Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T14:36:46.433104Z
Paper Citation Record · LEDGER
LiFTER: A Grounded Neuro-Symbolic Microscope for Continuous-Time Dynamic Graph Forecasting
As of 18 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2608.06765.
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 2026-08-18T06:34:40.430872+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
17 of 17 outbound references displayed
- verified exact2
- verified fuzzy15
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 900ca58b-8cb1-4c6b-aa58-c388b7b94ae8 · outbound
This paper cites Temporal graph networks for deep learning on dynamic graphs,.
LiFTER: A Grounded Neuro-Symbolic Microscope for Continuous-Time Dynamic Graph Forecasting Temporal graph networks for deep learning on dynamic graphs,
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:36:46.581132Z
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.
Observation 43440c8b-299e-4fe6-9ac9-85b25476c117 · outbound
This paper cites Induc- tive representation learning on temporal graphs,.
LiFTER: A Grounded Neuro-Symbolic Microscope for Continuous-Time Dynamic Graph Forecasting Induc- tive representation learning on temporal graphs,
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:36:46.573070Z
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.
Observation 81f8dc9b-41ec-4507-b1a9-e0bd07b68f1a · outbound
This paper cites Do we really need complicated model architectures for temporal networks?.
LiFTER: A Grounded Neuro-Symbolic Microscope for Continuous-Time Dynamic Graph Forecasting Do we really need complicated model architectures for temporal networks?
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:36:46.565873Z
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.
Observation 07038146-e6ca-4aa0-883c-e8406c305503 · outbound
This paper cites DyGFormer: A transformer- based architecture for dynamic graph representation learning,.
LiFTER: A Grounded Neuro-Symbolic Microscope for Continuous-Time Dynamic Graph Forecasting DyGFormer: A transformer- based architecture for dynamic graph representation learning,
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:36:46.558300Z
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.
Observation fffbb1bc-8164-4e65-9b04-e883d0154c5c · outbound
This paper cites Ex- plaining temporal graph models through an explorer-navigator framework,.
LiFTER: A Grounded Neuro-Symbolic Microscope for Continuous-Time Dynamic Graph Forecasting Ex- plaining temporal graph models through an explorer-navigator framework,
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:36:46.551112Z
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.
Observation b0d9c980-40b1-4793-8efb-13c55dc256ea · outbound
This paper cites TempME: Towards the explainability of temporal graph neural networks via motif discovery,.
LiFTER: A Grounded Neuro-Symbolic Microscope for Continuous-Time Dynamic Graph Forecasting TempME: Towards the explainability of temporal graph neural networks via motif discovery,
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:36:46.541705Z
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.
Observation b7ebb57f-8b6b-48d2-92d5-4b5b4be0c488 · outbound
This paper cites Self-explainable temporal graph networks based on graph information bottleneck,.
LiFTER: A Grounded Neuro-Symbolic Microscope for Continuous-Time Dynamic Graph Forecasting Self-explainable temporal graph networks based on graph information bottleneck,
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:36:46.533541Z
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.
Observation e2f861a6-7657-4669-b2fb-4fd683c8048a · outbound
This paper cites Invariant Graph Representations for Continuous-Time Dynamic Graphs Under Distribution Shifts.
LiFTER: A Grounded Neuro-Symbolic Microscope for Continuous-Time Dynamic Graph Forecasting Invariant Graph Representations for Continuous-Time Dynamic Graphs Under Distribution Shifts
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T14:36:46.467349Z
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.
Observation 64041c8e-da4e-4285-ab9c-1198e22fd5bb · outbound
This paper cites Differentiable learning of logical rules for knowledge base reasoning,.
LiFTER: A Grounded Neuro-Symbolic Microscope for Continuous-Time Dynamic Graph Forecasting Differentiable learning of logical rules for knowledge base reasoning,
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:36:46.525773Z
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.
Observation da29daf8-0462-4c8c-86bd-5a2585e52870 · outbound
This paper cites TLogic: Temporal logical rules for explainable link forecasting on tempo- ral knowledge graphs,.
LiFTER: A Grounded Neuro-Symbolic Microscope for Continuous-Time Dynamic Graph Forecasting TLogic: Temporal logical rules for explainable link forecasting on tempo- ral knowledge graphs,
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:36:46.519115Z
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.
Observation c0adf454-3b7e-47bb-a45e-ab0bbb6666d2 · outbound
This paper cites Temporal induc- tive logic reasoning,.
LiFTER: A Grounded Neuro-Symbolic Microscope for Continuous-Time Dynamic Graph Forecasting Temporal induc- tive logic reasoning,
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:36:46.512428Z
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.
Observation 7e303938-16da-4e67-9776-350e6ead41ec · outbound
This paper cites Towards better evaluation for dynamic link prediction,.
LiFTER: A Grounded Neuro-Symbolic Microscope for Continuous-Time Dynamic Graph Forecasting Towards better evaluation for dynamic link prediction,
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:36:46.505535Z
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.
Observation 78acac01-4784-478c-89bb-ab7af82aba03 · outbound
This paper cites On the power of heuristics in temporal graphs,.
LiFTER: A Grounded Neuro-Symbolic Microscope for Continuous-Time Dynamic Graph Forecasting On the power of heuristics in temporal graphs,
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:36:46.498420Z
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.
Observation 25939fe1-195c-4a1a-b2c3-fa18e8a44b12 · outbound
This paper cites TGB-Seq benchmark: Challenging temporal GNNs with complex sequential dynamics,.
LiFTER: A Grounded Neuro-Symbolic Microscope for Continuous-Time Dynamic Graph Forecasting TGB-Seq benchmark: Challenging temporal GNNs with complex sequential dynamics,
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:36:46.490025Z
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.
Observation 0b3e553f-14c9-46d2-9030-8a4d6669b71d · outbound
This paper cites Future Link Prediction Without Memory or Aggregation.
LiFTER: A Grounded Neuro-Symbolic Microscope for Continuous-Time Dynamic Graph Forecasting Future Link Prediction Without Memory or Aggregation
Reference 15
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T14:36:46.456709Z
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.
Observation 1a5b041b-4d39-44f7-823f-03dad495f961 · outbound
This paper cites HOT: Higher-order dynamic graph representation learning with efficient transformers,.
LiFTER: A Grounded Neuro-Symbolic Microscope for Continuous-Time Dynamic Graph Forecasting HOT: Higher-order dynamic graph representation learning with efficient transformers,
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:36:46.482043Z
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.
Observation 40c9e26a-6b44-43be-a8ec-f82a1e4dce67 · outbound
This paper cites Inductive rep- resentation learning in temporal networks via causal anonymous walks,.
LiFTER: A Grounded Neuro-Symbolic Microscope for Continuous-Time Dynamic Graph Forecasting Inductive rep- resentation learning in temporal networks via causal anonymous walks,
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:36:46.474765Z
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.
Pith citing papers
No inbound Pith citation observations are available.