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Paper Citation Record · LEDGER

DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 32 inbound Pith citation observations for arXiv:2309.11325.

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

pith.paper-citation-record.v1
2309.11325 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 32 of 32 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T19:58:04.158028Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T00:59:19.868722Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 18d225d4-54bc-4aee-a8eb-a965537c1944 · inbound

A Survey on Knowledge Distillation of Large Language Models cites this paper.

A Survey on Knowledge Distillation of Large Language Models DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 257

Resolution
metadata mismatch
arxiv_id, observed 2026-05-17T23:31:11.486679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-17T23:31:11.213552Z digest=sha256:d58ae06af0045be78a48e218e21bae2651018f26807001cf4eaa1ecba47a710d

Observation 3e21a8cf-657b-4856-8bef-2136eab9a4ac · inbound

Retrieval-Augmented Generation for AI-Generated Content: A Survey cites this paper.

Retrieval-Augmented Generation for AI-Generated Content: A Survey DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 195

Resolution
verified exact
arxiv_id, observed 2026-05-15T13:32:17.478365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-15T13:32:17.177021Z digest=sha256:7345ccd6575da8bd2f0fe691ae722320dd8c398d2ca28d424ee979ff100c0ac9

Observation 93cd4be0-0cf7-438e-b8c0-6dc22e1c589f · inbound

PDF-WuKong: A Large Multimodal Model for Efficient Long PDF Reading with End-to-End Sparse Sampling cites this paper.

PDF-WuKong: A Large Multimodal Model for Efficient Long PDF Reading with End-to-End Sparse Sampling DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-23T19:43:23.690395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-23T19:39:35.147671Z digest=sha256:32c36667115b8d3512f11c49f43232139f3a427622888befaab59a461f8a0f38

Observation a19cd849-bf51-4a0b-b279-73351a2db5d6 · inbound

Legal Evalutions and Challenges of Large Language Models cites this paper.

Legal Evalutions and Challenges of Large Language Models DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-12T19:58:04.158028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T19:58:04.158028Z digest=sha256:fa2cad62bc4b52f27ead4dca0dde7228271dd13a9f598201dbbb34f03d451750

Observation b684fec9-18de-48ea-9610-706b292886dc · inbound

On the Impact of Fine-Tuning on Chain-of-Thought Reasoning cites this paper.

On the Impact of Fine-Tuning on Chain-of-Thought Reasoning DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-12T14:24:17.326743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T14:24:17.326743Z digest=sha256:2740db826975812c773171419c0e4f5d740310aa6b961de5eb5e954fe15d4df8

Observation ec3e91e0-8e34-4731-8f45-03fc67016faf · inbound

LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods cites this paper.

LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 286

Resolution
verified exact
arxiv_id, observed 2026-05-11T23:08:35.879419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-11T23:08:34.312466Z digest=sha256:2a1aa316b94435f32a201ae45a6f293920ce68b767f8bc4b21aeb7f0756d6ed4

Observation 7d96d437-a10d-4401-8f4b-646c4c87c37a · inbound

Political-LLM: Large Language Models in Political Science cites this paper.

Political-LLM: Large Language Models in Political Science DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-11T19:52:03.927444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:52:03.927444Z digest=sha256:10885729eb9fb8f45e262096f8106c7bc7f853553237934d91f1e81b67d9db95

Observation 1cea019b-5392-475f-8d70-56e09118cd2c · inbound

TrimLLM: Progressive Layer Dropping for Domain-Specific LLMs cites this paper.

TrimLLM: Progressive Layer Dropping for Domain-Specific LLMs DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-11T15:13:23.660462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T15:13:23.660462Z digest=sha256:f85fa1c677c1d64ff063f3b44809e5ef201c430995249e2136702e461060c8d9

Observation cc16e312-4bbd-415a-89f2-4e96ff3fa1fb · inbound

CitaLaw: Enhancing LLM with Citations in Legal Domain cites this paper.

