 9d9f1967-9619-4e5d-b923-c34257ae8a5a · outbound

This paper cites LLaVA-Interactive: An All-in-One Demo for Image Chat, Segmentation, Generation and Editing.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents LLaVA-Interactive: An All-in-One Demo for Image Chat, Segmentation, Generation and Editing

Reference 54

Resolution: unresolved; no resolver link, observed 2026-07-11T10:41:33.954036Z

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Observation 746377dd-ed62-4931-93ce-2d2f922096ca · outbound

This paper cites Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation Models.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation Models

Reference 55

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Observation 7af3603d-494f-4f1c-bd01-db6bec3a32f0 · outbound

This paper cites Genartist: Multimodal LLM as an agent for unified image generation and editing,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Genartist: Multimodal LLM as an agent for unified image generation and editing,

Reference 56

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Observation fd0920c3-ab5a-44c6-89b2-04731b33e30d · outbound

This paper cites Loop Copilot: Conducting AI Ensembles for Music Generation and Iterative Editing.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Loop Copilot: Conducting AI Ensembles for Music Generation and Iterative Editing

Reference 57

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Observation 8e2f2a50-6a1d-47d8-8b6e-549dd9fdec0f · outbound

This paper cites Musicagent: An AI agent for music understanding and generation with large language models,.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents Musicagent: An AI agent for music understanding and generation with large language models,

Reference 58

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Observation ca2d2db1-2031-469e-87e7-bc8d8cb18bea · outbound

This paper cites WavJourney: Compositional Audio Creation with Large Language Models.

A Comprehensive Study of Implementation Bugs in Multi-modal Agents WavJourney: Compositional Audio Creation with Large Language Models

Reference 59

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