Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-20T22:21:03.637418Z
Paper Citation Record · LEDGER
Concordia: Self-Improving Synthetic Tables for Federated LLMs
As of 15 July 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2605.09855.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-07-14T06:31:01.685423+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
49 of 49 outbound references displayed
- verified exact27
- verified fuzzy21
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 3be08f9c-5d1f-43bf-8f69-36dd4a4317bb · outbound
This paper cites Teo, Lucas C.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Teo, Lucas C
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T22:23:49.143494Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation 31a8df04-c214-4d98-8832-7d67614fd678 · outbound
This paper cites Synthetic Data Aided Federated Learning Using Foundation Models.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Synthetic Data Aided Federated Learning Using Foundation Models
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:23:47.916724Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation b07cabbe-b17b-4a71-81e0-88fe99f89481 · outbound
This paper cites an unresolved cited work.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Unresolved cited work
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T22:23:49.159481Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation d7b9f298-0f38-45bd-8fbc-17d62038b1c2 · outbound
This paper cites SLoRA: Federated Parameter Efficient Fine-Tuning of Language Models.
Concordia: Self-Improving Synthetic Tables for Federated LLMs SLoRA: Federated Parameter Efficient Fine-Tuning of Language Models
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:23:47.924548Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation d76242ae-869d-4e66-b080-378097e83ebb · outbound
This paper cites Language Models are Realistic Tabular Data Generators.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Language Models are Realistic Tabular Data Generators
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:23:47.865667Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation af2357b0-ecfb-4fa6-9f53-03c7b6bb9807 · outbound
This paper cites an unresolved cited work.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Unresolved cited work
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T22:23:49.155006Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation 46fd01ee-94fc-472d-bd26-7bfe67ac612b · outbound
This paper cites Mind the Privacy Unit! User-Level Differential Privacy for Language Model Fine-Tuning.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Mind the Privacy Unit! User-Level Differential Privacy for Language Model Fine-Tuning
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:23:47.904172Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation ba674ff7-44af-462e-81db-1c20154d4cc9 · outbound
This paper cites Minghua Nuo and Chaofan Guo.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Minghua Nuo and Chaofan Guo
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:23:48.002825Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation 7f36d4df-df2e-4455-be7f-59a48433025d · outbound
This paper cites Exploiting Shared Representations for Personalized Federated Learning.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Exploiting Shared Representations for Personalized Federated Learning
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:23:47.892892Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation f2eb79d8-7a68-4510-91aa-ca918ac9886e · outbound
This paper cites Detrano, András Jánosi, Walter Steinbrunn, Matthias Emil Pfisterer, Johann-Jakob Schmid, Sarbjit Sandhu, Kern H Guppy, Stella Lee, and Victor Froelicher.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Detrano, András Jánosi, Walter Steinbrunn, Matthias Emil Pfisterer, Johann-Jakob Schmid, Sarbjit Sandhu, Kern H Guppy, Stella Lee, and Victor Froelicher
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T22:23:49.150799Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation be70d23b-098c-4332-a259-c194ecd13b05 · outbound
This paper cites FATE-LLM: A Industrial Grade Federated Learning Framework for Large Language Models.
Concordia: Self-Improving Synthetic Tables for Federated LLMs FATE-LLM: A Industrial Grade Federated Learning Framework for Large Language Models
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:23:47.881745Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation c87c9869-c8ab-47f6-b543-3fd6ad81ae65 · outbound
This paper cites Federated Learning via Synthetic Data.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Federated Learning via Synthetic Data
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:23:47.910624Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation 5ce47509-b6b2-4382-bf0d-ca0584cacdd2 · outbound
This paper cites an unresolved cited work.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Unresolved cited work
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:23:47.956850Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation d0f28a60-069a-4c1a-a87e-99322d7b953e · outbound
This paper cites Statlog (German Credit Data).
Concordia: Self-Improving Synthetic Tables for Federated LLMs Statlog (German Credit Data)
Reference 15
- Resolution
- verified exact
- doi, observed 2026-05-20T22:23:47.176500Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation 82c5a66e-1fb2-4e4a-82fe-4d2196cab866 · outbound
This paper cites an unresolved cited work.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Unresolved cited work
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T22:23:49.147232Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation cada88a5-020b-45e4-b14a-5d95000fea2b · outbound
This paper cites POPri: Private Federated Learning using Preference-Optimized Synthetic Data.
