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Paper Citation Record · LEDGER

Let Your Graph Do the Talking: Encoding Structured Data for LLMs

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 26 inbound Pith citation observations for arXiv:2402.05862.

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

pith.paper-citation-record.v1
2402.05862 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 26 of 26 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 26 of 26 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T00:42:57.098416Z

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

7
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 50a8b4eb-b85f-487f-9a70-600a93ea553d · inbound

Query-Aware Learnable Graph Pooling Tokens as Prompt for Large Language Models cites this paper.

Query-Aware Learnable Graph Pooling Tokens as Prompt for Large Language Models Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-23T04:37:32.016559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-23T04:36:06.247071Z digest=sha256:aaf34663870eb1466b1ddeaff536fbe8a5d5664bf991c069c9a502e2f27e2694

Observation 164f3290-2e23-4dbc-a8ef-901b5d79a03c · inbound

Multimodal Medical Code Tokenizer cites this paper.

Multimodal Medical Code Tokenizer Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-09T00:42:57.098416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T00:42:57.098416Z digest=sha256:4a346f7f6ba74474f6c93c447f90ea5a28b13019ecef6c3bdcdcf600bb3a4957

Observation 90a431ae-31c9-4481-9eea-6ea3fe575b05 · inbound

Spectral Journey: How Transformers Predict the Shortest Path cites this paper.

Spectral Journey: How Transformers Predict the Shortest Path Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T23:44:10.842813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T23:44:10.842813Z digest=sha256:0149ce3cda8fa131cd6a04a965a5111e5414ef8b66d8552eadd1932846277283

Observation 10f27037-fc5c-4d5d-8eb4-479fddcf45a5 · inbound

Walk&Retrieve: Simple Yet Effective Zero-shot Retrieval-Augmented Generation via Knowledge Graph Walks cites this paper.

Walk&Retrieve: Simple Yet Effective Zero-shot Retrieval-Augmented Generation via Knowledge Graph Walks Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T14:58:37.145173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:58:37.145173Z digest=sha256:0b15ba42bedb144e56d367523881654d22914cb6a6eeeaa032efebf0882b13b9

Observation 6ccf3fb3-5dd8-48f7-9523-fc31484157cb · inbound

G1: Teaching LLMs to Reason on Graphs with Reinforcement Learning cites this paper.

G1: Teaching LLMs to Reason on Graphs with Reinforcement Learning Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T14:34:04.112727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:34:04.112727Z digest=sha256:2689379f307daf03b4fa3979d9968cca4ce771fb0b86d9461bbb3cdec0175dd5

Observation eb477d62-1f18-487a-9d1a-5cfef0d628a5 · inbound

Generalizable LLM Learning of Graph Synthetic Data with Post-training Alignment cites this paper.

Generalizable LLM Learning of Graph Synthetic Data with Post-training Alignment Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-07T12:02:44.611941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:02:44.611941Z digest=sha256:89a85865d544661441f95fe463809c4cdae775d546efb3df544ae26bcedb862c

Observation 472fc51b-f42e-4220-9e2c-ebf6ae3bade1 · inbound

Are Large Language Models Good Temporal Graph Learners? cites this paper.

Are Large Language Models Good Temporal Graph Learners? Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T11:09:43.562095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:09:43.562095Z digest=sha256:c26d91613c97e50965e71dc2a38804256f473d9ab27047cdf69e4f7fae0aa07b

Observation 418d2b1c-b155-4850-af18-7d8445b9e85b · inbound

Graph-Based Physics-Guided Urban PM2.5 Air Quality Imputation with Constrained Monitoring Data cites this paper.

Graph-Based Physics-Guided Urban PM2.5 Air Quality Imputation with Constrained Monitoring Data Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T05:51:02.835418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:51:02.835418Z digest=sha256:8b9638036850eef3c7aa3ed48e89a0f4475841e30dc6c986255e926d82bd0707

Observation 1cfd3b10-90ab-49f1-afad-68cd4ae14c57 · inbound

Modeling Code: Is Text All You Need? cites this paper.

