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Paper Citation Record · LEDGER

LARA: Lightweight Adapters in the Residual Stream for Composable Adaptation and Alignment

As of 19 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2607.28669.

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

pith.paper-citation-record.v1
2607.28669 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T00:49:11.484463Z

measured 14 of 14 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 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

14 of 14 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ca92c25a-981c-4f55-a787-5b5788769155 · outbound

This paper cites Parallel Manifold Steering: Efficient Adaptation of Large Associative Memories via Residual Energy Shaping.

LARA: Lightweight Adapters in the Residual Stream for Composable Adaptation and Alignment Parallel Manifold Steering: Efficient Adaptation of Large Associative Memories via Residual Energy Shaping

Reference 1

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T00:49:09.668362Z digest=sha256:5ce31f0dd74dd6111cc4f2c084bbd9c93b5474268356783313eb88bccbb40521

Observation f7fc089b-5117-4270-a3b5-0e0945c3a0ae · outbound

This paper cites BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models.

LARA: Lightweight Adapters in the Residual Stream for Composable Adaptation and Alignment BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models

Reference 2

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-03T00:49:09.775746Z digest=sha256:8f188be4dbbc6b3f78ebb2d27c7580b63808fb55ae76d8f2d6cd8672e086fa8d

Observation 37191e02-0d01-45c7-af6d-12224634ab63 · outbound

This paper cites A Mathematical Frame- work for Transformer Circuits.Transformer Circuits Thread, 2021.https:// transformer-circuits.pub/2021/framework/index.html.

LARA: Lightweight Adapters in the Residual Stream for Composable Adaptation and Alignment A Mathematical Frame- work for Transformer Circuits.Transformer Circuits Thread, 2021.https:// transformer-circuits.pub/2021/framework/index.html

Reference 3

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source=pdf_text observed=2026-08-03T00:49:09.928200Z digest=sha256:0bf8a06fed7d686cf585c0405ae314604c67ef049e9950f243acb34a72f6bbb2

Observation 0c53a0c7-eb27-4c7a-8fc6-be767a473499 · outbound

This paper cites Parameter-Efficient Transfer Learning for NLP.

LARA: Lightweight Adapters in the Residual Stream for Composable Adaptation and Alignment Parameter-Efficient Transfer Learning for NLP

Reference 4

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source=pdf_text observed=2026-08-03T00:49:10.039888Z digest=sha256:309b16af2288bfd04798b63ff15b5f7e164f239ab656cc1c21f90442d1ee5d25

Observation 51bc4e80-18ab-4a77-8579-618caacd410c · outbound

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

LARA: Lightweight Adapters in the Residual Stream for Composable Adaptation and Alignment LoRA: Low-Rank Adaptation of Large Language Models

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T00:49:10.146342Z digest=sha256:c6d5383152e41f1fbb37ce111129c950d08e8b8486689d5188e9a22d2b060892

Observation d03eb20c-3fea-4629-b3c7-47255db72139 · outbound

This paper cites The Power of Scale for Parameter-Efficient Prompt Tuning.

LARA: Lightweight Adapters in the Residual Stream for Composable Adaptation and Alignment The Power of Scale for Parameter-Efficient Prompt Tuning

Reference 6

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source=pdf_text observed=2026-08-03T00:49:10.300160Z digest=sha256:ca18c476185e2aea6ccb52e458c6a667fbaa7eb3a34919f4cda6f7205d638975

Observation 3a7ac19d-ecb5-4730-bdcf-c75d7f4de15f · outbound

This paper cites Prefix-Tuning: Optimizing Continuous Prompts for Generation.

LARA: Lightweight Adapters in the Residual Stream for Composable Adaptation and Alignment Prefix-Tuning: Optimizing Continuous Prompts for Generation

Reference 7

Resolution
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source=pdf_text observed=2026-08-03T00:49:10.466279Z digest=sha256:c5223b0512c3ccbaf1dd6aebc2ed9881ecc81ea8667804ee41fba2e773eada80

Observation b97e5972-d4b9-4283-8c72-3f256778053e · outbound

This paper cites Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning.

LARA: Lightweight Adapters in the Residual Stream for Composable Adaptation and Alignment Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning

Reference 8

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source=pdf_text observed=2026-08-03T00:49:10.632805Z digest=sha256:d59cb5d0f5c9fe4bdcfaabbfc836ecac715c2c783ca12a5fb828a39ce160837c

Observation 12bf32a5-ba26-411c-a24a-ebc2b7d3f13f · outbound

This paper cites AdapterFusion: Non-Destructive Task Composition for Transfer Learning.

LARA: Lightweight Adapters in the Residual Stream for Composable Adaptation and Alignment AdapterFusion: Non-Destructive Task Composition for Transfer Learning

Reference 9

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source=pdf_text observed=2026-08-03T00:49:10.786634Z digest=sha256:84b156fce8bc9a66c5618d8d679320c4f2a1ba0e366f877024b06d08405b3799

Observation 26ccd02f-7da9-439b-b85d-1962414b53a5 · outbound

This paper cites Learning multiple visual domains with residual adapters.

LARA: Lightweight Adapters in the Residual Stream for Composable Adaptation and Alignment Learning multiple visual domains with residual adapters

Reference 10

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source=pdf_text observed=2026-08-03T00:49:10.955635Z digest=sha256:3182d2bcdc67b9562a27f39d7c1aa74b80437058c21a1dedb1f5ebfbb036cf79

Observation 61672f3f-3f15-48d6-b894-bab79ceaaff6 · outbound

This paper cites S-LoRA: Serving Thousands of Concurrent LoRA Adapters.

LARA: Lightweight Adapters in the Residual Stream for Composable Adaptation and Alignment S-LoRA: Serving Thousands of Concurrent LoRA Adapters

Reference 11

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source=pdf_text observed=2026-08-03T00:49:11.071790Z digest=sha256:9eca67cad7197aadf312546edf54f12e91d75cc992f343e4bcd88326e1408742

Observation c89aca71-2f04-4d96-bb18-03d225e50678 · outbound

This paper cites LST: Ladder Side-Tuning for Parameter and Memory Efficient Transfer Learning.

LARA: Lightweight Adapters in the Residual Stream for Composable Adaptation and Alignment LST: Ladder Side-Tuning for Parameter and Memory Efficient Transfer Learning

Reference 12

Resolution
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source=pdf_text observed=2026-08-03T00:49:11.293660Z digest=sha256:8d8cea707caa73e9f22fc930f80ca69ef9c29402ba808796cb45a35e39b59aa2

Observation aa73337b-9e32-409f-baa3-1a61487fd40b · outbound

This paper cites Side-Tuning: A Baseline for Network Adaptation via Additive Side Networks.

LARA: Lightweight Adapters in the Residual Stream for Composable Adaptation and Alignment Side-Tuning: A Baseline for Network Adaptation via Additive Side Networks

Reference 13

Resolution
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source=pdf_text observed=2026-08-03T00:49:11.399918Z digest=sha256:555a613482d75e84772f72930347a431739cca8be4bb778394717c8e2ed2b80d

Observation 507daed3-bed8-4a87-b602-3f513b4099f7 · outbound

This paper cites LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention.

LARA: Lightweight Adapters in the Residual Stream for Composable Adaptation and Alignment LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention

Reference 14

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source=pdf_text observed=2026-08-03T00:49:11.484463Z digest=sha256:e1d1115466beda208431e99ad32fdb90b765a12ebb3078e07125c9a8a6a1e590

Pith citing papers

No inbound Pith citation observations are available.