Paper Citation Record · LEDGER

WF-Bench: A Benchmark for Neural Network WaveFunction Expressivity and Scaling Laws

As of 14 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2605.29683.

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

pith.paper-citation-record.v1
2605.29683 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-29T00:13:22.204575Z

measured 14 of 14 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

14 of 14 outbound references displayed

verified exact11
verified fuzzy0
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation daa9d77d-8e4e-4e72-9463-6aa84b87e606 · outbound

This paper cites Neural Scaling Laws Surpass Chemical Accuracy for the Many-Electron Schr\"odinger Equation.

WF-Bench: A Benchmark for Neural Network WaveFunction Expressivity and Scaling Laws Neural Scaling Laws Surpass Chemical Accuracy for the Many-Electron Schr\"odinger Equation

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T00:22:51.756161Z

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.

Observation 8acf054b-ee2b-4ec4-acd2-478d8b3f48d1 · outbound

This paper cites Deep Learning and Quantum Entanglement: Fundamental Connections with Implications to Network Design.

WF-Bench: A Benchmark for Neural Network WaveFunction Expressivity and Scaling Laws Deep Learning and Quantum Entanglement: Fundamental Connections with Implications to Network Design

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-06-29T00:22:51.747477Z

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.

Observation 7614453d-6eb7-40a5-b6fe-9464a4fb6938 · outbound

This paper cites Symmetry enforced solution of the many-body Schr\"odinger equation with deep neural network.

WF-Bench: A Benchmark for Neural Network WaveFunction Expressivity and Scaling Laws Symmetry enforced solution of the many-body Schr\"odinger equation with deep neural network

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-06-29T00:22:51.753564Z

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.

Observation 69980112-588b-450c-bd02-d466108a8483 · outbound

This paper cites an unresolved cited work.

WF-Bench: A Benchmark for Neural Network WaveFunction Expressivity and Scaling Laws Unresolved cited work

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-29T00:13:22.204575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 032e70bb-cf03-42dc-81a9-b1004d82bf8b · outbound

This paper cites Information- theoretic scaling laws of neural quantum states.arXiv preprint arXiv:2603.23468,.

WF-Bench: A Benchmark for Neural Network WaveFunction Expressivity and Scaling Laws Information- theoretic scaling laws of neural quantum states.arXiv preprint arXiv:2603.23468,

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-06-29T00:22:51.750437Z

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.

Observation 6a06ef1a-1a27-450a-a732-e579ea944dc4 · outbound

This paper cites Gauge Equivariant Neural Networks for 2+1D U(1) Gauge Theory Simulations in Hamiltonian Formulation.

WF-Bench: A Benchmark for Neural Network WaveFunction Expressivity and Scaling Laws Gauge Equivariant Neural Networks for 2+1D U(1) Gauge Theory Simulations in Hamiltonian Formulation

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-06-29T00:22:51.744519Z

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.

Observation dd7317f9-c9d2-44aa-9ec9-b3245e6c6143 · outbound

This paper cites Simulating moir\'e quantum matter with neural network.

WF-Bench: A Benchmark for Neural Network WaveFunction Expressivity and Scaling Laws Simulating moir\'e quantum matter with neural network

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-06-29T00:22:51.741747Z

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.

Observation c3d28215-e620-4dea-9ee6-099c16b95b35 · outbound

This paper cites Solving fractional electron states in twisted MoTe$_2$ with deep neural network.

WF-Bench: A Benchmark for Neural Network WaveFunction Expressivity and Scaling Laws Solving fractional electron states in twisted MoTe$_2$ with deep neural network

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-06-29T00:22:51.741598Z

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.

Observation 8e414c5e-42bd-42bf-a6ac-37a75e6f4629 · outbound

This paper cites Nazaryan, F.

WF-Bench: A Benchmark for Neural Network WaveFunction Expressivity and Scaling Laws Nazaryan, F

Reference 9

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T00:22:51.744795Z

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.

Observation 47208e50-5e4f-41be-b558-38ad1361d17d · outbound

This paper cites Paul, Bound on entanglement in neural quantum states (2025), arXiv:2510.11797 [quant-ph].

WF-Bench: A Benchmark for Neural Network WaveFunction Expressivity and Scaling Laws Paul, Bound on entanglement in neural quantum states (2025), arXiv:2510.11797 [quant-ph]

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-06-29T00:22:51.758733Z

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.

Observation fa071994-a621-4932-8b48-bb6f5557dc73 · outbound

This paper cites A Self-Attention Ansatz for Ab-initio Quantum Chemistry.

WF-Bench: A Benchmark for Neural Network WaveFunction Expressivity and Scaling Laws A Self-Attention Ansatz for Ab-initio Quantum Chemistry

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-06-29T00:22:51.747162Z

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.

Observation b184c302-ae0c-4f20-a0e8-1f4cf2eacbd7 · outbound

This paper cites When can classical neural networks represent quantum states?.

WF-Bench: A Benchmark for Neural Network WaveFunction Expressivity and Scaling Laws When can classical neural networks represent quantum states?

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-06-29T00:22:51.749801Z

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.

Observation 78b409a6-83a5-43c1-b124-d199ccd65271 · outbound

This paper cites Zhang and D.

WF-Bench: A Benchmark for Neural Network WaveFunction Expressivity and Scaling Laws Zhang and D

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-06-29T00:22:51.761909Z

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.

Observation a6957954-5f96-4165-a7be-c209f0fdb3d4 · outbound

This paper cites Erwin: A Tree-based Hierarchical Transformer for Large-scale Physical Systems.

WF-Bench: A Benchmark for Neural Network WaveFunction Expressivity and Scaling Laws Erwin: A Tree-based Hierarchical Transformer for Large-scale Physical Systems

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-06-29T00:22:51.764503Z

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.

Pith citing papers

No inbound Pith citation observations are available.