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Paper Citation Record · LEDGER

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models

As of 17 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 2 inbound Pith citation observations for arXiv:2512.18934.

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

pith.paper-citation-record.v1
2512.18934 v2

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T14:52:20.978146Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T05:36:27.389766Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-04T12:59:52.809074Z

Reference resolution

26 of 26 outbound references displayed

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  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 59c67b02-ca42-435a-9bfd-4b11e4f74ed5 · outbound

This paper cites Post-training 4-bit quantization of convolution networks for rapid-deployment.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models Post-training 4-bit quantization of convolution networks for rapid-deployment

Reference 1

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source=pdf_text observed=2026-08-03T14:52:19.128097Z digest=sha256:aefcc0820373e101b3223174c056d8bb8464be208e5203f59538e71d17839e0f

Observation b741da97-7a17-48f3-800c-b46a46646581 · outbound

This paper cites Experience Grounds Language.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models Experience Grounds Language

Reference 2

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source=pdf_text observed=2026-08-03T14:52:19.195657Z digest=sha256:3b1e8300ef6ca457f244d5fd1b0db07b7e1927fb32ed73770e420fd3c4564da9

Observation 9aeb714c-fb05-4e12-955a-b935da78319e · outbound

This paper cites Ex-Model: Continual Learning from a Stream of Trained Models.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models Ex-Model: Continual Learning from a Stream of Trained Models

Reference 3

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source=pdf_text observed=2026-08-03T14:52:19.354739Z digest=sha256:628c9c92038ff25294212d0e0c76c019e83431c1b07d3ee13ec8692a5ccade81

Observation 200d27c9-eeff-42ab-adb2-ae53d2e88182 · outbound

This paper cites On Tiny Episodic Memories in Continual Learning.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models On Tiny Episodic Memories in Continual Learning

Reference 4

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source=pdf_text observed=2026-08-03T14:52:19.420000Z digest=sha256:91f14a9307db3a7f78978c9c0d33360f3f4a60a1638d41bf889af47c43e13374

Observation 651af4f7-43d7-4099-a172-8d4d9e1e590c · outbound

This paper cites Evaluating Large Language Models Trained on Code.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models Evaluating Large Language Models Trained on Code

Reference 5

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source=pdf_text observed=2026-08-03T14:52:19.473060Z digest=sha256:9acaf518aad33a7606137b32d18201180ac9a2ffa0d0e0aa73902bde8e53ab6b

Observation 77776c8a-b75a-4ce5-97f7-57c317815809 · outbound

This paper cites Overcoming forgetting catastrophe in quantization-aware training.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models Overcoming forgetting catastrophe in quantization-aware training

Reference 6

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source=pdf_text observed=2026-08-03T14:52:19.560273Z digest=sha256:813bf9edfe441c454288daff427d76815fd346a95689284cde1105bfbac6c229

Observation ba7a2cac-08c9-4e1d-a527-af98616f0c9f · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 7

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source=pdf_text observed=2026-08-03T14:52:19.622756Z digest=sha256:0bf262b32a4e19a0a45d19015cb056ba59783069f2df90a8906eb1724e50193a

Observation 26e4a2bb-7bcc-411a-a1a5-273f9b81df4c · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models Training Verifiers to Solve Math Word Problems

Reference 8

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source=pdf_text observed=2026-08-03T14:52:19.684996Z digest=sha256:bdc06d5f44d97b2af318362dc2cee160ddb4cdf6449aeb6ac821bb3fde6a1295

Observation 14e0117f-6c35-4359-a242-a7646836cf89 · outbound

This paper cites LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale

Reference 9

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source=pdf_text observed=2026-08-03T14:52:19.745055Z digest=sha256:417addff8fd8da53c369b13ca769c7db5500bae5f3d45384a93faa9a8d7d34bb

Observation f61e057b-ad46-4ba0-92f0-230c6f43287b · outbound

This paper cites 8-bit Optimizers via Block-wise Quantization.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models 8-bit Optimizers via Block-wise Quantization

