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Paper Citation Record · LEDGER

Fantastic Semantics and Where to Find Them: Investigating Which Layers of Generative LLMs Reflect Lexical Semantics

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2403.01509.

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

pith.paper-citation-record.v1
2403.01509 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 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 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:29:59.693030Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T00:39:16.230716Z

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 64afa96f-68a7-4d35-8637-7117b79dd4e5 · inbound

Token Prepending: A Training-Free Approach for Eliciting Better Sentence Embeddings from LLMs cites this paper.

Token Prepending: A Training-Free Approach for Eliciting Better Sentence Embeddings from LLMs Fantastic Semantics and Where to Find Them: Investigating Which Layers of Generative LLMs Reflect Lexical Semantics

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-11T14:53:05.947792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:53:05.947792Z digest=sha256:b99c27085fe3e60650405efa7bd1637c303bfe08c948829f2f2029d1315f86f1

Observation 4ba9b9f9-dc59-4c6d-8735-e4dd6158e53b · inbound

Emergent effects of scaling on the functional hierarchies within large language models cites this paper.

Emergent effects of scaling on the functional hierarchies within large language models Fantastic Semantics and Where to Find Them: Investigating Which Layers of Generative LLMs Reflect Lexical Semantics

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-10T20:47:13.618322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:47:13.618322Z digest=sha256:dedb0c4f813a93785d2e399448cc233ec7ee71260ac38a165ec4ac7fc401cd44

Observation ef38339d-0b30-41fa-b882-91079f074a33 · inbound

TruthFlow: Truthful LLM Generation via Representation Flow Correction cites this paper.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Fantastic Semantics and Where to Find Them: Investigating Which Layers of Generative LLMs Reflect Lexical Semantics

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-08T22:23:28.406670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:23:28.406670Z digest=sha256:667cf79f692cae36d6595ef9e63fcd39d7b3c45c63a570a655a2c5e783e01014

Observation b5c50d45-b42a-400a-93a0-6d467c86983d · inbound

Logo-LLM: Local and Global Modeling with Large Language Models for Time Series Forecasting cites this paper.

Logo-LLM: Local and Global Modeling with Large Language Models for Time Series Forecasting Fantastic Semantics and Where to Find Them: Investigating Which Layers of Generative LLMs Reflect Lexical Semantics

Reference 9

Resolution
metadata mismatch
arxiv_id, observed 2026-05-22T15:21:45.091681Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-22T15:17:13.583856Z digest=sha256:f551c164876d117242f965aac6f450f3db03d8e5e10b00a8d8f0a8fda3ca45e2

Observation 7c4a2082-60cc-44af-b04c-c21a879719b5 · inbound

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering cites this paper.

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering Fantastic Semantics and Where to Find Them: Investigating Which Layers of Generative LLMs Reflect Lexical Semantics

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-15T20:29:59.693030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:29:59.693030Z digest=sha256:5e89e618e6dabfda17d3f9acaf041c6c8668b0204fd717c5b886c57a2e738e67

Observation 9494912b-8c09-407f-8ccd-0cbc9de6a8ff · inbound

A Comprehensive Study of Decoder-Only LLMs for Text-to-Image Generation cites this paper.

A Comprehensive Study of Decoder-Only LLMs for Text-to-Image Generation Fantastic Semantics and Where to Find Them: Investigating Which Layers of Generative LLMs Reflect Lexical Semantics

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T05:20:51.123785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:20:51.123785Z digest=sha256:311abf06db0690f9158d18a30ad309919f4f2969627288e7dddce4261b7bcb51

Observation 02c42fcb-6b4e-4151-b79c-b91655505b04 · inbound

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention cites this paper.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Fantastic Semantics and Where to Find Them: Investigating Which Layers of Generative LLMs Reflect Lexical Semantics

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T04:58:52.744221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:58:52.744221Z digest=sha256:e3fc34b5379e4d611806c6cc8abf71f5b680243bab56b889ca1fc8a00034add4

Observation f85b788e-f5b3-499a-bf87-c79492fe658d · inbound

NITP: Next Implicit Token Prediction for LLM Pre-training cites this paper.

NITP: Next Implicit Token Prediction for LLM Pre-training Fantastic Semantics and Where to Find Them: Investigating Which Layers of Generative LLMs Reflect Lexical Semantics

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-06-30T12:24:39.148491Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-06-30T12:23:42.587689Z digest=sha256:beb86cfb16cc21784e7a17d9ac0543c78e5fb1f4ddf8e302908336fd904dbc5f

Observation ea25829f-329a-49e5-a596-3253dbdab3b6 · inbound

NITP: Next Implicit Token Prediction for LLM Pre-training cites this paper.

NITP: Next Implicit Token Prediction for LLM Pre-training Fantastic Semantics and Where to Find Them: Investigating Which Layers of Generative LLMs Reflect Lexical Semantics

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-07-04T00:39:16.233234Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-07-04T00:38:33.708836Z digest=sha256:dc00324fa15da898260b05a5d6fd24fe84c8036d9fb4ea0ad274bdc17e6ed504

Observation e08aa440-a3fe-4438-93b4-fc33196a1850 · inbound

NITP: Next Implicit Token Prediction for LLM Pre-training cites this paper.

NITP: Next Implicit Token Prediction for LLM Pre-training Fantastic Semantics and Where to Find Them: Investigating Which Layers of Generative LLMs Reflect Lexical Semantics

Reference 17

Resolution
unresolved
no resolver link, observed 2026-07-14T18:45:28.635910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T18:45:28.635910Z digest=sha256:f5ff1e940f835e40fb6ee247c80d001505127bdc8454f8c1c85524d1ef4596b8