Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T22:32:10.566454Z
Paper Citation Record · LEDGER
MAx-DNN: Multi-Level Arithmetic Approximation for Energy-Efficient DNN Hardware Accelerators
As of 18 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2506.21371.
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
13 of 13 outbound references displayed
- verified exact0
- verified fuzzy13
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation e755e9c2-0336-4746-b569-5de80faa672b · outbound
This paper cites A Survey of Techniques for Approximate Computing,.
MAx-DNN: Multi-Level Arithmetic Approximation for Energy-Efficient DNN Hardware Accelerators A Survey of Techniques for Approximate Computing,
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:32:10.778629Z
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 120bdcc9-ed28-4105-bb0a-71fe47747a93 · outbound
This paper cites Cooperative Arithmetic-Aware Approximation Tech- niques for Energy-Efficient Multipliers,.
MAx-DNN: Multi-Level Arithmetic Approximation for Energy-Efficient DNN Hardware Accelerators Cooperative Arithmetic-Aware Approximation Tech- niques for Energy-Efficient Multipliers,
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:32:10.764997Z
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 6f036274-7857-46f8-a10c-6e4ba7a0c21c · outbound
This paper cites AUGER: A Tool for Generating Approximate Arithmetic Circuits,.
MAx-DNN: Multi-Level Arithmetic Approximation for Energy-Efficient DNN Hardware Accelerators AUGER: A Tool for Generating Approximate Arithmetic Circuits,
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:32:10.750783Z
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 ee500705-182a-4c34-a752-45de31696399 · outbound
This paper cites Approximate Hybrid High Radix Encoding for Energy- Efficient Inexact Multipliers,.
MAx-DNN: Multi-Level Arithmetic Approximation for Energy-Efficient DNN Hardware Accelerators Approximate Hybrid High Radix Encoding for Energy- Efficient Inexact Multipliers,
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:32:10.737324Z
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 846a3ea1-d566-4fee-a1b4-46e832fee0f6 · outbound
This paper cites EvoApprox8b: Library of Approximate Adders and Multipliers for Circuit Design and Benchmarking of Approximation Meth- ods,.
MAx-DNN: Multi-Level Arithmetic Approximation for Energy-Efficient DNN Hardware Accelerators EvoApprox8b: Library of Approximate Adders and Multipliers for Circuit Design and Benchmarking of Approximation Meth- ods,
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:32:10.723631Z
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 fd9efe5f-ede7-4f0d-8ecd-6bc2812532b0 · outbound
This paper cites Exploiting the Potential of Approximate Arithmetic in DSP & AI Hardware Accelerators,.
MAx-DNN: Multi-Level Arithmetic Approximation for Energy-Efficient DNN Hardware Accelerators Exploiting the Potential of Approximate Arithmetic in DSP & AI Hardware Accelerators,
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:32:10.709502Z
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 d3302a40-d3b5-498c-8a0b-a44ce43a0aa9 · outbound
This paper cites ALW ANN: Automatic Layer-Wise Approximation of Deep Neural Network Accelerators without Retraining,.
MAx-DNN: Multi-Level Arithmetic Approximation for Energy-Efficient DNN Hardware Accelerators ALW ANN: Automatic Layer-Wise Approximation of Deep Neural Network Accelerators without Retraining,
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:32:10.695853Z
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 621e76f3-89db-47e6-9903-028286049e8d · outbound
This paper cites Combining Arithmetic Approximation Techniques for Improved CNN Circuit Design,.
MAx-DNN: Multi-Level Arithmetic Approximation for Energy-Efficient DNN Hardware Accelerators Combining Arithmetic Approximation Techniques for Improved CNN Circuit Design,
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:32:10.679565Z
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 3cdc8ef7-730d-42e4-8d89-e8fa0d38f656 · outbound
This paper cites Efficient AI System Design With Cross-Layer Approximate Computing,.
MAx-DNN: Multi-Level Arithmetic Approximation for Energy-Efficient DNN Hardware Accelerators Efficient AI System Design With Cross-Layer Approximate Computing,
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:32:10.663154Z
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 2f850894-3470-4557-b52b-b79e4be6b98c · outbound
This paper cites ApproxQAM: High-Order QAM Demodulation Circuits with Approximate Arithmetic,.
MAx-DNN: Multi-Level Arithmetic Approximation for Energy-Efficient DNN Hardware Accelerators ApproxQAM: High-Order QAM Demodulation Circuits with Approximate Arithmetic,
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:32:10.649006Z
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 cf69b809-c8d7-4aa6-9693-b790b57a81aa · outbound
This paper cites Flexpoint: An Adaptive Numerical Format for Efficient Training of Deep Neural Networks,.
MAx-DNN: Multi-Level Arithmetic Approximation for Energy-Efficient DNN Hardware Accelerators Flexpoint: An Adaptive Numerical Format for Efficient Training of Deep Neural Networks,
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:32:10.634067Z
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 6474740c-292e-4514-8ea4-b2703eb266d5 · outbound
This paper cites Quantized Convolutional Neural Networks for Mobile De- vices,.
MAx-DNN: Multi-Level Arithmetic Approximation for Energy-Efficient DNN Hardware Accelerators Quantized Convolutional Neural Networks for Mobile De- vices,
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:32:10.617840Z
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 129e0a01-14fc-474e-955f-b941e6902f52 · outbound
This paper cites Structured Pruning of Deep Convolutional Neural Net- works,.
MAx-DNN: Multi-Level Arithmetic Approximation for Energy-Efficient DNN Hardware Accelerators Structured Pruning of Deep Convolutional Neural Net- works,
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:32:10.602439Z
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.