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Paper Citation Record · LEDGER

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering

As of 7 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2606.06214.

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

pith.paper-citation-record.v1
2606.06214 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T00:18:29.038464Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

31 of 31 outbound references displayed

  • verified exact9
  • verified fuzzy0
  • unresolved22
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1c22b027-7fe5-4d04-83e5-275cbabb7641 · outbound

This paper cites Spinellis,Code quality: the open source perspective.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering Spinellis,Code quality: the open source perspective

Reference 1

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Observation 7c324745-80b0-429f-b4db-e9f7bc75b65d · outbound

This paper cites Improving source code readability: Theory and practice,.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering Improving source code readability: Theory and practice,

Reference 2

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Observation 115dd07e-8ba7-4466-9765-ac281851e6bd · outbound

This paper cites Learning a metric for code readability,.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering Learning a metric for code readability,

Reference 3

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Observation 40884a90-520d-436f-bd63-40f6c4538d23 · outbound

This paper cites A simpler model of software readability,.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering A simpler model of software readability,

Reference 4

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Observation e2a5e62c-4033-4726-b2a0-02e79b6d1553 · outbound

This paper cites Automatically assessing code understandability: How far are we?.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering Automatically assessing code understandability: How far are we?

Reference 5

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Observation 3ac4acb0-b03b-4a9a-bf7d-1e93f1b99b5f · outbound

This paper cites Krzysztof and U.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering Krzysztof and U

Reference 6

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Observation 2f19ef63-a330-4b9d-9e7a-9aa22644a87a · outbound

This paper cites A neural proba- bilistic language model,.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering A neural proba- bilistic language model,

Reference 7

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Observation d3952b78-46fe-4846-b16a-4037a701f43c · outbound

This paper cites code2vec: Learning distributed representations of code,.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering code2vec: Learning distributed representations of code,

Reference 8

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source=pdf_text observed=2026-06-28T00:18:29.038464Z digest=sha256:13138f1abd0818fd323ff791bcb7b0e3724ec7f9689091aebe98a5bda634c537

Observation 167f2897-1208-4a29-9b95-4afced83be37 · outbound

This paper cites A review on code generation with llms: Application and evaluation,.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering A review on code generation with llms: Application and evaluation,

Reference 9

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Observation 46314821-eef5-4594-9985-ff5e3431ef63 · outbound

This paper cites A Survey on Large Language Models for Code Generation.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering A Survey on Large Language Models for Code Generation

Reference 10

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local_arxiv, observed 2026-07-02T14:37:03.893876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation e45f043b-f677-4f41-951b-b46330909c11 · outbound

This paper cites Code readability in the age of large language models: An industrial case study from atlassian,.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering Code readability in the age of large language models: An industrial case study from atlassian,

Reference 11

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Observation 2fdb974b-2d46-4d28-9a59-d7313af6742b · outbound

This paper cites Style2code: A style-controllable code generation framework with dual-modal con- trastive representation learning,.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering Style2code: A style-controllable code generation framework with dual-modal con- trastive representation learning,

Reference 12

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 0be1429a-d542-458b-9e2b-bdd210046354 · outbound

This paper cites Representation Engineering: A Top-Down Approach to AI Transparency.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering Representation Engineering: A Top-Down Approach to AI Transparency

Reference 13

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 12c34944-dc54-46ee-9854-4f31ab1863ce · outbound

This paper cites Tradeoffs between alignment and helpfulness in language models with steering methods,.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering Tradeoffs between alignment and helpfulness in language models with steering methods,

Reference 14

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Observation 67325e35-0f3d-453a-b958-1063f53d3cc9 · outbound

This paper cites Badam: A memory efficient full parameter optimization method for large language models,.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering Badam: A memory efficient full parameter optimization method for large language models,

Reference 15

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Observation 3913ae85-96e0-48c5-8e23-909243d54d52 · outbound

This paper cites Federated full- parameter tuning of billion-sized language models with communication cost under 18 kilobytes,.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering Federated full- parameter tuning of billion-sized language models with communication cost under 18 kilobytes,

Reference 16

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Observation 97faf671-5f3a-4561-b908-196f9f7439c2 · outbound