Concordia: Self-Improving Synthetic Tables for Federated LLMs POPri: Private Federated Learning using Preference-Optimized Synthetic Data
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:23:47.887440Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation 85da6fb9-b03c-4749-8804-72af355468aa · outbound
This paper cites LoRA: Low-Rank Adaptation of Large Language Models.
Concordia: Self-Improving Synthetic Tables for Federated LLMs LoRA: Low-Rank Adaptation of Large Language Models
Reference 18
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-20T22:23:47.897976Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation ae5399af-3862-47bb-ae5f-386507305b2b · outbound
This paper cites an unresolved cited work.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Unresolved cited work
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T22:23:49.136922Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation 4b984567-082e-4009-bc8b-0c2391ee70d9 · outbound
This paper cites FedSynth: Gradient Compression via Synthetic Data in Federated Learning.
Concordia: Self-Improving Synthetic Tables for Federated LLMs FedSynth: Gradient Compression via Synthetic Data in Federated Learning
Reference 20
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:23:47.932238Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation 91961e6b-5afa-44fa-9b2d-42834c9e3ea6 · outbound
This paper cites an unresolved cited work.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Unresolved cited work
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T22:23:49.163066Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation aa544519-9f94-4c30-90dd-d1f7b197d09f · outbound
This paper cites Federated Knowledge Recycling: Privacy-Preserving Synthetic Data Sharing.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Federated Knowledge Recycling: Privacy-Preserving Synthetic Data Sharing
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:23:47.987416Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation 86c7db9e-fb81-4bb0-ae36-056d1a76582a · outbound
This paper cites Matthews.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Matthews
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T22:23:49.140275Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation d832a3eb-e861-4feb-a94a-44fed34faddd · outbound
This paper cites Optimized Feature Generation for Tabular Data via LLMs with Decision Tree Reasoning.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Optimized Feature Generation for Tabular Data via LLMs with Decision Tree Reasoning
Reference 24
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:23:48.010937Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation cc95c3f0-75dd-44ae-a325-0dafc0ba7890 · outbound
This paper cites Classification Accuracy Score for Conditional Generative Models.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Classification Accuracy Score for Conditional Generative Models
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:23:48.016355Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation 87820754-e2bc-4c0f-ab3e-153c8679ed8d · outbound
This paper cites an unresolved cited work.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Unresolved cited work
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T22:23:49.208040Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation 397bbcea-acaf-4f39-ad4a-e4748ca0ac91 · outbound
This paper cites Roth, Shadi Albarqouni, Spyridon Bakas, Mathieu Galtier, Bennett A.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Roth, Shadi Albarqouni, Spyridon Bakas, Mathieu Galtier, Bennett A
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T22:23:49.211716Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation ec348b63-5010-4795-b280-0c4ca52c7957 · outbound
This paper cites an unresolved cited work.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Unresolved cited work
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T22:23:49.215567Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation 92a49cec-a51e-4e6b-a8c3-50288f287f8f · outbound
This paper cites REaLTabFormer: Generating Realistic Relational and Tabular Data using Transformers.
Concordia: Self-Improving Synthetic Tables for Federated LLMs REaLTabFormer: Generating Realistic Relational and Tabular Data using Transformers
Reference 29
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:23:47.871200Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation 37d16b7d-9b9d-4ace-b10e-1387e881b36c · outbound
This paper cites Town, Rory M.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Town, Rory M
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:23:47.981219Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation 86a113de-2147-4898-9ab2-80a8a8bdb895 · outbound
This paper cites an unresolved cited work.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Unresolved cited work
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T22:23:49.200484Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation 1c63c6e7-d28d-4666-a4ed-abbc443d5f16 · outbound
This paper cites Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data?.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data?
Reference 32
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:23:47.975182Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation 63c5cb93-82f3-42f0-9d10-455abf7e2972 · outbound
This paper cites an unresolved cited work.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Unresolved cited work
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T22:23:49.204062Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation c071c875-0441-4c93-acad-a7875df17fb4 · outbound
This paper cites Qwen3 Technical Report.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Qwen3 Technical Report
Reference 34
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T22:23:47.876051Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation c2cd6388-aaf3-403d-9873-eb02b016b1f2 · outbound
This paper cites RewardDS: Privacy-Preserving Fine-Tuning for Large Language Models via Reward Driven Data Synthesis.