Reference 10

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source=pdf_text observed=2026-08-03T14:52:19.865798Z digest=sha256:0bc149a532b99198039444212552724ba6927249642b5cdf119ef927bd93b348

Observation 419839c0-5292-4ba6-826a-172bccbb3f19 · outbound

This paper cites GFlowNet-EM for learning compositional latent variable models.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models GFlowNet-EM for learning compositional latent variable models

Reference 11

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source=pdf_text observed=2026-08-03T14:52:19.945390Z digest=sha256:58fe7d55e75c539e86c2f9fb4303ad57dcd8af1ec76853fa6af78c774390a7d5

Observation ddf067c8-4ff3-463c-b47c-01cb6f3dccd3 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models LoRA: Low-Rank Adaptation of Large Language Models

Reference 12

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source=pdf_text observed=2026-08-03T14:52:19.997623Z digest=sha256:5c8321b6234beae82fd4f5f5aff24f6ad01de52261d149f735d36c185d067304

Observation 8075e9ef-40bb-4055-9e95-ddbaac3ab9f7 · outbound

This paper cites Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference

Reference 13

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source=pdf_text observed=2026-08-03T14:52:20.058797Z digest=sha256:248cb1f1a021d941542c04301f41e05f241d5700b6fe26923edcc6cc1a658c33

Observation 4978a2e6-4819-4667-9c40-590e26f86048 · outbound

This paper cites Overcoming catastrophic forgetting in neural networks.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models Overcoming catastrophic forgetting in neural networks

Reference 14

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source=pdf_text observed=2026-08-03T14:52:20.116377Z digest=sha256:f8d600bba956488fa454c6e7bbe70bb2763bb33cb124f4361c46cc9b310a4d96

Observation fc8acdc0-b001-485f-8c4d-72213b2bba8f · outbound

This paper cites Learning without Forgetting.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models Learning without Forgetting

Reference 15

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source=pdf_text observed=2026-08-03T14:52:20.172508Z digest=sha256:d7a144898c5dbd82638fab5d6fc2e1f2df3fc7897af6852b131d1aef8e17ead0

Observation 9545f3d2-f0c5-4be3-b776-e0729130c1cc · outbound

This paper cites A Structured Self-attentive Sentence Embedding.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models A Structured Self-attentive Sentence Embedding

Reference 16

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source=pdf_text observed=2026-08-03T14:52:20.223881Z digest=sha256:b3ac4aeb585030ecdc480792504de416077c4e14a63af937106efeb8591caaa0

Observation c4374c4b-c987-44eb-ac72-a7c864889dc1 · outbound

This paper cites Gradient Episodic Memory for Continual Learning.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models Gradient Episodic Memory for Continual Learning

Reference 17

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source=pdf_text observed=2026-08-03T14:52:20.268370Z digest=sha256:28293d200b80a82b8fb542cf494a08e369ee67477ef4357e1c315287c40ce65f

Observation 9b962a08-632d-407b-b32b-47711dcd898e · outbound

This paper cites An Empirical Study of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models An Empirical Study of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning

Reference 18

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source=pdf_text observed=2026-08-03T14:52:20.319003Z digest=sha256:0c64f91d84f9fad7419cad4f61b0219860aa4e2bac9e7ae5b93af22c6445d1e9

Observation c8d77d7d-87b5-43b4-8938-479949cd4a24 · outbound

This paper cites Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights

Reference 19

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source=pdf_text observed=2026-08-03T14:52:20.376800Z digest=sha256:ef7b198633354dbd2a0e9c0505f42f90e2e46a893d3774e92c6b8ec2982224ce

Observation ecbab376-0db1-4880-8dd8-f7b0df148272 · outbound

This paper cites Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering

Reference 20

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source=pdf_text observed=2026-08-03T14:52:20.497986Z digest=sha256:bcbba53a5ed788fe822dbd3de76577ce65344b6dc354b746502f601c7fd14a8a

