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Paper Citation Record · LEDGER

Super Weights in LLMs and the Failure of Selective Training

As of 10 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2607.08733.

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

pith.paper-citation-record.v1
2607.08733 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-10T02:26:06.457776Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

17 of 17 outbound references displayed

  • verified exact2
  • verified fuzzy12
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a0a8abeb-2053-4019-9092-1b42944753ed · outbound

This paper cites Intrinsic dimensionality explains the effectiveness of language model fine-tuning.

Super Weights in LLMs and the Failure of Selective Training Intrinsic dimensionality explains the effectiveness of language model fine-tuning

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T02:26:43.143871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-10T02:26:06.457776Z digest=sha256:f82d0bfdb4a31647e54a9c52dd372784623dfb566e9cada6f2900fb4908c4269

Observation a3f4058f-d427-4686-a6f3-52ab0e7e9cbe · outbound

This paper cites Systematic Outliers in Large Language Models.

Super Weights in LLMs and the Failure of Selective Training Systematic Outliers in Large Language Models

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-07-10T02:26:42.779156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-10T02:26:06.457776Z digest=sha256:e6144430605d75a700c2956819fad650d4670f72136918df5c6e94bb8d2ede50

Observation f2b77621-530d-4b1a-b52f-664713cad9fe · outbound

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

Super Weights in LLMs and the Failure of Selective Training Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-07-10T02:26:42.774803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-10T02:26:06.457776Z digest=sha256:0a7a782ae8d98bfcf2fba39be1b15a184663b9ebc4567ab6ed6cd09abc966e0e

Observation c6e8e3b4-f2e3-4777-8640-cfe2a4a889b0 · outbound

This paper cites GPT3.int8() : 8-bit matrix multiplication for transformers at scale.

Super Weights in LLMs and the Failure of Selective Training GPT3.int8() : 8-bit matrix multiplication for transformers at scale

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T02:26:43.133504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-10T02:26:06.457776Z digest=sha256:e64d70a35dcf2cb528baf953578b12356d7b8b228fb6c93e81fef998869796b7

Observation ff173f1a-fbb0-4a46-922a-5cdd91c0f1cb · outbound

This paper cites [Fou23] Nicolas Fournier.

Super Weights in LLMs and the Failure of Selective Training [Fou23] Nicolas Fournier

Reference 5

Resolution
metadata mismatch
arxiv_id, observed 2026-07-10T02:26:42.770708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-10T02:26:06.457776Z digest=sha256:b113658072506cbb3abc0a921a3bd96b06f3283f31f4c347a040d49ab276050c

Observation 8226ece8-143b-4959-92ff-4e618bbf3f60 · outbound

This paper cites OLMo : Accelerating the science of language models.

Super Weights in LLMs and the Failure of Selective Training OLMo : Accelerating the science of language models

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T02:26:43.127977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-10T02:26:06.457776Z digest=sha256:e6a1436331a2f7ac87aba5e7f68195585d9c4facc4379f90c529f9ea71245c5f

Observation 18b1d65e-1866-409d-a29b-39e246318568 · outbound

This paper cites LoRA : Low-rank adaptation of large language models.

Super Weights in LLMs and the Failure of Selective Training LoRA : Low-rank adaptation of large language models

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T02:26:43.126021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-10T02:26:06.457776Z digest=sha256:f3014cbc7e7b2978e6b87af0e9d0570e1d44816638d6f11c9d9ca749eddaf436

Observation 613a7e7d-62cb-44de-9543-beaa55a1613a · outbound

This paper cites The emergence of essential sparsity in large pre-trained models: The weights that matter.

Super Weights in LLMs and the Failure of Selective Training The emergence of essential sparsity in large pre-trained models: The weights that matter

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T02:26:43.140719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-10T02:26:06.457776Z digest=sha256:9255fc45c271f7a9ac0a24d3d67a2dc76b8c213f750ff9de210303baad0b04fd

Observation 1fa34088-dd81-4eb1-8876-f794b7979979 · outbound

This paper cites On relation-specific neurons in large language models.