CitaLaw: Enhancing LLM with Citations in Legal Domain DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-11T12:10:16.866902Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:10:16.866902Z digest=sha256:24069b7a8db5dd9790f0f9c459cac06a90f71d14cc89cd332789c2245931a684

Observation 930672f6-6cd4-44b2-a948-5ea9b58fd39d · inbound

Beyond Guilt: Legal Judgment Prediction with Trichotomous Reasoning cites this paper.

Beyond Guilt: Legal Judgment Prediction with Trichotomous Reasoning DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-11T12:10:00.661921Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:10:00.661921Z digest=sha256:205eda02fd530f631667c641ee3fc48214b5af93ae169ef875091de733139c76

Observation 79562efb-7a7f-48ea-8b7e-000cae45be9e · inbound

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement cites this paper.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-10T23:23:28.172779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:23:28.172779Z digest=sha256:1edda1e50b179e7487dd7c5eeaa36f1451b44a59c5ccd443dcbc064306c89c6a

Observation 4981cee5-5431-43e7-9d3c-eafd6f392777 · inbound

Finding Needles in Emb(a)dding Haystacks: Legal Document Retrieval via Bagging and SVR Ensembles cites this paper.

Finding Needles in Emb(a)dding Haystacks: Legal Document Retrieval via Bagging and SVR Ensembles DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-10T21:23:56.489385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:23:56.489385Z digest=sha256:f2e796de7888560c64084672a6ea87d7d35f2107e98c2b08a6cb5e5dcff56e92

Observation 0fbf9f14-22a4-4ea8-be2e-43b7aa2a1613 · inbound

AppealCase: A Dataset and Benchmark for Civil Case Appeal Scenarios cites this paper.

AppealCase: A Dataset and Benchmark for Civil Case Appeal Scenarios DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T15:03:47.230735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:03:47.230735Z digest=sha256:266428317024fb0f993e3848bb4091385fefc652544107063903a37e6d12e08e

Observation 953eeec4-bd06-40a2-bf4d-992683bb46c2 · inbound

EpiCoDe: Boosting Model Performance Beyond Training with Extrapolation and Contrastive Decoding cites this paper.

EpiCoDe: Boosting Model Performance Beyond Training with Extrapolation and Contrastive Decoding DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T11:12:18.762796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:12:18.762796Z digest=sha256:909db560220855fbe538d2a7bba76703b3d7d542a73311a1a452c80beba4c1f8

Observation f3df008a-d87d-4b2d-94f5-ec0652849643 · inbound

EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices cites this paper.

EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 94

Resolution
unresolved
no resolver link, observed 2026-08-06T20:59:03.268870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:59:03.268870Z digest=sha256:8493377176b5151d4842e5059c7aed3c7a28c74e5504062395ab8cfbe1a58e89

Observation c7799ae0-b84f-437d-8650-0d001e4f2d6b · inbound

When Large Language Models Meet Law: Dual-Lens Taxonomy, Technical Advances, and Ethical Governance cites this paper.

When Large Language Models Meet Law: Dual-Lens Taxonomy, Technical Advances, and Ethical Governance DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 205

Resolution
unresolved
no resolver link, observed 2026-08-06T18:37:11.293301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:37:11.293301Z digest=sha256:9cd37d444347910d212856c020e776256ca7d72414fd39cb717c3291d4f37223

Observation 1bceebe9-2661-45fd-98a8-0f5e789d64cf · inbound

Using Large Language Models for Legal Decision-Making in Austrian Value-Added Tax Law: An Experimental Study cites this paper.

Using Large Language Models for Legal Decision-Making in Austrian Value-Added Tax Law: An Experimental Study DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T18:22:21.232106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:22:21.232106Z digest=sha256:c8804318410b9e0c320e41c5a18a6fc0b92efe323d4ced06280d0028ae6159fa

Observation 2ace7340-eeb6-4687-9183-43c0b14e3f96 · inbound

SVGen: Interpretable Vector Graphics Generation with Large Language Models cites this paper.

