Paper Citation Record · LEDGER

OneBit: Towards Extremely Low-bit Large Language Models

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2402.11295.

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

pith.paper-citation-record.v1
2402.11295 v6

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:46:01.284612Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T15:54:49.328128Z

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 40732215-a09e-41ab-9da8-fce2c45ab70d · inbound

Anda: Unlocking Efficient LLM Inference with a Variable-Length Grouped Activation Data Format cites this paper.

Anda: Unlocking Efficient LLM Inference with a Variable-Length Grouped Activation Data Format OneBit: Towards Extremely Low-bit Large Language Models

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-12T13:46:01.284612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32adf834-400b-4180-8ee8-7374a6b9e8db · inbound

Hamming Attention Distillation: Binarizing Keys and Queries for Efficient Long-Context Transformers cites this paper.

Hamming Attention Distillation: Binarizing Keys and Queries for Efficient Long-Context Transformers OneBit: Towards Extremely Low-bit Large Language Models

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-09T14:38:49.930687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ae27ece-5255-4b0c-b991-0cb5d2e17b75 · inbound

RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models cites this paper.

RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models OneBit: Towards Extremely Low-bit Large Language Models

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T23:03:44.696274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 401a0149-7bef-4eb7-95a5-cff96ea5e6e1 · inbound

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models cites this paper.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models OneBit: Towards Extremely Low-bit Large Language Models

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.621017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7415f28-0d79-4155-a9b3-bf1fa81e3d9f · inbound

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs cites this paper.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs OneBit: Towards Extremely Low-bit Large Language Models

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T19:09:16.636435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9312bc1-a71b-440c-9f13-65118d9f6667 · inbound

GeLaCo: An Evolutionary Approach to Layer Compression cites this paper.

GeLaCo: An Evolutionary Approach to Layer Compression OneBit: Towards Extremely Low-bit Large Language Models

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-06T17:45:20.907756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9ffc058-5768-4068-be87-316fefd80943 · inbound

Rethinking 1-bit Optimization Leveraging Pre-trained Large Language Models cites this paper.

Rethinking 1-bit Optimization Leveraging Pre-trained Large Language Models OneBit: Towards Extremely Low-bit Large Language Models

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-21T23:44:26.598786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7715ab1b-072b-4683-af15-09bc88d460a3 · inbound

APT-LLM: Exploiting Arbitrary-Precision Tensor Core Computing for LLM Acceleration cites this paper.

APT-LLM: Exploiting Arbitrary-Precision Tensor Core Computing for LLM Acceleration OneBit: Towards Extremely Low-bit Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T16:03:31.642699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a828655e-af32-44f0-91a8-547b1247e065 · inbound

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs cites this paper.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs OneBit: Towards Extremely Low-bit Large Language Models

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-05T15:52:45.067539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca793098-5702-4d56-9da1-abd372637612 · inbound

LiquidGEMM: Hardware-Efficient W4A8 GEMM Kernel for High-Performance LLM Serving cites this paper.

LiquidGEMM: Hardware-Efficient W4A8 GEMM Kernel for High-Performance LLM Serving OneBit: Towards Extremely Low-bit Large Language Models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-05T12:51:01.211009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 455bd6ae-0839-4e31-8eea-f0286653fcfb · inbound

SEPTQ: A Simple and Effective Post-Training Quantization Paradigm for Large Language Models cites this paper.

SEPTQ: A Simple and Effective Post-Training Quantization Paradigm for Large Language Models OneBit: Towards Extremely Low-bit Large Language Models

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-11T08:30:58.341686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 02b44b9c-b5b3-4f97-be6b-211e60e49bd1 · inbound

Signs Beat Floats: Low-Rank Double-Binary Adaptation for On-Device Fine-Tuning cites this paper.

Signs Beat Floats: Low-Rank Double-Binary Adaptation for On-Device Fine-Tuning OneBit: Towards Extremely Low-bit Large Language Models

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-06-30T15:54:49.329601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d615411e-6a98-4668-9e91-ff53a1bfa1f5 · inbound

Cross-Layer Error Compensation and Finite-Sample Feature-Statistics Matching for Extreme Low-Bit Quantization of Large Language Models cites this paper.

Cross-Layer Error Compensation and Finite-Sample Feature-Statistics Matching for Extreme Low-Bit Quantization of Large Language Models OneBit: Towards Extremely Low-bit Large Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T01:35:43.341032Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c712599-3bb5-41eb-a94d-9aaf89d62f69 · inbound

From Sweep to Seam: Interleaved Cross-Block Post-Training Quantization cites this paper.

From Sweep to Seam: Interleaved Cross-Block Post-Training Quantization OneBit: Towards Extremely Low-bit Large Language Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T14:28:36.431750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.