Modeling Code: Is Text All You Need? Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-06T17:11:49.719008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:11:49.719008Z digest=sha256:ef8d493c63af0e4d9d5b7835cecd39aba08725c490c86f3a58a51238f7791798

Observation be0bc078-97a6-4fd8-9512-ecb922c0078e · inbound

Exploring the In-Context Learning Capabilities of LLMs for Money Laundering Detection in Financial Graphs cites this paper.

Exploring the In-Context Learning Capabilities of LLMs for Money Laundering Detection in Financial Graphs Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-19T03:57:02.964867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-19T03:55:56.563517Z digest=sha256:9c426a9429ffa4df96f7b85dd0af0966044df4a5110b5a7b7244c58583bc3e68

Observation 56645149-51d2-4ff8-adcf-ba8c101a2056 · inbound

Harnessing Adaptive Topology Representations for Zero-Shot Graph Question Answering cites this paper.

Harnessing Adaptive Topology Representations for Zero-Shot Graph Question Answering Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-05T22:55:20.857765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T22:55:20.857765Z digest=sha256:eaebc8f405694008a78bd27cf8105a4b9d0ec14b072000fc7462872542c4cfcc

Observation cb783ae2-60d1-4d08-846f-1355fbf3f4a5 · inbound

Efficient Graph Understanding with LLMs via Structured Context Injection cites this paper.

Efficient Graph Understanding with LLMs via Structured Context Injection Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-05T13:19:47.547168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:19:47.547168Z digest=sha256:d8d3aaeb8baf5e03ecd0f6f4c397563993e9e11ae6279150e739aefde33adbc0

Observation ee465691-ffa1-45c0-8237-8be7b0285dcd · inbound

Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning cites this paper.

Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-03T19:22:02.445263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T19:22:02.445263Z digest=sha256:c7063a8bda17510a9fafc5f27620f36d7078de5e0fbfe5ab2cf37626e78e56d3

Observation 1e43032a-30d6-4f33-a1ab-5fdc20287857 · inbound

Heterogeneous Scientific Foundation Model Collaboration cites this paper.

Heterogeneous Scientific Foundation Model Collaboration Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 143

Resolution
verified exact
arxiv_id, observed 2026-05-09T04:30:09.957806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-07T08:50:05.980191Z digest=sha256:bf4ba682a4c6dbcc64cbc28ea74bf10efd6199252df7c94f0c304fac8c81985b

Observation 55a207df-2d15-4428-a5c2-cc3e9f1bff89 · inbound

Bridging Input Feature Spaces Towards Graph Foundation Models cites this paper.

Bridging Input Feature Spaces Towards Graph Foundation Models Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-11T17:41:08.673821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-08T17:18:21.259797Z digest=sha256:3a0d986f684c6c77d1edbfc3c1c932a85151b2e2daa2cb9f0059beaa834b9fc0

Observation 7ac7f3aa-463d-4365-a886-0aa0b7005a32 · inbound

RelAgent: LLM Agents as Data Scientists for Relational Learning cites this paper.

RelAgent: LLM Agents as Data Scientists for Relational Learning Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-11T03:15:56.322694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-11T02:33:34.960543Z digest=sha256:e7b5fc3b7675d14f4c11b0d9086880be689e341a9f5572209fa70f7305051946

Observation a5ab4c58-63e2-4e2e-8436-e35a131e0e6c · inbound

SAGE: A Self-Evolving Agentic Graph-Memory Engine for Structure-Aware Associative Memory cites this paper.

SAGE: A Self-Evolving Agentic Graph-Memory Engine for Structure-Aware Associative Memory Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 244

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T04:57:17.762220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-13T04:45:34.957298Z digest=sha256:e84a890be0ee1c3a61c8c29df6296357b50b318304f465607d6fb75c20eceba4

Observation 8c8f8d5b-4c90-4185-b739-d6cc5ece75ee · inbound

A Unified Graph Language Model for Multi-Domain Multi-Task Graph Alignment Instruction Tuning cites this paper.

