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Paper Citation Record · LEDGER

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback

As of 18 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 1 inbound Pith citation observation for arXiv:2506.02298.

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

pith.paper-citation-record.v1
2506.02298 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:30:57.048733Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:45:59.767986Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-06T16:46:03.964361Z

Reference resolution

30 of 30 outbound references displayed

  • verified exact0
  • verified fuzzy1
  • unresolved29
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 784323fb-bcbd-4a17-83bc-97e9da8aa4fc · outbound

This paper cites GPT-4 Technical Report.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback GPT-4 Technical Report

Reference 1

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no resolver link, observed 2026-08-07T11:30:54.759555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:54.759555Z digest=sha256:597a7c101204a0b503fa132a87516d08a4d48d41af990b5acc4d91a84f262ce4

Observation 3856173b-3022-4920-b467-67c7b4a97525 · outbound

This paper cites an unresolved cited work.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback Unresolved cited work

Reference 2

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no resolver link, observed 2026-08-07T11:30:54.810276Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:54.810276Z digest=sha256:3c1a5d2359fd984fc20f9b5cc93dff2960502f45611a667cfc8f7d4278c300d8

Observation 7722ca1e-4be8-49b1-b8d0-65aaa2cb1e06 · outbound

This paper cites FireAct: Toward Language Agent Fine-tuning.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback FireAct: Toward Language Agent Fine-tuning

Reference 3

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source=arxiv_source observed=2026-08-07T11:30:54.902423Z digest=sha256:fae011799a243a0362a0492ca1250ba96872e43b8121d3e8b6f4828e057b35b6

Observation 5424dcfb-a1fc-4f34-8475-3f14546a082b · outbound

This paper cites The Llama 3 Herd of Models.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback The Llama 3 Herd of Models

Reference 4

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no resolver link, observed 2026-08-07T11:30:54.978221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:54.978221Z digest=sha256:83e6e309f6f3afdfaf294f607f5a591c79cb1189f3364ad482c758fac3bfcc3c

Observation b124154d-4a45-4a0c-99f7-8696387b869d · outbound

This paper cites ToolTalk: Evaluating Tool-Usage in a Conversational Setting.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback ToolTalk: Evaluating Tool-Usage in a Conversational Setting

Reference 5

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no resolver link, observed 2026-08-07T11:30:55.058714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:55.058714Z digest=sha256:7c22e6774ad241f12a2ac212849978ff86fa2770dd38a1802f9a373894cd3fb2

Observation 67f1e5c9-5bc6-452e-b189-7713f76606e3 · outbound

This paper cites an unresolved cited work.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback Unresolved cited work

Reference 6

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raw_fallback, observed 2026-08-07T11:30:58.475493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T11:30:55.152532Z digest=sha256:3fea1eba22a08e11f0e3a04bb6ef525825322a28de22503d4384f7d9545ac3ec

Observation 23cb4f08-1b04-48a3-9c2d-2262cb79a598 · outbound

This paper cites Mixtral of Experts.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback Mixtral of Experts

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:55.239784Z digest=sha256:614b25ab23b27e9fbe47147bfd47560367a5b56013aad39e15770ae207759599

Observation 9da97f14-6dec-49f7-8e6b-b925afd3ce4a · outbound

This paper cites ToolScan: A Benchmark for Characterizing Errors in Tool-Use LLMs.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback ToolScan: A Benchmark for Characterizing Errors in Tool-Use LLMs

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:55.307859Z digest=sha256:55647478541c35d6ba311be58e7cd0a162ccaf44645e91aefb66b8f17986a0f3

Observation f72839fa-1d8f-4c98-b8b6-028e3ec1722f · outbound

This paper cites AgentBench: Evaluating LLMs as Agents.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback AgentBench: Evaluating LLMs as Agents

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:55.404623Z digest=sha256:373cc15a2b18b00fa5a0be123fab9d2deabbf8f59854858ca07cf12c0f176532

