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Paper Citation Record · LEDGER

ABLE: Representing and Mapping LLMs via Attribution-Based Large-model Embedding

As of 18 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2606.07524.

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

pith.paper-citation-record.v1
2606.07524 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-05T16:01:11.490737Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

15 of 15 outbound references displayed

  • verified exact1
  • verified fuzzy3
  • unresolved3
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch7

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f2a03c00-713a-49f9-9993-d1a6f7829b29 · outbound

This paper cites William B Johnson, Joram Lindenstrauss, and 1 others.

ABLE: Representing and Mapping LLMs via Attribution-Based Large-model Embedding William B Johnson, Joram Lindenstrauss, and 1 others

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T16:11:15.878361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-07-05T16:01:11.490737Z digest=sha256:b56a46d756a03b7ee30c53e83c2c7e8fdc0c0787fe490a22fe6027234509bd4a

Observation 8ff3b2f6-dcd9-49bb-9041-948d649bedd4 · outbound

This paper cites SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing.

ABLE: Representing and Mapping LLMs via Attribution-Based Large-model Embedding SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing

Reference 2

Resolution
metadata mismatch
local_arxiv, observed 2026-07-05T16:11:15.783030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-07-05T16:01:11.490737Z digest=sha256:b044e7228ae2bcd8e2564e478f6af5d5acde2707fff7d736740e23b2cfb9797b

Observation 8ea7b8ae-3d13-42f4-a6d4-15df4a55681c · outbound

This paper cites Qwen2 Technical Report.

ABLE: Representing and Mapping LLMs via Attribution-Based Large-model Embedding Qwen2 Technical Report

Reference 3

Resolution
metadata mismatch
local_arxiv, observed 2026-07-05T16:11:15.785861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-07-05T16:01:11.490737Z digest=sha256:14a576a06c84938355b6e378ea109801fdd53f7b1f9ecb3627c08dec1542e6a3

Observation a41a34d7-03c8-48ac-b196-b3d55ee4d82b · outbound

This paper cites Protect Your Prompts: Protocols for IP Protection in LLM Applications.

ABLE: Representing and Mapping LLMs via Attribution-Based Large-model Embedding Protect Your Prompts: Protocols for IP Protection in LLM Applications

Reference 4

Resolution
metadata mismatch
local_arxiv, observed 2026-07-05T16:11:15.769297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-07-05T16:01:11.490737Z digest=sha256:6993b1178e5b1b0838974a544ff900b5c173486e1339a79b34d198f6611721a5

Observation 25ff6adc-aaf8-4670-b11b-7ac693a6d245 · outbound

This paper cites Gradient based Feature Attribution in Explainable AI: A Technical Review.

ABLE: Representing and Mapping LLMs via Attribution-Based Large-model Embedding Gradient based Feature Attribution in Explainable AI: A Technical Review

Reference 5

Resolution
metadata mismatch
local_arxiv, observed 2026-07-05T16:11:15.779753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-07-05T16:01:11.490737Z digest=sha256:eaa84e8af9accce0aa4b49f9ef41c127de67ce3ded554b5b0719ec4016c6a162

Observation f7928dbc-0230-4bc7-9f90-3df9f0ea3c13 · outbound

This paper cites Qwen3 Technical Report.

ABLE: Representing and Mapping LLMs via Attribution-Based Large-model Embedding Qwen3 Technical Report

Reference 6

Resolution
metadata mismatch
local_arxiv, observed 2026-07-05T16:11:15.772906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-07-05T16:01:11.490737Z digest=sha256:3a40cefd0707e1afa52a136a7d025927ae2ad1ffa7b91739ed56b9fee20aad10

Observation ffb5917d-ab13-4426-99f0-e6bee7181d43 · outbound

This paper cites Phylolm: Inferring the phylogeny of large language models and predicting their performances in benchmarks.

ABLE: Representing and Mapping LLMs via Attribution-Based Large-model Embedding Phylolm: Inferring the phylogeny of large language models and predicting their performances in benchmarks

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-07-05T16:11:15.762000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-07-05T16:01:11.490737Z digest=sha256:e63b4384db15e54fa84c6ca045531375ac8366184536685c5dad8c64af965131

Observation 028946e9-6e9c-40ed-8495-bc09ce5fc56b · outbound

This paper cites A Survey of Large Language Models.