Observation acdebb15-a577-4064-bbf7-35ce70bb709a · outbound

This paper cites iCaRL: Incremental Classifier and Representation Learning.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models iCaRL: Incremental Classifier and Representation Learning

Reference 21

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source=pdf_text observed=2026-08-03T14:52:20.589314Z digest=sha256:e76286bd63189b8a4d31cf84c13f3baa2b3575cc6ad7ecd7231458d1c41ef468

Observation cc272b12-1569-4d04-a75b-dbec69fbab4f · outbound

This paper cites WinoGrande: An Adversarial Winograd Schema Challenge at Scale.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models WinoGrande: An Adversarial Winograd Schema Challenge at Scale

Reference 22

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source=pdf_text observed=2026-08-03T14:52:20.652223Z digest=sha256:0c21983dbb05e4377fb6d0a55c2b0176e578e7267bda2253ebaa28cb6d6dc1d6

Observation 788744fc-b16c-4115-b805-35d56fad9ee3 · outbound

This paper cites SocialIQA: Commonsense Reasoning about Social Interactions.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models SocialIQA: Commonsense Reasoning about Social Interactions

Reference 23

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source=pdf_text observed=2026-08-03T14:52:20.746473Z digest=sha256:8a9366bfd040bc1b7fb5d8fbb9773cb04299c83d1d7db482c05f0a60e9af8924

Observation 7ba31c96-c618-47ac-bdd2-875181b14ba0 · outbound

This paper cites HellaSwag: Can a Machine Really Finish Your Sentence?.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models HellaSwag: Can a Machine Really Finish Your Sentence?

Reference 24

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source=pdf_text observed=2026-08-03T14:52:20.812688Z digest=sha256:d2c624651b552800420e1595766c723c33a3b10c927e1e1455d4c72c8f4ca3d9

Observation 076f7d42-6fad-4413-a4b0-f861bceffed6 · outbound

This paper cites Continual Learning Through Synaptic Intelligence.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models Continual Learning Through Synaptic Intelligence

Reference 25

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source=pdf_text observed=2026-08-03T14:52:20.913287Z digest=sha256:1c972f81528b1205728bdaef899de23f9db4ad6bec285f547772f4d483caa483

Observation fd2ee2a6-09cc-499d-95e1-3f1a7c59771b · outbound

This paper cites LoRI: Reducing Cross-Task Interference in Multi-Task Low-Rank Adaptation.

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models LoRI: Reducing Cross-Task Interference in Multi-Task Low-Rank Adaptation

Reference 26

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source=pdf_text observed=2026-08-03T14:52:20.978146Z digest=sha256:8edbf14064d026db5ae91ab23c15314d6935778b3554c77e66406fb7b890dce1

Pith citing papers

Observation 5752d74c-4814-4823-a2cb-01b0d5dcad2c · inbound

SuperLocalMemory V3.3: The Living Brain -- Biologically-Inspired Forgetting, Cognitive Quantization, and Multi-Channel Retrieval for Zero-LLM Agent Memory Systems cites this paper.

SuperLocalMemory V3.3: The Living Brain -- Biologically-Inspired Forgetting, Cognitive Quantization, and Multi-Channel Retrieval for Zero-LLM Agent Memory Systems When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models

Reference 3

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arxiv_id, observed 2026-07-02T01:17:26.518557Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-10T19:48:34.606351Z digest=sha256:286949261ae1132a205cf433932fd3c1cfb1733ad6f885a8b377fd7b579341e6

Observation db0373e1-1d38-4ba7-afcd-b510f6838c8e · inbound

What Survives When You Compress a Recursive Reasoner for the Edge? cites this paper.

What Survives When You Compress a Recursive Reasoner for the Edge? When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models

Reference 30

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local_arxiv, observed 2026-07-04T12:59:52.810512Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-06-26T05:36:27.389766Z digest=sha256:80db395a01cc095c5c748a18a024829b4ef68fa95c30deccf12207ca86fa47db