Paper Citation Record · LEDGER

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration

As of 8 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 1 inbound Pith citation observation for arXiv:2506.08785.

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

pith.paper-citation-record.v1
2506.08785 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:06:29.544632Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T22:03:10.316005Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T22:06:52.048057Z

Reference resolution

37 of 37 outbound references displayed

verified exact0
verified fuzzy36
unresolved0
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5641c75b-0656-416d-bcca-ebcc3b02a483 · outbound

This paper cites Next-generation domain-specific accelerators: From hard- ware to system,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration Next-generation domain-specific accelerators: From hard- ware to system,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.962565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2d224a20-a7ed-4c46-ac23-4dce7201f014 · outbound

This paper cites How to keep pushing ml accelerator performance? know your rooflines!,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration How to keep pushing ml accelerator performance? know your rooflines!,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.951944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1f78d493-d64d-45b0-8b17-952b21df20c9 · outbound

This paper cites Co-Optimization of GPU AI Chip: Technology, Design, System and Algorithms,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration Co-Optimization of GPU AI Chip: Technology, Design, System and Algorithms,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.941143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7042c132-7505-45ab-80ae-9e28f114f386 · outbound

This paper cites AI and Memory Wall,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration AI and Memory Wall,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.930521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 46a7b951-a09f-479d-953c-3ee65203b9fd · outbound

This paper cites MEGA.mini: A Universal Generative AI Processor with a New Big/Little Core Architecture for NPU,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration MEGA.mini: A Universal Generative AI Processor with a New Big/Little Core Architecture for NPU,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.920409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation aa6701cb-b322-4dcb-97ae-c1f0a7b0d0b6 · outbound

This paper cites Flex-PE: Flexible and SIMD Multiprecision Processing Element for AI Workloads,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration Flex-PE: Flexible and SIMD Multiprecision Processing Element for AI Workloads,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.910031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 47c750a6-c2b1-4ff7-b87c-e1337abe67fc · outbound

This paper cites Parallel Accurate Minifloat MACCs for Neural Network Inference on Versal FPGAs,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration Parallel Accurate Minifloat MACCs for Neural Network Inference on Versal FPGAs,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.899035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 88dc0666-a84c-425e-b050-48f7777ee3ae · outbound

This paper cites A Reconfigurable Processing Element for Multiple- Precision Floating/Fixed-Point HPC,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration A Reconfigurable Processing Element for Multiple- Precision Floating/Fixed-Point HPC,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.888417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cb041992-7d22-40c1-8456-b3401a088bd9 · outbound

This paper cites A Low-Cost Floating-Point Dot-Product-Dual- Accumulate Architecture for HPC-Enabled AI,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration A Low-Cost Floating-Point Dot-Product-Dual- Accumulate Architecture for HPC-Enabled AI,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.877530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3736659f-f2bb-4692-84c3-2ab31b2674b6 · outbound

This paper cites A Low-Cost Floating-Point FMA Unit Supporting Package Operations for HPC-AI Applications,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration A Low-Cost Floating-Point FMA Unit Supporting Package Operations for HPC-AI Applications,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.867716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 27b882b7-c9d4-47bb-a3fa-9ca562998ca2 · outbound

This paper cites RAMAN: A Reconfigurable and Sparse tinyML Accelerator for Inference on Edge,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration RAMAN: A Reconfigurable and Sparse tinyML Accelerator for Inference on Edge,

Reference 11

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T05:06:29.857474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e7ab7ff9-ecee-4efb-a204-518afc9b4ac5 · outbound

This paper cites A Multi-Mode 8k-MAC HW-Utilization- Aware Neural Processing Unit With a Unified Multi-Precision Datapath in 4-nm Flagship Mobile SoC,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration A Multi-Mode 8k-MAC HW-Utilization- Aware Neural Processing Unit With a Unified Multi-Precision Datapath in 4-nm Flagship Mobile SoC,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.847265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c17603c7-a3df-4dcf-911a-33303a2f75a9 · outbound

