Paper Citation Record · LEDGER

Accelerating Large-Scale Inference with Anisotropic Vector Quantization

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:1908.10396.

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

pith.paper-citation-record.v1
1908.10396 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:51:21.073577Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T13:28:18.591775Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3381c33e-a3a0-46d6-a97f-0ec50f53e1e3 · inbound

Improving language models by retrieving from trillions of tokens cites this paper.

Improving language models by retrieving from trillions of tokens Accelerating Large-Scale Inference with Anisotropic Vector Quantization

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-17T12:55:41.697929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8176a4f6-69ea-47bf-a467-d7ae6c5d7c09 · inbound

FlexRAG: A Flexible and Comprehensive Framework for Retrieval-Augmented Generation cites this paper.

FlexRAG: A Flexible and Comprehensive Framework for Retrieval-Augmented Generation Accelerating Large-Scale Inference with Anisotropic Vector Quantization

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T00:51:21.073577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c88995f3-3899-46b0-9ee8-919175a07ead · inbound

CleANN: Efficient Full Dynamism in Graph-based Approximate Nearest Neighbor Search cites this paper.

CleANN: Efficient Full Dynamism in Graph-based Approximate Nearest Neighbor Search Accelerating Large-Scale Inference with Anisotropic Vector Quantization

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T14:03:50.074410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6cc460d-a29b-4f76-ab56-ceeb08798667 · inbound

Efficient Item ID Generation for Large-Scale LLM-based Recommendation cites this paper.

Efficient Item ID Generation for Large-Scale LLM-based Recommendation Accelerating Large-Scale Inference with Anisotropic Vector Quantization

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T10:46:47.726726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b72c218a-3e0b-4278-9fb0-1ff77a91710c · inbound

An LLM-Guided Query-Aware Inference System for GNN Models on Large Knowledge Graphs cites this paper.

An LLM-Guided Query-Aware Inference System for GNN Models on Large Knowledge Graphs Accelerating Large-Scale Inference with Anisotropic Vector Quantization

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-15T16:16:15.047534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7b585021-d3de-44fe-8b41-6a6507c8a9ce · inbound

A Replicability Study of XTR cites this paper.

A Replicability Study of XTR Accelerating Large-Scale Inference with Anisotropic Vector Quantization

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:16:06.259671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 078cefab-55dc-4fd9-bc63-398e1b87a232 · inbound

Ascend-RaBitQ: Heterogeneous NPU-CPU Acceleration of Billion-Scale Similarity Search with 1-bit Quantization cites this paper.

Ascend-RaBitQ: Heterogeneous NPU-CPU Acceleration of Billion-Scale Similarity Search with 1-bit Quantization Accelerating Large-Scale Inference with Anisotropic Vector Quantization

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-19T22:12:50.655158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4c03a581-254a-45e7-a8f2-764cb3ef301f · inbound

LLM-Based User Personas for Recommendations at Scale cites this paper.

LLM-Based User Personas for Recommendations at Scale Accelerating Large-Scale Inference with Anisotropic Vector Quantization

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-07-03T13:28:18.593206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 76536953-a1da-4d59-ad2e-29c32718c19d · inbound

LLM-Based User Personas for Recommendations at Scale cites this paper.

LLM-Based User Personas for Recommendations at Scale Accelerating Large-Scale Inference with Anisotropic Vector Quantization

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T11:48:19.748054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6af0f54f-810d-4337-836e-9101de15ee9d · inbound

The Decomposition Is the Fingerprint: Per-Component Identity for Agent Skills cites this paper.

The Decomposition Is the Fingerprint: Per-Component Identity for Agent Skills Accelerating Large-Scale Inference with Anisotropic Vector Quantization

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-07-01T10:15:44.246476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d3f69538-26ab-498c-883e-0168da5f4eab · inbound

RACORN-1: Adaptive Recall-Preserving Speedup for Low-Selectivity Filtered Vector Search cites this paper.

RACORN-1: Adaptive Recall-Preserving Speedup for Low-Selectivity Filtered Vector Search Accelerating Large-Scale Inference with Anisotropic Vector Quantization

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-07-02T03:16:33.276974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 94dd7dfa-5042-4dfc-a46d-9430e95c9447 · inbound

Exploiting Structural Properties for Efficient Constraint-Aware HNSW Hyperparameter Tuning cites this paper.

Exploiting Structural Properties for Efficient Constraint-Aware HNSW Hyperparameter Tuning Accelerating Large-Scale Inference with Anisotropic Vector Quantization

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-11T16:08:01.254231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.