Concordia: Self-Improving Synthetic Tables for Federated LLMs RewardDS: Privacy-Preserving Fine-Tuning for Large Language Models via Reward Driven Data Synthesis
Reference 35
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:23:47.994611Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation 592d5da6-8582-4dd6-b949-b198e9032dcc · outbound
This paper cites HARMONIC: Harnessing LLMs for Tabular Data Synthesis and Privacy Protection.
Concordia: Self-Improving Synthetic Tables for Federated LLMs HARMONIC: Harnessing LLMs for Tabular Data Synthesis and Privacy Protection
Reference 36
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:23:47.859042Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation ae81d926-32bf-430f-b274-47b1d1881329 · outbound
This paper cites an unresolved cited work.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Unresolved cited work
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T22:23:49.185310Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation ba14e55b-2a40-4e84-8983-664c8cfaa8c8 · outbound
This paper cites an unresolved cited work.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Unresolved cited work
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T22:23:49.190753Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation df99e8cd-8655-4b87-b1b8-c5ea081306b1 · outbound
This paper cites https://api.semanticscholar.org/CorpusID:275048075.
Concordia: Self-Improving Synthetic Tables for Federated LLMs https://api.semanticscholar.org/CorpusID:275048075
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T22:23:49.195971Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation e3621137-a592-4114-a56a-d380a12945d2 · outbound
This paper cites LanFL: Differentially Private Federated Learning with Large Language Models using Synthetic Samples.
Concordia: Self-Improving Synthetic Tables for Federated LLMs LanFL: Differentially Private Federated Learning with Large Language Models using Synthetic Samples
Reference 40
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:23:47.969370Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation fbe2ff4d-06ab-4d21-9308-1fbfb458f756 · outbound
This paper cites an unresolved cited work.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Unresolved cited work
Reference 41
- Resolution
- verified exact
- doi, observed 2026-05-20T22:23:47.179637Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation b22111d8-933c-4ef9-a964-84daac11b2e7 · outbound
This paper cites an unresolved cited work.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Unresolved cited work
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T22:23:49.174656Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation 3d045b1a-0e27-4336-8058-8f4a77f5e1de · outbound
This paper cites an unresolved cited work.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Unresolved cited work
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T22:23:49.177857Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation 033eaec2-72fd-4bf3-9ff1-6930c617eb14 · outbound
This paper cites On Protecting the Data Privacy of Large Language Models (LLMs): A Survey.
Concordia: Self-Improving Synthetic Tables for Federated LLMs On Protecting the Data Privacy of Large Language Models (LLMs): A Survey
Reference 44
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:23:47.949249Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation c8aedd37-9b03-4bce-b1b7-02e954fa3494 · outbound
This paper cites an unresolved cited work.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Unresolved cited work
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T22:23:49.171062Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation 4ab129e2-7a9d-4f01-8f63-6de9898d8ddc · outbound
This paper cites FedLLM-Bench: Realistic Benchmarks for Federated Learning of Large Language Models.
Concordia: Self-Improving Synthetic Tables for Federated LLMs FedLLM-Bench: Realistic Benchmarks for Federated Learning of Large Language Models
Reference 46
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:23:47.942647Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation b39f553a-dee7-4d9e-8d8d-88261ed2daaf · outbound
This paper cites an unresolved cited work.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Unresolved cited work
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T22:23:49.181599Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation 2f8e6630-3611-41c1-96f4-ee97d0b5b9b7 · outbound
This paper cites pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning.
Concordia: Self-Improving Synthetic Tables for Federated LLMs pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning
Reference 48
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:23:47.963447Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation 037cde7d-c0d8-44f8-83ed-ac248028161b · outbound
This paper cites an unresolved cited work.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Unresolved cited work
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T22:23:49.167271Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Observation 54a702d1-65f0-4de8-9904-5689f5088abe · outbound
This paper cites Contrastive Private Data Synthesis via Weighted Multi-PLM Fusion.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Contrastive Private Data Synthesis via Weighted Multi-PLM Fusion
Reference 50
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:23:47.937996Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.
Pith citing papers
No inbound Pith citation observations are available.