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Paper Citation Record · LEDGER

Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers

As of 14 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2412.00029.

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

pith.paper-citation-record.v1
2412.00029 v2

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T17:37:13.133120Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

19 of 19 outbound references displayed

  • verified exact1
  • verified fuzzy4
  • unresolved14
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4dfe7392-4c4f-4440-8190-4cf9cad4a226 · outbound

This paper cites Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning.

Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T17:37:13.038657Z digest=sha256:f498b1797d75f9e3f45b96605c5a183aba28b825d08b7a191136bec32b0ad1b4

Observation b603b766-1b86-41f7-990f-f439f55ed1c4 · outbound

This paper cites The pitfalls of next-token prediction.

Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers The pitfalls of next-token prediction

Reference 3

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source=pdf_text observed=2026-08-12T17:37:13.051058Z digest=sha256:240f97225e40e79f5ae54f9d56f6dd79e8bd6df7f560a7305cf8c34df91c18e2

Observation bc05d85c-87e9-43ec-9d4d-d8dc63233340 · outbound

This paper cites LoRA Learns Less and Forgets Less.

Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers LoRA Learns Less and Forgets Less

Reference 4

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source=pdf_text observed=2026-08-12T17:37:13.056300Z digest=sha256:6936b4e49721b22b34bb87017aba9ede5f31d17153bfe9d31fc7652c0ea1556d

Observation 5e7e02aa-080a-4fef-9ea3-dc19358ddf25 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers Training Verifiers to Solve Math Word Problems

Reference 5

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T17:37:13.061080Z digest=sha256:4422b4803d3a7167189659aa6b6d8ad712488d0f4dd29775ea74d834152a41c4

Observation 12b04ac9-bf12-473b-8b1f-494ab84b1f3b · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 6

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T17:37:13.066899Z digest=sha256:08c1f22e339c32dfd19f5e2a79f87a601a60d4aa96941bf5b8deab8e7170e9c5

Observation 2d31c8cb-4f29-47d0-bf32-dcbecc0ed953 · outbound

This paper cites an unresolved cited work.

Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers Unresolved cited work

Reference 7

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unresolved
raw_fallback, observed 2026-08-12T17:37:13.488622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T17:37:13.072196Z digest=sha256:b94699245c725204a04dbf9b886bd4d28e089f78123781a53adeaabb081e19d7

Observation 1726a73c-1f23-49b6-9e3f-1796d32ee0ed · outbound

This paper cites RULER: What's the Real Context Size of Your Long-Context Language Models?.

Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers RULER: What's the Real Context Size of Your Long-Context Language Models?

Reference 8

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source=pdf_text observed=2026-08-12T17:37:13.081736Z digest=sha256:a52bb8c0649108d15afa9fc5331f208015c948ed21d30c7c48a33b24a755d3be

Observation 4517a93b-4424-4a20-842a-815f1485c9d0 · outbound

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

Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers LoRA: Low-Rank Adaptation of Large Language Models

Reference 9

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T17:37:13.085869Z digest=sha256:230e15cf80a0ea7ff8a03e6afbbf7b623554083779c42d0560d56bf56fd58f44

Observation 9e3e4810-1e9d-494a-9db6-b339a39cc21c · outbound

This paper cites Textbooks Are All You Need II: phi-1.5 technical report.

Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers Textbooks Are All You Need II: phi-1.5 technical report

Reference 10

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no resolver link, observed 2026-08-12T17:37:13.090152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T17:37:13.090152Z digest=sha256:151414561108dc21f698b3f24742c2766fe7475bd4bd60d97d3c34b7a36e9de9

Observation 7d5a7532-3fcf-4c4e-b3a0-1be9a0d48c3f · outbound

This paper cites HashHop: Long Context Evaluation, 2024.

Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers HashHop: Long Context Evaluation, 2024

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T17:37:13.473227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T17:37:13.094437Z digest=sha256:db885ba2b9ff5fdf1bae2d1ae723b4f7f160cb7ad82b64c4f51719b11c378e94

Observation c4ab6a36-7cef-4164-b324-1a70f4dfb949 · outbound

This paper cites Language Models are Unsupervised Multitask Learners.

Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers Language Models are Unsupervised Multitask Learners

Reference 12

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verified fuzzy
raw_fallback, observed 2026-08-12T17:37:13.458307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T17:37:13.098683Z digest=sha256:db4cb6884200b0ed0d94240b62b4116eeb0b730ffb16761fc47f61535a1f176b

Observation 1675f53e-e596-43e0-9361-3b6dbfef5013 · outbound

This paper cites The effective rank: A measure of effective dimensionality.

Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers The effective rank: A measure of effective dimensionality

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T17:37:13.439810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T17:37:13.102702Z digest=sha256:08e212e05b22ad82a9b03da273d369192dfab8864eb4f4f3091a5844643c8253

Observation f2c47aff-6ac2-4c02-b100-9ade80244d43 · outbound

This paper cites Continual Learning of Large Language Models: A Comprehensive Survey, June.

Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers Continual Learning of Large Language Models: A Comprehensive Survey, June

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T17:37:13.417423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T17:37:13.106620Z digest=sha256:4f03b45a47f87d650458e7ac2276b22a1bae57765c7a234c5ee3936ecd974153

Observation 023e5d42-90c9-4f2f-af2c-10bf48f9dea0 · outbound

This paper cites FroSSL: Frobenius Norm Minimization for Efficient Multiview Self-Supervised Learning.

Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers FroSSL: Frobenius Norm Minimization for Efficient Multiview Self-Supervised Learning

Reference 15

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local_arxiv, observed 2026-08-12T17:37:13.246059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T17:37:13.115555Z digest=sha256:7ccc8fe3525d44715deaae403942b7bef7b23e44aaa55a5eeac1ba16641cb8af

Observation 7cf2f62d-36df-47fc-bf25-243329eef74d · outbound

This paper cites Continual Learning of Large Language Models: A Comprehensive Survey.

Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers Continual Learning of Large Language Models: A Comprehensive Survey

Reference 16

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source=pdf_text observed=2026-08-12T17:37:13.110730Z digest=sha256:8187989bc5c0e7df6b6fd57ef811970d2d8a5f66ab9affb2d3f95cabeb8473bd

Observation 77d3875c-0e56-4716-935a-e5d509fac53a · outbound

This paper cites Batched Low-Rank Adaptation of Foundation Models.

Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers Batched Low-Rank Adaptation of Foundation Models

Reference 17

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source=pdf_text observed=2026-08-12T17:37:13.125205Z digest=sha256:01da0f05932e6f18133ea2ded23918b14ca2730aa78d7936875f66992f9c5072

Observation 903710b6-f592-424e-806a-9e58992d768a · outbound

This paper cites Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM.

Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM

Reference 18

Resolution
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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T17:37:13.120746Z digest=sha256:37c237c2adf816911c80ce0e68208f22293df7ab632532ee3e427ff72727e2d5

Observation 3c80abb0-db87-4f5e-b303-8f377e29a449 · outbound

This paper cites Continual Learning with Low Rank Adaptation.

Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers Continual Learning with Low Rank Adaptation

Reference 20

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source=pdf_text observed=2026-08-12T17:37:13.133120Z digest=sha256:56c4d4ab7c6f8b0d641445f30003dbb89e6362c889704287db8d30f39a0705f4

Observation 973c2bfd-6ec2-4ff1-9dc1-1cf1c6e73fc6 · outbound

This paper cites Higher Layers Need More LoRA Experts.

Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers Higher Layers Need More LoRA Experts

Reference 2024

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source=pdf_text observed=2026-08-12T17:37:13.076797Z digest=sha256:84ec4984f2707a1ab6b71c87e3327d03aa894f63d82dc6144dd4f5553bf6408c

Pith citing papers

No inbound Pith citation observations are available.