ABLE: Representing and Mapping LLMs via Attribution-Based Large-model Embedding A Survey of Large Language Models

Reference 8

Resolution
metadata mismatch
local_arxiv, observed 2026-07-05T16:11:15.765876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-07-05T16:01:11.490737Z digest=sha256:2d8a42787eb91da02e09bf38653d5f418c50bf106c7ef40571a0f63e28d96327

Observation 64a7d00e-e083-4373-9ec2-399bdca5ba76 · outbound

This paper cites EmbedLLM: Learning Compact Representations of Large Language Models.

ABLE: Representing and Mapping LLMs via Attribution-Based Large-model Embedding EmbedLLM: Learning Compact Representations of Large Language Models

Reference 9

Resolution
metadata mismatch
local_arxiv, observed 2026-07-05T16:11:15.776152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-07-05T16:01:11.490737Z digest=sha256:03bf08f933ea4ab5dae479364f25a4265fa81117964c3e5a358e0af3bd76a5b6

Observation 076535a0-717c-469f-ae66-bbd4f5e5877a · outbound

This paper cites an unresolved cited work.

ABLE: Representing and Mapping LLMs via Attribution-Based Large-model Embedding Unresolved cited work

Reference 10

Resolution
unresolved
raw_fallback, observed 2026-07-05T16:11:15.880720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-07-05T16:01:11.490737Z digest=sha256:84a1298b88881a5e46abde6cc9663b87c32cdb5b0158965bd532655b2eb87a3e

Observation a852c03d-529d-45ce-8340-ad6873b014f8 · outbound

This paper cites Then the ABLE mappingΦ :θ7→Φ(θ)is Lips- chitz continuous: ∥Φ(θ)−Φ(θ ′)∥2 ≤L∥θ−θ ′∥2, whereL=BM L ϕ.

ABLE: Representing and Mapping LLMs via Attribution-Based Large-model Embedding Then the ABLE mappingΦ :θ7→Φ(θ)is Lips- chitz continuous: ∥Φ(θ)−Φ(θ ′)∥2 ≤L∥θ−θ ′∥2, whereL=BM L ϕ

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T16:11:15.888445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-07-05T16:01:11.490737Z digest=sha256:942e51796793a949ea8a2c27a758aa9a06483134fee484efbe2875bd2f1902e5

Observation d36864a8-02ae-4463-885c-0a3f155d5bce · outbound

This paper cites an unresolved cited work.

ABLE: Representing and Mapping LLMs via Attribution-Based Large-model Embedding Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-07-05T16:11:15.885686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-07-05T16:01:11.490737Z digest=sha256:361eb00274ea6e8b7a3a71562ada572c17f8bc2b06923de177e060596a43ffb8

Observation 5837503a-ad74-47df-9ef8-2cf1ec7783a6 · outbound

This paper cites an unresolved cited work.

ABLE: Representing and Mapping LLMs via Attribution-Based Large-model Embedding Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-07-05T16:11:15.890493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-07-05T16:01:11.490737Z digest=sha256:449fc3e0a4d3c479ad866e8fc2fe199951e509fc62999e9199da4f2be8f82a99

Observation a28bbab9-ecb6-4db3-9501-6366b3d72338 · outbound

This paper cites Then the gradient field∇ xsθ(x)isM-Lipschitz continuous inθfor some constantM >0.

ABLE: Representing and Mapping LLMs via Attribution-Based Large-model Embedding Then the gradient field∇ xsθ(x)isM-Lipschitz continuous inθfor some constantM >0

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T16:11:15.875994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-07-05T16:01:11.490737Z digest=sha256:701589e999f61cb32d67e19d67d58eeafbe118355aa5b737ef437a2bca6351a6

Observation 2ef2d874-a67e-4283-a8bc-95e034c6c490 · outbound

This paper cites Conversely, dimensions beyond 256 offer only marginal gains while incur- ring higher computational and storage costs.

ABLE: Representing and Mapping LLMs via Attribution-Based Large-model Embedding Conversely, dimensions beyond 256 offer only marginal gains while incur- ring higher computational and storage costs

Reference 15

Resolution
malformed identifier
raw_fallback, observed 2026-07-05T16:11:15.883429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-07-05T16:01:11.490737Z digest=sha256:34e8ef52b605c45a38c69ccf77974940dec752a980fe2be6433035b6928a3bab

Pith citing papers

No inbound Pith citation observations are available.