Observation 57c884b9-c144-4f9b-965c-25e88c647e55 · outbound

This paper cites AgentLite: A Lightweight Library for Building and Advancing Task-Oriented LLM Agent System.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback AgentLite: A Lightweight Library for Building and Advancing Task-Oriented LLM Agent System

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:55.494458Z digest=sha256:cba39ad518a11306d29bcd97968bf5e7ed26114ae8ff40b300be65b1b2e62c15

Observation 0033256e-4c6a-44d5-84b0-8f3f55f264d8 · outbound

This paper cites an unresolved cited work.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback Unresolved cited work

Reference 11

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raw_fallback, observed 2026-08-07T11:30:58.236604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 07df1bbd-0184-437d-ac61-5330f2269e25 · outbound

This paper cites AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:55.654047Z digest=sha256:cc61c67024315ee6204be47127d2be5c6db00cb28bd25d7cf547fcf44340c785

Observation a6b2997e-2852-4a30-b082-e3494ea93b59 · outbound

This paper cites an unresolved cited work.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback Unresolved cited work

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:55.726969Z digest=sha256:4b818a58ace274d981b3dd42734e091da463445bbeab2655e646f7eccebd107a

Observation e1509e81-cb5b-4906-b6aa-ad0eb7cb1fd3 · outbound

This paper cites an unresolved cited work.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback Unresolved cited work

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:55.820959Z digest=sha256:36e59b54c83d2d670746d51f0557c5249b98a0769e0785ef8867cd5ea355ce63

Observation 53a71b66-ade2-484c-a333-c54d6e689ae1 · outbound

This paper cites ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:55.882646Z digest=sha256:da32f9d72f4f10f15c73b4e50caeb221ad228d712308e934e2cedd689c70f09c

Observation 7be69043-74e1-4d4b-9984-ba1366878922 · outbound

This paper cites an unresolved cited work.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback Unresolved cited work

Reference 16

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:55.960177Z digest=sha256:3c0881f908f6e4f6f7d2ffa5517d31b1432ed31e6db9d0f5bd94cc6b6e09947a

Observation 19867723-796a-4262-b848-43cf24b3e5e8 · outbound

This paper cites Trial and Error: Exploration-Based Trajectory Optimization for LLM Agents.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback Trial and Error: Exploration-Based Trajectory Optimization for LLM Agents

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:56.040940Z digest=sha256:44ce425fb87ca68bb74092603b276eeae77474d59891f0462aef441d7a19af67

Observation 82ce7764-72c6-4eba-b8f9-e75bc4f81d44 · outbound

This paper cites Learn-by-interact: A Data-Centric Framework for Self-Adaptive Agents in Realistic Environments.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback Learn-by-interact: A Data-Centric Framework for Self-Adaptive Agents in Realistic Environments

Reference 18

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source=arxiv_source observed=2026-08-07T11:30:56.118004Z digest=sha256:c8326a1e49657d9ae408ea50f3166c66b85595fe28ad341eebd8b1cc03cab1fc

Observation 6aa6d5e7-af23-4734-a2bf-b0c769644d38 · outbound

This paper cites an unresolved cited work.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback Unresolved cited work

Reference 19

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:56.192550Z digest=sha256:8c4078b0933eba5f85f1b23b711de2874526bafda7d874df42aeb415805f61a6

Observation ba39a1fd-be63-4687-abeb-baa85f06085d · outbound

This paper cites OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:56.287971Z digest=sha256:8b8aff68b58584b14c5283bb24df404acba64e5394cc68b897bcee113e4f4a21

Observation e63821cd-ced6-402c-89ee-9737b051f880 · outbound

This paper cites an unresolved cited work.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback Unresolved cited work

Reference 21

Resolution
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raw_fallback, observed 2026-08-07T11:30:57.896383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T11:30:56.369516Z digest=sha256:ae6c9347989ceec8d3880bfd123e99e21a641e3965406a1c7dad783c1e1f3b90

Observation 5bb1e9e3-be8d-4c99-b788-d47dc6d59e0a · outbound

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

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback Patil, Ion Stoica, and Joseph E