A Unified Graph Language Model for Multi-Domain Multi-Task Graph Alignment Instruction Tuning Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-13T06:42:25.959187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-13T06:41:55.783539Z digest=sha256:04428ce327ef67eb9c9fae8c808922ba5ac5ce87bd78779d524981ff0b1a5a70

Observation e124c7fa-c355-41fa-9c6c-0b4ffdda659e · inbound

KoRe: Compact Knowledge Representations for Large Language Models cites this paper.

KoRe: Compact Knowledge Representations for Large Language Models Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-20T05:28:05.106955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-20T05:24:12.315885Z digest=sha256:22069569c0843bb1841f225413051647a521fe21057ad4e82fc612ef682d28d2

Observation 5b7f38eb-4f55-476b-8ee3-441ef483c651 · inbound

KoRe: Compact Knowledge Representations for Large Language Models cites this paper.

KoRe: Compact Knowledge Representations for Large Language Models Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-02T13:39:15.683309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T13:39:15.683309Z digest=sha256:25711dbc5109d7969a30a30d1aaf94d2d6d84dff8ca96679e7842d1237cbbaa9

Observation fec324b2-f7f4-4f2d-9313-d8e40c7eb723 · inbound

Mixture-of-Experts Knowledge Graph Retrieval-Augmented Generation for Multi-Agent LLM-based Recommendation cites this paper.

Mixture-of-Experts Knowledge Graph Retrieval-Augmented Generation for Multi-Agent LLM-based Recommendation Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-06-29T10:13:17.964290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-29T10:03:45.368681Z digest=sha256:26bd9f7d6210bbb980c0aab36202c5ac0597499a56283d1638d0422d9e9156bc

Observation 589fb112-4a1a-4fe0-943e-a648ece5a520 · inbound

Edge-Aware Curvature Modeling for Graph Understanding in Large Language Models cites this paper.

Edge-Aware Curvature Modeling for Graph Understanding in Large Language Models Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-07-02T15:47:06.048382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-27T23:35:37.053602Z digest=sha256:d9e066181624e0ae2a87607ddfc1043e8236125b78726d9c9b1d7fc93153704b

Observation 23a58642-77ad-42ad-bd4f-552c22dc6ab3 · inbound

Are Large Language Models Suitable for Graph Computation? Progress and Prospects cites this paper.

Are Large Language Models Suitable for Graph Computation? Progress and Prospects Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 227

Resolution
verified exact
arxiv_id, observed 2026-07-02T17:07:12.264737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-27T22:15:03.223540Z digest=sha256:8d0ea82cc40f36ddabd2d83355510771c1a84bacbe7b3ee59e3e5f999495fa37

Observation 08b64dd0-fda8-4b0c-8142-1d8152614c75 · inbound

GraphInfer-Bench: Benchmarking LLM's Inference Capability on Graphs cites this paper.

GraphInfer-Bench: Benchmarking LLM's Inference Capability on Graphs Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-07-03T08:57:47.504673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-27T10:41:37.290485Z digest=sha256:d6f99b57c0bfb80531aa0cb501423e358178cc28292d482468dda17cb3a7d6e2

Observation bb86061a-d8cb-4532-882c-4d859f0ad647 · inbound

C-RE-ACT: Causal RE-ACTing Agent for O-RAN Forensic Triage cites this paper.

C-RE-ACT: Causal RE-ACTing Agent for O-RAN Forensic Triage Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 25

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no resolver link, observed 2026-08-01T01:26:39.129204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T01:26:39.129204Z digest=sha256:3bb5267c40eef2aebca45293410da7ffa4900e3606378dcda5de16d07e0a6627

Observation 216fc8d6-7966-4330-8f6a-db23f3f93454 · inbound

GARDRec: Decision-Level Graph Grounding for Large Language Model Recommendation cites this paper.

GARDRec: Decision-Level Graph Grounding for Large Language Model Recommendation Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-04T00:55:46.461814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T00:55:46.461814Z digest=sha256:5b6b17f69aaf3724c17efbcc9dd7be8617fc0c14991a7db0bd3b2d7cbc7c02de