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Paper Citation Record · LEDGER

OpenAGI: When LLM Meets Domain Experts

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2304.04370.

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

pith.paper-citation-record.v1
2304.04370 v6

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T18:34:13.131422Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

76
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 8bb57ac0-e361-4108-806c-4031807235fb · inbound

LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model cites this paper.

LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model OpenAGI: When LLM Meets Domain Experts

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-15T08:41:04.833789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T08:41:04.743886Z digest=sha256:c50a117684c44d976a5f365f3df9678424e3ed3cbec62e84c4d87b5048e0cb53

Observation c75114b5-a65c-4fe9-bc01-89f8735f8832 · inbound

Mind2Web: Towards a Generalist Agent for the Web cites this paper.

Mind2Web: Towards a Generalist Agent for the Web OpenAGI: When LLM Meets Domain Experts

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-15T20:05:16.222771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T20:05:15.992207Z digest=sha256:723d1f621b637814960fc4c2e4ea4d9cc5b299604bd2b960e22f86cd23e09506

Observation 8385fa71-353c-4e23-a367-f1f51cbc518f · inbound

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

The Rise and Potential of Large Language Model Based Agents: A Survey OpenAGI: When LLM Meets Domain Experts

Reference 212

Resolution
verified exact
arxiv_id, observed 2026-05-11T10:47:47.828071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-11T10:47:44.152066Z digest=sha256:4f460a3c534ba3fdad4654d5ba9dcc731ff30a42027166876c0fc63fa1f2aeef

Observation e44c9970-b78e-4cd3-9036-c4345c4fea9a · inbound

MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI cites this paper.

MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI OpenAGI: When LLM Meets Domain Experts

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-15T05:37:41.645563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T05:37:41.401736Z digest=sha256:f375e2cda52f658af94b11081c31afe2fa8178a1b6779fa2ca6a2284d040e0ef

Observation 274b802c-92c4-4231-aa26-e1274c7f6fd3 · inbound

VocalCrypt: Novel Active Defense Against Deepfake Voice Based on Masking Effect cites this paper.

VocalCrypt: Novel Active Defense Against Deepfake Voice Based on Masking Effect OpenAGI: When LLM Meets Domain Experts

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-07T18:34:13.131422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T18:34:13.131422Z digest=sha256:8c02a7ffb446b03cc495a382f4b338fb416298150a2a1424fa6d53be2b3d9146

Observation 69576767-6a51-4a02-ad25-12840a615fd9 · inbound

ORFS-agent: Tool-Using Agents for Chip Design Optimization cites this paper.

ORFS-agent: Tool-Using Agents for Chip Design Optimization OpenAGI: When LLM Meets Domain Experts

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-19T11:27:16.156104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-19T11:23:29.010807Z digest=sha256:c66294dacbf80daeaa9bdd8417284b2600f3711fe874cd3b3f2d0df2326f8693

Observation 3900cef5-523c-42da-a6af-0a85bf44899c · inbound

Error Reflection Prompting: Can Large Language Models Successfully Understand Errors? cites this paper.

Error Reflection Prompting: Can Large Language Models Successfully Understand Errors? OpenAGI: When LLM Meets Domain Experts

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-05T17:14:15.058933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:14:15.058933Z digest=sha256:773f9bfb11a9057db4c17c8a60ce068cc1fb84a23e93bfda09d74e6eaddc5077

Observation d5b38302-8193-4914-bf59-266d4451455b · inbound

IoT-Brain: Grounding LLMs for Semantic-Spatial Sensor Scheduling cites this paper.

IoT-Brain: Grounding LLMs for Semantic-Spatial Sensor Scheduling OpenAGI: When LLM Meets Domain Experts

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-11T06:05:56.848279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T17:49:16.409834Z digest=sha256:2d105d8e2408e1d91af0ce391fb3a8199d4888145967997b4bc0abe9c6ab3b6c

Observation e9b82573-1226-4fc5-94bb-27285920ddfa · inbound

OPT-BENCH: Evaluating the Iterative Self-Optimization of LLM Agents in Large-Scale Search Spaces cites this paper.

OPT-BENCH: Evaluating the Iterative Self-Optimization of LLM Agents in Large-Scale Search Spaces OpenAGI: When LLM Meets Domain Experts

Reference 98

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T03:01:18.738997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-12T02:57:15.521594Z digest=sha256:af2f5ceb43e3ef67a656112205fc65e80667071def8247eeacc0271df94cc41e