This paper cites Full parameter fine-tuning for large language models with limited resources,.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering Full parameter fine-tuning for large language models with limited resources,

Reference 17

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Observation 6090af3d-a0d0-4563-b980-c678775a3e7f · outbound

This paper cites Qlora: Efficient finetuning of quantized llms,.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering Qlora: Efficient finetuning of quantized llms,

Reference 18

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Observation 539e959c-a18f-4474-8ef6-d6c19c774c9f · outbound

This paper cites Adaptive budget allocation for parameter-efficient fine-tuning,.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering Adaptive budget allocation for parameter-efficient fine-tuning,

Reference 19

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Observation 8a75cf58-7313-48f2-819b-4bb91c1e3933 · outbound

This paper cites Llama-adapter: Efficient fine-tuning of large language models with zero-initialized attention,.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering Llama-adapter: Efficient fine-tuning of large language models with zero-initialized attention,

Reference 20

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Observation cc2e13da-1bf4-4230-8d3c-fe03fa140849 · outbound

This paper cites Training language models to follow instructions with human feedback,.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering Training language models to follow instructions with human feedback,

Reference 21

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Observation ad9f9820-d6fe-46b7-947b-1b5160e6821d · outbound

This paper cites Rrhf: Rank responses to align language models with human feedback,.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering Rrhf: Rank responses to align language models with human feedback,

Reference 22

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Observation 26840b86-96e3-4466-be07-4553c3dee44a · outbound

This paper cites Orpo: Monolithic preference optimiza- tion without reference model,.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering Orpo: Monolithic preference optimiza- tion without reference model,

Reference 23

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Observation 644a33d1-9c1b-48ea-bd13-2774ad781bde · outbound

This paper cites Richtungsfelder und fernparallelismus in n-dimensionalen mannigfaltigkeiten,.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering Richtungsfelder und fernparallelismus in n-dimensionalen mannigfaltigkeiten,

Reference 24

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Observation f3c1dbf8-2238-4858-9844-a516fe92e668 · outbound

This paper cites Correctness Assessment of Code Generated by Large Language Models Using Internal Representations.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering Correctness Assessment of Code Generated by Large Language Models Using Internal Representations

Reference 25

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arxiv_id, observed 2026-07-02T14:37:03.897674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 29e8fd2d-c367-4107-894f-a7a596b89a07 · outbound

This paper cites Towards understanding code readability and its impact on design quality,.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering Towards understanding code readability and its impact on design quality,

Reference 26

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Observation 6382c706-7938-45bb-9886-edef65e2bef2 · outbound

This paper cites Extending Activation Steering to Broad Skills and Multiple Behaviours.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering Extending Activation Steering to Broad Skills and Multiple Behaviours

Reference 27

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arxiv_id, observed 2026-07-02T14:37:03.897399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 070a6392-2979-4c66-a99f-1803e38bbe34 · outbound

This paper cites Program Synthesis with Large Language Models.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering Program Synthesis with Large Language Models

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-28T00:18:29.038464Z digest=sha256:9a4baa4941b5ddd4c45e59139ee618b3a2d75ab00c26416c15dbac77743c7dbb

Observation 64320f00-c4c4-479b-9688-3670a4cef7e4 · outbound

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

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 29

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local_arxiv, observed 2026-07-02T14:37:03.891603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-28T00:18:29.038464Z digest=sha256:e68b15ce140cbf940e23a1a8c5febb2e7e301dbdfc98116099e1922d30668129

Observation d24ffd26-bcf2-4a71-836a-cccfda1dce90 · outbound

This paper cites Qwen2.5-Coder Technical Report.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering Qwen2.5-Coder Technical Report

Reference 30

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local_arxiv, observed 2026-07-02T14:37:03.910407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-28T00:18:29.038464Z digest=sha256:f9193232a72ac98c4de237f555249fd70e12671a5ce0a1b8c6a609ac7f8ffa24

Observation 07714056-7f1e-445e-8797-3dca289ccbcf · outbound

This paper cites Code Llama: Open Foundation Models for Code.

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering Code Llama: Open Foundation Models for Code

Reference 31

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local_arxiv, observed 2026-07-02T14:37:03.891336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Pith citing papers

No inbound Pith citation observations are available.