Paper Citation Record · LEDGER

BitDistiller: Unleashing the Potential of Sub-4-Bit LLMs via Self-Distillation

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2402.10631.

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

pith.paper-citation-record.v1
2402.10631 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:43:49.699214Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T00:48:45.818630Z

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 0bee0ec6-1ed2-4e86-999d-400f46f30a90 · inbound

Taming Sensitive Weights : Noise Perturbation Fine-tuning for Robust LLM Quantization cites this paper.

Taming Sensitive Weights : Noise Perturbation Fine-tuning for Robust LLM Quantization BitDistiller: Unleashing the Potential of Sub-4-Bit LLMs via Self-Distillation

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T20:08:46.548503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c7bbd9e-662b-4c71-a055-6c65c17b0897 · 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 BitDistiller: Unleashing the Potential of Sub-4-Bit LLMs via Self-Distillation

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T23:03:44.578813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d430272-568b-490a-80d5-9ae523b74862 · inbound

ICQuant: Index Coding enables Low-bit LLM Quantization cites this paper.

ICQuant: Index Coding enables Low-bit LLM Quantization BitDistiller: Unleashing the Potential of Sub-4-Bit LLMs via Self-Distillation

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-16T04:43:49.699214Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3cb6aee2-6a07-482b-b315-3ac18a450963 · inbound

FPTQuant: Function-Preserving Transforms for LLM Quantization cites this paper.

FPTQuant: Function-Preserving Transforms for LLM Quantization BitDistiller: Unleashing the Potential of Sub-4-Bit LLMs via Self-Distillation

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T10:43:45.503765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd29aa23-4d4d-4923-ac68-3e36efdde6b6 · inbound

Unifying Block-wise PTQ and Distillation-based QAT for Progressive Quantization toward 2-bit Instruction-Tuned LLMs cites this paper.

Unifying Block-wise PTQ and Distillation-based QAT for Progressive Quantization toward 2-bit Instruction-Tuned LLMs BitDistiller: Unleashing the Potential of Sub-4-Bit LLMs via Self-Distillation

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T05:04:03.290534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d868afb-fdfd-45fe-bb10-ff16c7170931 · inbound

LCD: Advancing Extreme Low-Bit Clustering for Large Language Models via Knowledge Distillation cites this paper.

LCD: Advancing Extreme Low-Bit Clustering for Large Language Models via Knowledge Distillation BitDistiller: Unleashing the Potential of Sub-4-Bit LLMs via Self-Distillation

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T14:52:08.203274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ae8183d-82e0-46cc-9bf1-0bb9076891e9 · 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 BitDistiller: Unleashing the Potential of Sub-4-Bit LLMs via Self-Distillation

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.525721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01cd78bf-1d50-4303-a284-58fb525edde4 · inbound

BiVM: Accurate Binarized Neural Network for Efficient Video Matting cites this paper.

BiVM: Accurate Binarized Neural Network for Efficient Video Matting BitDistiller: Unleashing the Potential of Sub-4-Bit LLMs via Self-Distillation

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T19:54:28.682947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f314e75-ca3b-447b-9648-af25be343cd5 · inbound

SiLQ: Simple Large Language Model Quantization-Aware Training cites this paper.

SiLQ: Simple Large Language Model Quantization-Aware Training BitDistiller: Unleashing the Potential of Sub-4-Bit LLMs via Self-Distillation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:26.859827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1fa332ee-f1d5-405e-b287-ff37af7eb41d · 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 BitDistiller: Unleashing the Potential of Sub-4-Bit LLMs via Self-Distillation

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T15:52:44.893150Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5afab62d-aaad-407f-b8dc-495894eafe76 · inbound

Vec-LUT: Vector Table Lookup for Parallel Ultra-Low-Bit LLM Inference on Edge Devices cites this paper.

Vec-LUT: Vector Table Lookup for Parallel Ultra-Low-Bit LLM Inference on Edge Devices BitDistiller: Unleashing the Potential of Sub-4-Bit LLMs via Self-Distillation

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-17T00:48:45.820162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fca360e3-a349-4951-888d-83270b0534d3 · inbound

Efficient Reasoning on the Edge cites this paper.

Efficient Reasoning on the Edge BitDistiller: Unleashing the Potential of Sub-4-Bit LLMs via Self-Distillation

Reference 108

Resolution: unresolved; no resolver link, observed 2026-07-13T23:28:12.790404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d05dc86-78ed-416a-87a5-374b3f8b6f17 · inbound

Reliability Scaling Laws for Quantized Large Language Models cites this paper.

Reliability Scaling Laws for Quantized Large Language Models BitDistiller: Unleashing the Potential of Sub-4-Bit LLMs via Self-Distillation

Reference 91

Resolution: unresolved; no resolver link, observed 2026-07-14T08:45:52.855783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.