This paper cites Unified Posit/IEEE-754 Vector MAC Unit for Transprecision Computing,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration Unified Posit/IEEE-754 Vector MAC Unit for Transprecision Computing,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.837191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 056bc1f5-ae78-40ea-9aac-5b704bba8722 · outbound

This paper cites Multiple-Mode-Supporting Floating- Point FMA Unit for Deep Learning Processors,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration Multiple-Mode-Supporting Floating- Point FMA Unit for Deep Learning Processors,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.826908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e7f01d19-8d67-4c9c-a298-41e62a1a0b68 · outbound

This paper cites Multiply-accumulate unit for single- instruction/multiple-data instructions,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration Multiply-accumulate unit for single- instruction/multiple-data instructions,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.816717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3ef4c9ee-beaa-4f63-83eb-218458ebe241 · outbound

This paper cites Multipurpose functional unit with combined integer and floating-point multiply-add pipeline,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration Multipurpose functional unit with combined integer and floating-point multiply-add pipeline,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.806852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 823c8b05-a598-4e42-b4db-e2dd4a31b3ca · outbound

This paper cites Apparatus and method for performing multiply-and-accumulate-products operations,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration Apparatus and method for performing multiply-and-accumulate-products operations,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.796760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 89025b8d-aca6-4d52-aaea-2051c2dff301 · outbound

This paper cites A Configurable Floating-Point Multiple-Precision Processing Element for HPC and AI Converged Computing,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration A Configurable Floating-Point Multiple-Precision Processing Element for HPC and AI Converged Computing,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.786614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ba0cb916-5b36-4c36-be32-fd15b3e903e2 · outbound

This paper cites TSUNAMI: Triple Sparsity-Aware Ultra Energy- Efficient NN Training Accelerator With Multi-Modal Iterative Pruning,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration TSUNAMI: Triple Sparsity-Aware Ultra Energy- Efficient NN Training Accelerator With Multi-Modal Iterative Pruning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.776101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 217529a9-2ca4-411e-aaf5-e72d01c7e408 · outbound

This paper cites QuaRL: Quantization for fast and envi- ronmentally sustainable reinforcement learning,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration QuaRL: Quantization for fast and envi- ronmentally sustainable reinforcement learning,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.765722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation dce597f9-d37d-462c-ac14-4d083c053fc0 · outbound

This paper cites MSDF-Based MAC for Energy-Efficient Neural Networks ,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration MSDF-Based MAC for Energy-Efficient Neural Networks ,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.755561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 67751d9c-19be-4778-88f8-a87d1e124fea · outbound

This paper cites LPRE: Logarithmic Posit-enabled Reconfigurable edge-AI Engine,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration LPRE: Logarithmic Posit-enabled Reconfigurable edge-AI Engine,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.745269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 74b093ae-ac72-4601-83e8-781ef1dd3fae · outbound

This paper cites Low-Precision Mixed- Computation Models for Inference on Edge,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration Low-Precision Mixed- Computation Models for Inference on Edge,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.734508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4e3ab385-f72f-45de-91a4-f1564e0b2e63 · outbound

This paper cites An Empirical Approach to Enhance Performance for Scalable CORDIC-Based DNNs,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration An Empirical Approach to Enhance Performance for Scalable CORDIC-Based DNNs,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.723834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2ec5b5c3-c733-4a0e-84ab-9bbb2d792724 · outbound

This paper cites QuantMAC: Enhancing Hardware Performance in DNNs With Quantize Enabled Multiply-Accumulate Unit,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration QuantMAC: Enhancing Hardware Performance in DNNs With Quantize Enabled Multiply-Accumulate Unit,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.713175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 100467f1-d594-497f-a07e-0c8c125296e5 · outbound

This paper cites A two-stage operand trimming ap- proximate logarithmic multiplier,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration A two-stage operand trimming ap- proximate logarithmic multiplier,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.703353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation eb6ed032-0817-455c-a02c-ed1b3d5d48f2 · outbound

