Pith. sign in

Paper Citation Record · LEDGER

LLM-FP4: 4-Bit Floating-Point Quantized Transformers

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2310.16836.

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

pith.paper-citation-record.v1
2310.16836 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 2026-08-09T06:31:02.800959+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:08:18.429756Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T02:06:26.972501Z

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 2324a57e-820d-4a59-baf5-e5ffa36b689a · inbound

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design cites this paper.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design LLM-FP4: 4-Bit Floating-Point Quantized Transformers

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T15:08:18.429756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:08:18.429756Z digest=sha256:37b71fd34a6fa00135eec28b377531e5a85f15ade4e82e2cb77b5449243b9432

Observation 2e530c43-7315-46f0-a0eb-0ae3f8e057a2 · inbound

Pioneering 4-Bit FP Quantization for Diffusion Models: Mixup-Sign Quantization and Timestep-Aware Fine-Tuning cites this paper.

Pioneering 4-Bit FP Quantization for Diffusion Models: Mixup-Sign Quantization and Timestep-Aware Fine-Tuning LLM-FP4: 4-Bit Floating-Point Quantized Transformers

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T13:45:43.829649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:45:43.829649Z digest=sha256:23725b8edc4fbcdc01eccd15c1e72fd37fdb168b5f5caf27a4b43bacbf7e4f8a

Observation 36bfd8de-f8c2-4a01-ab36-f0d3724f9906 · inbound

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models cites this paper.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models LLM-FP4: 4-Bit Floating-Point Quantized Transformers

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-06T22:43:57.403719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:43:57.403719Z digest=sha256:d2e705d8a276f8623aebf555fedee0e94d194080857f0f460896b20800594c57

Observation 890a1171-f933-4662-951e-180cecf31f3a · inbound

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration cites this paper.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration LLM-FP4: 4-Bit Floating-Point Quantized Transformers

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-06T11:15:33.980434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:15:33.980434Z digest=sha256:03fa381eacbc5ea97bf7782d66037be708e9eea8d2ddef3f244653018582ec1d

Observation 11fdd9e4-c41d-4afb-8553-55c8972b8e15 · inbound

Four Over Six: More Accurate NVFP4 Quantization with Adaptive Block Scaling cites this paper.

Four Over Six: More Accurate NVFP4 Quantization with Adaptive Block Scaling LLM-FP4: 4-Bit Floating-Point Quantized Transformers

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-17T02:23:52.799774Z

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.

source=pdf_text observed=2026-05-17T02:23:01.845123Z digest=sha256:a8e74ddfae69f4fa0dece5a839672a5ec222f07050c236f4e675fa8f38c402aa

Observation 07301f2b-70f3-412c-beed-4f5fcaa9d863 · inbound

Balancing FP8 Computation Accuracy and Efficiency on Digital CIM via Shift-Aware On-the-fly Aligned-Mantissa Bitwidth Prediction cites this paper.

Balancing FP8 Computation Accuracy and Efficiency on Digital CIM via Shift-Aware On-the-fly Aligned-Mantissa Bitwidth Prediction LLM-FP4: 4-Bit Floating-Point Quantized Transformers

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-21T13:54:11.571256Z

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.

source=pdf_text observed=2026-05-21T13:50:18.114223Z digest=sha256:bcd2206ee8820a70432b7c22c847d685d905b3f5a341e78df5e6249391384e9d

Observation ce62154b-2599-4b03-8489-f9767284ae82 · inbound

LBLLM: Lightweight Binarization of Large Language Models via Three-Stage Distillation cites this paper.

LBLLM: Lightweight Binarization of Large Language Models via Three-Stage Distillation LLM-FP4: 4-Bit Floating-Point Quantized Transformers

Reference 33

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T12:46:04.735239Z

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.

source=arxiv_source observed=2026-05-10T03:04:14.900791Z digest=sha256:e9167f0cb0e6ad85ecb4483d4bc9a7b903193ebd4712dccfa1fbb05dc98ee190

Observation 25408452-67d5-48a3-89bd-ff1d5243257f · inbound

StatQAT: Statistical Quantizer Optimization for Deep Networks cites this paper.

StatQAT: Statistical Quantizer Optimization for Deep Networks LLM-FP4: 4-Bit Floating-Point Quantized Transformers

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-20T01:22:55.759536Z

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.

source=pdf_text observed=2026-05-20T01:20:06.033991Z digest=sha256:a2fdbb9308eafeccf896bd77b25582c7424173e3f92c12a840fd664656662dfb

Observation 124fc26e-1dcb-4307-b0c2-b8ccde03095f · inbound

LiftQuant: Continuous Bit-Width LLM via Dimensional Lifting and Projection cites this paper.

LiftQuant: Continuous Bit-Width LLM via Dimensional Lifting and Projection LLM-FP4: 4-Bit Floating-Point Quantized Transformers

Reference 56

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T02:06:26.974312Z

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.

source=arxiv_source observed=2026-06-28T11:14:03.535306Z digest=sha256:bb069947be79b7747654d5bb65cfa2280823617ce62c4c0cb3018e818e0bf932

Observation e43ff9b1-7882-4250-b931-cc879970e0bf · inbound

LiftQuant: Continuous Bit-Width LLM via Dimensional Lifting and Projection cites this paper.

LiftQuant: Continuous Bit-Width LLM via Dimensional Lifting and Projection LLM-FP4: 4-Bit Floating-Point Quantized Transformers

Reference 56

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T11:24:38.288399Z

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.

source=arxiv_source observed=2026-06-30T11:17:53.736872Z digest=sha256:ac1bcc9945d20cbabcc84274349ab42f72ac7ecc47c8bae52d5ba40742d52c60

Observation 24bc865a-0128-415d-87f9-e41886342922 · inbound

FlipGuard: Defending Large Language Models Against Quantization-Conditioned Backdoor Attacks cites this paper.

FlipGuard: Defending Large Language Models Against Quantization-Conditioned Backdoor Attacks LLM-FP4: 4-Bit Floating-Point Quantized Transformers

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-06-30T09:44:37.644081Z

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.

source=pdf_text observed=2026-06-30T09:39:35.673341Z digest=sha256:9df856cf563426dc5aeca5a9080310bf91cbf98eabd40dfa770fc514ac379661

Observation 0c3c5375-3baf-4474-aa13-bc64a22eb754 · inbound

Breaking the Rounding Trap: Securing LLMs against Quantization-Conditioned Backdoors cites this paper.

Breaking the Rounding Trap: Securing LLMs against Quantization-Conditioned Backdoors LLM-FP4: 4-Bit Floating-Point Quantized Transformers

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-06-30T08:04:28.687869Z

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.

source=pdf_text observed=2026-06-30T07:47:18.350953Z digest=sha256:20e07c3cd0a4cc4f9a1feb8a6fa623c592961c7f3fb93e87f7b20b9a664bb929

Observation 6e5740c5-124e-4846-b72f-8571c5924488 · inbound

Breaking the Rounding Trap: Securing LLMs against Quantization-Conditioned Backdoors cites this paper.

Breaking the Rounding Trap: Securing LLMs against Quantization-Conditioned Backdoors LLM-FP4: 4-Bit Floating-Point Quantized Transformers

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-04T04:39:06.862258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T04:39:06.862258Z digest=sha256:1cedfd63eae2fc2a483b23b3683af94b61352089f340e4270af2ce1a5235390b