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:30:57.750331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T11:30:56.474114Z digest=sha256:99cc80afb8cc42b700782247b55b837d38135423fb9de65c76b8b6eab10aca25

Observation f24f8c81-bc38-4130-9d76-e8d7303ecdda · outbound

This paper cites $\tau$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback $\tau$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains

Reference 23

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:56.554440Z digest=sha256:34c6a990f49f36978ec6566072705218abaa820370a2d31491ae20c3ca3fc9b1

Observation 17537d2f-6127-43fb-9c65-0315d93d996b · outbound

This paper cites an unresolved cited work.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback Unresolved cited work

Reference 24

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no resolver link, observed 2026-08-07T11:30:56.611814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:56.611814Z digest=sha256:8473fecc9f925bf8414aa19185ef38aa5139c625d42c7ffd920a3a2e7869a9b7

Observation 17d6f05d-44d4-4250-8ca1-a25226fcd2c9 · outbound

This paper cites ActionStudio: A Lightweight Framework for Data and Training of Large Action Models.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback ActionStudio: A Lightweight Framework for Data and Training of Large Action Models

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T11:30:56.700112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:56.700112Z digest=sha256:660d533af224c496ee4c69eab4f2f2e6b16bb44e0a740b0da993a58ca2626b27

Observation 8b37857e-8851-413d-87d0-9aa357bf5ecf · outbound

This paper cites AgentOhana: Design Unified Data and Training Pipeline for Effective Agent Learning.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback AgentOhana: Design Unified Data and Training Pipeline for Effective Agent Learning

Reference 26

Resolution
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no resolver link, observed 2026-08-07T11:30:56.761441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:56.761441Z digest=sha256:3e7a211d7e26effa1893d79a27d3e56c0c26243cc7e2f460e21ad107306570d4

Observation 903d018c-e11c-4446-9e6b-614dd46ea320 · outbound

This paper cites xLAM: A Family of Large Action Models to Empower AI Agent Systems.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback xLAM: A Family of Large Action Models to Empower AI Agent Systems

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T11:30:56.817155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:56.817155Z digest=sha256:4964c9130ff441296637a5c5840d46a47e60616fdbd793b16987f752801b0eb2

Observation f80f2062-b766-4401-9e76-ef9e5998702d · outbound

This paper cites WebArena: A Realistic Web Environment for Building Autonomous Agents.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback WebArena: A Realistic Web Environment for Building Autonomous Agents

Reference 28

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unresolved
no resolver link, observed 2026-08-07T11:30:56.886944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:56.886944Z digest=sha256:d6dba43f80f5e86ab08afe76a4934d2e484807952f4d481c0eb1481382f88d68

Observation a894b1dc-9508-4ff3-b46f-74929a17e9c9 · outbound

This paper cites online" 'onlinestring :=.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback online" 'onlinestring :=

Reference 29

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unresolved
no resolver link, observed 2026-08-07T11:30:56.979211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:56.979211Z digest=sha256:3ceb05b44e399de83c360a9bbb98548b407a0266a781e24fc6d867f7d2ab6bce

Observation 89235b0e-808b-44b9-99b6-4ddb72295c6a · outbound

This paper cites write newline.

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback write newline

Reference 30

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unresolved
no resolver link, observed 2026-08-07T11:30:57.048733Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:57.048733Z digest=sha256:321b4ceb140d3eb72ad3fced641ab37a03deeefbfdf8655e8ce35c10ea6b6cbe

Pith citing papers

Observation a05bf665-2307-4f98-84fe-e0c110d1fff4 · inbound

MCPEval: Automatic MCP-based Deep Evaluation for AI Agent Models cites this paper.

MCPEval: Automatic MCP-based Deep Evaluation for AI Agent Models LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback

Reference 12

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verified exact
local_arxiv, observed 2026-08-06T16:46:04.002763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T16:45:59.767986Z digest=sha256:e174acd5d8847ce902f3ed976f7216b5085ab9ecf12d756198364cf3dad5ddef