SVGen: Interpretable Vector Graphics Generation with Large Language Models DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-05T23:59:29.519552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:59:29.519552Z digest=sha256:f84c05e9d0c71519121e915fbb7701f7b226c9128ee7336c509dc4ff3f24a556

Observation 62efc341-c659-4a15-b3c1-427d5da09328 · inbound

LexRel: Benchmarking Legal Relation Extraction for Chinese Civil Cases cites this paper.

LexRel: Benchmarking Legal Relation Extraction for Chinese Civil Cases DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 2

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T22:48:38.287995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-16T22:44:17.919447Z digest=sha256:b445be3dd4f9ec0896295a47e4e01cd90070376cdbf1cbf795dc644a177fb73e

Observation 40cc7cab-2c87-462d-becd-1f861144b07a · inbound

VLegal-Bench: Cognitively Grounded Benchmark for Vietnamese Legal Reasoning of Large Language Models cites this paper.

VLegal-Bench: Cognitively Grounded Benchmark for Vietnamese Legal Reasoning of Large Language Models DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-16T21:38:34.173591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-16T21:36:24.376401Z digest=sha256:a694b08fd8480b35018387d749a64707f25d00896d3d6ea1f724f2d0e1503a7a

Observation 698e83ed-bd67-4e19-bd62-05d3dbc38cf9 · inbound

LLM-AutoDP: Automatic Data Processing via LLM Agents for Model Fine-tuning cites this paper.

LLM-AutoDP: Automatic Data Processing via LLM Agents for Model Fine-tuning DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 54

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T10:57:46.861359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-16T10:54:22.183741Z digest=sha256:02587b7ace955c167885e9256d9a30e5b0d7f833648bae7e68a4309087c8983c

Observation a8862b74-64f3-4a52-9fed-031c20242023 · inbound

TaxPraBen: A Scalable Benchmark for Structured Evaluation of LLMs in Chinese Real-World Tax Practice cites this paper.

TaxPraBen: A Scalable Benchmark for Structured Evaluation of LLMs in Chinese Real-World Tax Practice DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 56

Resolution
verified exact
arxiv_id, observed 2026-05-11T05:41:00.640807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-10T17:59:44.844149Z digest=sha256:3b25f393a3a8fa352de43c470a0ca5d8e1a4ccd5855f4c35f13b329ea9572421

Observation 67ac3a1a-d77f-4f92-aeca-685a11b26bee · inbound

RCBSF: A Multi-Agent Framework for Automated Contract Revision via Stackelberg Game cites this paper.

RCBSF: A Multi-Agent Framework for Automated Contract Revision via Stackelberg Game DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 2

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T09:50:58.757138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-10T15:49:23.444938Z digest=sha256:21c8a269210228b08c6bd8a1cbb367fcc6434e9b31bc69585f2d4243eaed7b78

Observation 571762a2-1c13-4d3f-a25e-e5dd3eb4d85a · inbound

LegalDrill: Diagnosis-Driven Synthesis for Legal Reasoning in Small Language Models cites this paper.

LegalDrill: Diagnosis-Driven Synthesis for Legal Reasoning in Small Language Models DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 8

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T21:16:25.978199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-08T06:06:53.959061Z digest=sha256:3827d346932080ced1143f222e1977bcdcf534dc8e89dfe26468d4ffe7437406

Observation 832f54c2-1fbc-4fa8-906f-ff973d9be835 · inbound

Which Changes Matter? Towards Trustworthy Legal AI via Relevance-Sensitive Evaluation and Solver-Grounded Reasoning cites this paper.

