Paper Citation Record · LEDGER

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law

As of 19 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 1 inbound Pith citation observation for arXiv:2506.13216.

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

pith.paper-citation-record.v1
2506.13216 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:42:03.731235Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-08T18:45:52.380042Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-09T06:15:37.236583Z

Reference resolution

40 of 40 outbound references displayed

verified exact2
verified fuzzy0
unresolved38
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 47352f9c-cfd1-471a-89fa-c9625f79d6e3 · outbound

This paper cites A Theory for Emergence of Complex Skills in Language Models.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law A Theory for Emergence of Complex Skills in Language Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T00:41:59.813968Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e890e31-a817-4159-bae8-b3921f9c860e · outbound

This paper cites an unresolved cited work.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:42:05.306194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 11ec7c3a-b7f9-4d54-bdde-1f917093e875 · outbound

This paper cites Qwen Technical Report.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Qwen Technical Report

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T00:41:59.909257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25fc96ec-49df-4f03-be97-f2646bfa24e9 · outbound

This paper cites an unresolved cited work.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Unresolved cited work

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T00:41:59.998753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7079b3dd-8e63-47e1-9d05-6742a27e85b7 · outbound

This paper cites InternLM2 Technical Report.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law InternLM2 Technical Report

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:00.044321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2aa446d-f0bc-4cca-94e7-dd482663ea6f · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Training Verifiers to Solve Math Word Problems

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:00.134273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b3bc751-9f18-48be-84e9-3321172e30f3 · outbound

This paper cites an unresolved cited work.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Unresolved cited work

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:00.178877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6bfdbe2c-2e2a-4e3f-999c-51fd69d932cc · outbound

This paper cites an unresolved cited work.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Unresolved cited work

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:00.235628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8dae9bd0-9a5c-419a-ba21-37e4a47687ba · outbound

This paper cites Understanding Emergent Abilities of Language Models from the Loss Perspective.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Understanding Emergent Abilities of Language Models from the Loss Perspective

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:00.296033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dec9ba48-7f58-444a-9747-8a5abd389b97 · outbound

This paper cites The Llama 3 Herd of Models.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law The Llama 3 Herd of Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:00.355514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b28c3092-7bbd-410f-bb9d-c04b4d123d55 · outbound

This paper cites Language models scale reliably with over-training and on downstream tasks.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Language models scale reliably with over-training and on downstream tasks

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:00.412605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07cf7857-0943-4575-b603-7eebe0d0dd09 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Measuring Massive Multitask Language Understanding

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:00.507815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab77f60b-801c-4009-b756-ae7a5a76be65 · outbound

This paper cites Training Compute-Optimal Large Language Models.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Training Compute-Optimal Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:00.563289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2efbe2d0-ff55-47a2-a639-3a4fd5af98ca · outbound

This paper cites an unresolved cited work.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:42:05.171014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation eda7acf7-2a28-433b-be37-2cafb4ae7ef0 · outbound

This paper cites an unresolved cited work.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Unresolved cited work

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:00.668869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52e2baaf-c097-4b6c-b8e1-ead68812d88d · outbound

This paper cites Scaling Laws for Neural Language Models.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Scaling Laws for Neural Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:00.722581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d6133d1-c2e2-4143-8d7f-6fd5889bdb46 · outbound

This paper cites metabench -- A Sparse Benchmark of Reasoning and Knowledge in Large Language Models.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law metabench -- A Sparse Benchmark of Reasoning and Knowledge in Large Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:00.775227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9720c97c-b729-4721-a50b-7b2d3595864e · outbound

This paper cites CMMLU: Measuring massive multitask language understanding in Chinese.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law CMMLU: Measuring massive multitask language understanding in Chinese

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:00.856511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a9f4759-c3dc-40ae-b1c3-776290aa4053 · outbound

This paper cites Holistic Evaluation of Language Models.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Holistic Evaluation of Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:00.924943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7bba15c1-ce11-4a95-b04b-30fe549d7e98 · outbound

This paper cites Rho-1: Not All Tokens Are What You Need.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Rho-1: Not All Tokens Are What You Need