Super Weights in LLMs and the Failure of Selective Training On relation-specific neurons in large language models

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T02:26:43.129809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-10T02:26:06.457776Z digest=sha256:17021855bdf37be69901489fa586277b886a5ae351cc69348be5ddee55df9450

Observation 918d72e4-cf13-45be-bd16-c3e2f2cd2c61 · outbound

This paper cites Pointer sentinel mixture models.

Super Weights in LLMs and the Failure of Selective Training Pointer sentinel mixture models

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T02:26:43.142202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-10T02:26:06.457776Z digest=sha256:d50c2ff88cf0606a64403f26b52f32b07f1b2655c405eced18900908d9a23236

Observation 0a54edfb-eee5-4f3f-a28c-4de355db50d7 · outbound

This paper cites Morris, Niloofar Mireshghallah, Mark Ibrahim, and Saeed Mahloujifar.

Super Weights in LLMs and the Failure of Selective Training Morris, Niloofar Mireshghallah, Mark Ibrahim, and Saeed Mahloujifar

Reference 11

Resolution
metadata mismatch
arxiv_id, observed 2026-07-10T02:26:42.777802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-10T02:26:06.457776Z digest=sha256:2b85245359dff3707f577f259fae55bc9f6970cef1221668cccd9080d2163445

Observation 0793b112-447a-467f-b3c2-81f2030b99a0 · outbound

This paper cites WinoGrande : An adversarial winograd schema challenge at scale.

Super Weights in LLMs and the Failure of Selective Training WinoGrande : An adversarial winograd schema challenge at scale

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T02:26:43.146078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-10T02:26:06.457776Z digest=sha256:b1464e7fc5bda89cc3a127e1101c1018c2cd73b3980b402e02024f1624fa1339

Observation 8270d540-b70e-4ff5-9455-ebf0af5ea9cc · outbound

This paper cites Maximum-margin matrix factorization.

Super Weights in LLMs and the Failure of Selective Training Maximum-margin matrix factorization

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T02:26:43.142406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-10T02:26:06.457776Z digest=sha256:16da57d4b7c8da95a82e2041a2757d23a6a584ba23e0f108275b07c21766fdd0

Observation 21992097-4b64-4a36-960d-b6419e7797d9 · outbound

This paper cites Massive activations in large language models.

Super Weights in LLMs and the Failure of Selective Training Massive activations in large language models

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T02:26:43.144085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-10T02:26:06.457776Z digest=sha256:8f0faf88bab4f2fb5919271892083d8381443fc38d039c67599f8a876f9bf6a3

Observation b345d8bb-1f66-427e-8488-41ef38298df2 · outbound

This paper cites The Super Weight in Large Language Models.

Super Weights in LLMs and the Failure of Selective Training The Super Weight in Large Language Models

Reference 15

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T02:26:42.780422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-10T02:26:06.457776Z digest=sha256:5c5e42c8380dc21d43f299591abb0c8e564039c22c8ce2be2b0580feb2e0a83f

Observation f8bcc10c-e703-4665-a259-2ce32a4d52c3 · outbound

This paper cites BitFit : Simple parameter-efficient fine-tuning for transformer-based masked language-models.

Super Weights in LLMs and the Failure of Selective Training BitFit : Simple parameter-efficient fine-tuning for transformer-based masked language-models

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T02:26:43.137283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-10T02:26:06.457776Z digest=sha256:198de7dd1481fe6c0b09989589bf0bd8136447f8523e1dd9ad5451a8485e6426

Observation a812e5ef-4241-49a7-b0d7-6c225253bcd9 · outbound

This paper cites Adaptive budget allocation for parameter-efficient fine-tuning.

Super Weights in LLMs and the Failure of Selective Training Adaptive budget allocation for parameter-efficient fine-tuning

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T02:26:43.138983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-10T02:26:06.457776Z digest=sha256:8bb74629e4dbbae9eb34ee8e9ca591c04abdf6b575617ed199a787b42a8c07e9

Pith citing papers

No inbound Pith citation observations are available.