Which Changes Matter? Towards Trustworthy Legal AI via Relevance-Sensitive Evaluation and Solver-Grounded Reasoning DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 32

Resolution
malformed identifier
arxiv_id, observed 2026-06-29T18:43:50.581003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-29T18:39:41.991608Z digest=sha256:362bfe9a6912a8867454324fc7c7e34b0242836c55c3c3732c54d7efc06c3f72

Observation 29058fe9-b49b-4a97-8787-c97b9e6a1e23 · inbound

LegalGraphRAG: Multi-Agent Graph Retrieval-Augmented Generation for Reliable Legal Reasoning cites this paper.

LegalGraphRAG: Multi-Agent Graph Retrieval-Augmented Generation for Reliable Legal Reasoning DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 13

Resolution
malformed identifier
arxiv_id, observed 2026-06-29T13:23:28.251857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-29T13:15:34.622020Z digest=sha256:515619145c5fe7d7e10ebe2e8beb1aec634065ef458d6dba23ab1faa0aa59796

Observation 9bc49c3d-e9cd-4169-963d-76a78640ebfc · inbound

An Ontology-Guided Multi-Anchor Graph Retrieval Framework for Traffic Legal Liability Determination cites this paper.

An Ontology-Guided Multi-Anchor Graph Retrieval Framework for Traffic Legal Liability Determination DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-07-03T11:18:03.655705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-27T09:36:45.509889Z digest=sha256:62acdcca33d558b56e7955cfc2709e8f36e48d93d407a5963889f9a8ca5d8d7f

Observation 367108e7-7ca9-4547-bfa9-f2319b556411 · inbound

LegalWorld: A Life-Cycle Interactive Environment for Legal Agents cites this paper.

LegalWorld: A Life-Cycle Interactive Environment for Legal Agents DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 80

Resolution
verified exact
arxiv_id, observed 2026-07-04T00:59:19.873586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-06-26T20:50:25.070041Z digest=sha256:727ce713f92f99e59caabe294fd399a5156d898225fe58b058b4f39ab7e65cf9

Observation 1e734676-426f-4feb-9734-724d1c6dc678 · inbound

NormWorlds-CF: Solver-Verified Counterfactual Normative Reasoning with Metamorphic-Relation GRPO cites this paper.

NormWorlds-CF: Solver-Verified Counterfactual Normative Reasoning with Metamorphic-Relation GRPO DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 24

Resolution
unresolved
no resolver link, observed 2026-07-11T22:45:47.429470Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T22:45:47.429470Z digest=sha256:f97e4772fdee6ac21cfa0607e9c5abc332e5fae222e54dcc549ce0911c9cfb07

Observation 93769064-59df-4fd4-aa35-46300b928e1e · inbound

NormWorlds-CF: Solver-Verified Counterfactual Normative Reasoning with Metamorphic-Relation GRPO cites this paper.

NormWorlds-CF: Solver-Verified Counterfactual Normative Reasoning with Metamorphic-Relation GRPO DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-02T08:49:45.991281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T08:49:45.991281Z digest=sha256:ae4ed3ae8236d902f122ce61065d0e5eae2a83ae7ea64426c83ff4df7fec297b

Observation 83b901b2-45f7-4d04-86cf-772714be97c9 · inbound

Memory Decoder at Scale: A Pretrained, Parametric Long-Term Memory cites this paper.

Memory Decoder at Scale: A Pretrained, Parametric Long-Term Memory DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 31

Resolution
unresolved
no resolver link, observed 2026-07-31T23:07:18.133745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T23:07:18.133745Z digest=sha256:ee91b4d8c22274f615e8abe72feb8a1db60dba1e81492102e3dda1eba90ac0c7

Observation 3399fe5d-a551-456f-a326-816453930bdd · inbound

LexKairos: Benchmarking Legal Temporal Capabilities in LLMs cites this paper.

LexKairos: Benchmarking Legal Temporal Capabilities in LLMs DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-11T23:29:20.785588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T23:29:20.785588Z digest=sha256:97c06c5b31a26af1652ba7c22d38b28e9239a6077b7dbdda55f81b417197ffc6