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:00.976666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9e6578f-d4ed-40ce-9ac3-1696843d68e1 · outbound

This paper cites an unresolved cited work.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:42:04.948236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 58a8ccf9-add8-4a51-8a2c-a60c51a1c070 · outbound

This paper cites an unresolved cited work.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:42:04.737140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 58f4697f-35f3-479a-8a8a-6028b9f01fd9 · outbound

This paper cites an unresolved cited work.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Unresolved cited work

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:01.293638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40fd6055-0c1d-4a1c-bcc0-0685509ffc0b · outbound

This paper cites How predictable is language model benchmark performance?.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law How predictable is language model benchmark performance?

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:01.341630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c101de66-854a-412a-97a9-21b2d6f251a1 · outbound

This paper cites 100 instances is all you need: predicting the success of a new LLM on unseen data by testing on a few instances.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law 100 instances is all you need: predicting the success of a new LLM on unseen data by testing on a few instances

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:01.431425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a20a6729-266d-4ba0-812b-bb669541417c · outbound

This paper cites Efficient Benchmarking of Language Models.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Efficient Benchmarking of Language Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:01.663487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d59413fb-5a76-4f9d-9122-6bf1fde6b3a1 · outbound

This paper cites tinyBenchmarks: evaluating LLMs with fewer examples.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law tinyBenchmarks: evaluating LLMs with fewer examples

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:01.796039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c005dc66-f098-46ca-9697-9dbc9d6651ed · outbound

This paper cites Observational Scaling Laws and the Predictability of Language Model Performance.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Observational Scaling Laws and the Predictability of Language Model Performance

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:01.938683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a895cd9e-67aa-47a6-a767-fa403577897d · outbound

This paper cites Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:02.070082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6cac282e-53c0-4bbb-bb95-a84a01279c5f · outbound

This paper cites Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:02.236382Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37485b41-ca59-4384-8f7f-01f153b5156e · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Gemma 2: Improving Open Language Models at a Practical Size

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:02.352884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6fa9abe8-9111-46d4-bf28-e193f6343930 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:02.553800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87b1c8c5-13f9-4c96-aac4-392dacadbba9 · outbound

This paper cites Training Trajectories of Language Models Across Scales.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Training Trajectories of Language Models Across Scales

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:02.700113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2cbf349e-b34f-4d50-93ef-eeb2fdef00ce · outbound

This paper cites Qwen2 Technical Report.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Qwen2 Technical Report

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:02.816662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa346af3-6301-42b3-bcc5-58d20e21c54d · outbound

This paper cites How Predictable Are Large Language Model Capabilities? A Case Study on BIG-bench.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law How Predictable Are Large Language Model Capabilities? A Case Study on BIG-bench

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:42:04.171085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d48bbfed-e2c7-409b-831b-714a10103cb7 · outbound

This paper cites Yi: Open Foundation Models by 01.AI.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Yi: Open Foundation Models by 01.AI

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:03.138335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26e27fe6-c587-4a97-b013-deb39986be93 · outbound

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

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law HellaSwag: Can a Machine Really Finish Your Sentence?

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:03.322283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 011f2f21-f0f6-417f-a427-dd566d70cc5f · outbound

This paper cites Collaborative Performance Prediction for Large Language Models.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Collaborative Performance Prediction for Large Language Models

Reference 38

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:42:03.902498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ee42030b-3be9-4092-840a-3d8c134a8ab8 · outbound

This paper cites online" 'onlinestring :=.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law online" 'onlinestring :=

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:03.627047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6bcaf595-291c-452b-921b-a8ce658579dd · outbound

This paper cites write newline.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law write newline

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:03.731235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 9e7d1f0a-44e0-42cb-82f6-574c6dd46af9 · inbound

InfoLaw: Information Scaling Laws for Large Language Models with Quality-Weighted Mixture Data and Repetition cites this paper.

InfoLaw: Information Scaling Laws for Large Language Models with Quality-Weighted Mixture Data and Repetition Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:15:37.238284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.