This paper cites An Efficient and Flexible Accelerator Design for Sparse CNNs,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration An Efficient and Flexible Accelerator Design for Sparse CNNs,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.691980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 043d5211-7c4f-48fc-a0f0-193f3ed571b8 · outbound

This paper cites ShortcutFusion: From Tensorflow to FPGA- Based Accelerator With a Reuse-Aware Memory Allocation for Shortcut Data,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration ShortcutFusion: From Tensorflow to FPGA- Based Accelerator With a Reuse-Aware Memory Allocation for Shortcut Data,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.681036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f1166dad-edc5-410e-80e0-7ffa67d7cf64 · outbound

This paper cites A Real-Time Object Detection Pro- cessor With XNOR-Based Variable-Precision Computing Unit,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration A Real-Time Object Detection Pro- cessor With XNOR-Based Variable-Precision Computing Unit,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.670322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ab46a100-66d3-4221-bcf9-b35124281466 · outbound

This paper cites Edge-Side Fine-Grained Sparse CNN Accelerator With Efficient Dynamic Pruning Scheme,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration Edge-Side Fine-Grained Sparse CNN Accelerator With Efficient Dynamic Pruning Scheme,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.658775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 77c8a886-9899-4c8b-af57-aeecfeebdacb · outbound

This paper cites A high-throughput full-dataflow mo- bilenetv2 accelerator on edge fpga,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration A high-throughput full-dataflow mo- bilenetv2 accelerator on edge fpga,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.647743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4b71fb8e-0c4e-41b3-bca2-d5676926d876 · outbound

This paper cites Dedicated FPGA Implementation of the Gaussian TinyYOLOv3 Accelerator,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration Dedicated FPGA Implementation of the Gaussian TinyYOLOv3 Accelerator,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.635678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 26fd2c6d-3044-409f-977f-440b08499cca · outbound

This paper cites A Low-Latency FPGA Accelerator for YOLOv3- Tiny With Flexible Layerwise Mapping and Dataflow,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration A Low-Latency FPGA Accelerator for YOLOv3- Tiny With Flexible Layerwise Mapping and Dataflow,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.623509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f0249f46-7d35-4af8-b5dd-ef8ee8af5d03 · outbound

This paper cites A 29.12- TOPS/W Vector Systolic Accelerator With NAS-Optimized DNNs in 28-nm CMOS,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration A 29.12- TOPS/W Vector Systolic Accelerator With NAS-Optimized DNNs in 28-nm CMOS,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.612480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e4176a24-f881-44f2-881a-d8d3f4a9d444 · outbound

This paper cites A 12.4TOPS/W @ 136GOPS AI-IoT System- on-Chip with 16 RISC-V , 2-to-8b Precision-Scalable DNN Acceleration and 30%-Boost Adaptive Body Biasing,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration A 12.4TOPS/W @ 136GOPS AI-IoT System- on-Chip with 16 RISC-V , 2-to-8b Precision-Scalable DNN Acceleration and 30%-Boost Adaptive Body Biasing,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.600916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1f982e23-776c-4f9d-88c8-35d6cf2c36d6 · outbound

This paper cites A 28nm Energy-Area-Efficient Row-based pipelined Training Accelerator with Mixed FXP4/FP16 for On-Device Transfer Learning,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration A 28nm Energy-Area-Efficient Row-based pipelined Training Accelerator with Mixed FXP4/FP16 for On-Device Transfer Learning,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.589248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1e215b5f-bc1e-437a-a7ab-435473551d64 · outbound

This paper cites PL-NPU: An Energy-Efficient Edge-Device DNN Training Processor With Posit-Based Logarithm-Domain Comput- ing,.

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration PL-NPU: An Energy-Efficient Edge-Device DNN Training Processor With Posit-Based Logarithm-Domain Comput- ing,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:06:29.576932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

Observation 36798001-44c1-4683-8bd1-a99bbc0f67e0 · inbound

ShadowNPU: System and Algorithm Co-design for NPU-Centric On-Device LLM Inference cites this paper.

ShadowNPU: System and Algorithm Co-design for NPU-Centric On-Device LLM Inference POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-18T22:06:52.050294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.