Paper Citation Record · LEDGER

Improving Code Generation by Training with Natural Language Feedback

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 inbound Pith citation observations for arXiv:2303.16749.

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

pith.paper-citation-record.v1
2303.16749 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:34:33.035686Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

10
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 6299dcf4-484a-44a0-939d-6c8034328c3e · inbound

Teaching Large Language Models to Self-Debug cites this paper.

Teaching Large Language Models to Self-Debug Improving Code Generation by Training with Natural Language Feedback

Reference 79

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T06:24:24.799760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5b2fca4e-7d04-448d-8360-df2eabbd3101 · inbound

Search, Verify and Feedback: Towards Next Generation Post-training Paradigm of Foundation Models via Verifier Engineering cites this paper.

Search, Verify and Feedback: Towards Next Generation Post-training Paradigm of Foundation Models via Verifier Engineering Improving Code Generation by Training with Natural Language Feedback

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T18:28:46.742685Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91ae101e-4aa1-4e22-b5dc-fa35983840bc · inbound

Enhancing LLM Reasoning via Critique Models with Test-Time and Training-Time Supervision cites this paper.

Enhancing LLM Reasoning via Critique Models with Test-Time and Training-Time Supervision Improving Code Generation by Training with Natural Language Feedback

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-12T13:02:57.303363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4b4a406-c774-4134-b8bf-c809e5d3ede1 · inbound

Physics Reasoner: Knowledge-Augmented Reasoning for Solving Physics Problems with Large Language Models cites this paper.

Physics Reasoner: Knowledge-Augmented Reasoning for Solving Physics Problems with Large Language Models Improving Code Generation by Training with Natural Language Feedback

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T12:52:14.653569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7fd8dec-0564-43af-8d3d-a8422fc09754 · inbound

HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs cites this paper.

HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs Improving Code Generation by Training with Natural Language Feedback

Reference 71

Resolution: verified exact; arxiv_id, observed 2026-05-15T12:36:50.191963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 32948035-f2d1-4ee4-aef3-e32bb4c234c1 · inbound

Can ChatGPT implement finite element models for geotechnical engineering applications? cites this paper.

Can ChatGPT implement finite element models for geotechnical engineering applications? Improving Code Generation by Training with Natural Language Feedback

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-10T22:18:41.773350Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31138803-58b2-454f-9b8f-12b66c91510d · inbound

LLMs for Generation of Architectural Components: An Exploratory Empirical Study in the Serverless World cites this paper.

LLMs for Generation of Architectural Components: An Exploratory Empirical Study in the Serverless World Improving Code Generation by Training with Natural Language Feedback

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-09T11:52:34.911098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 401c170f-e5f1-4bea-91b4-84cf1145ed3d · inbound

Thinking Before Running! Efficient Code Generation with Thorough Exploration and Optimal Refinement cites this paper.

Thinking Before Running! Efficient Code Generation with Thorough Exploration and Optimal Refinement Improving Code Generation by Training with Natural Language Feedback

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T23:17:48.493851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f55c3c1-99eb-425d-9fe1-1be51ccea2f8 · inbound

kAgent: An execution-guided crash resolution agent for the Linux kernel cites this paper.

kAgent: An execution-guided crash resolution agent for the Linux kernel Improving Code Generation by Training with Natural Language Feedback

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-16T05:34:33.035686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35a2ba66-ab2b-4980-a9ce-024fd63519cc · inbound

Boosting Open-Source LLMs for Program Repair via Reasoning Transfer and LLM-Guided Reinforcement Learning cites this paper.

Boosting Open-Source LLMs for Program Repair via Reasoning Transfer and LLM-Guided Reinforcement Learning Improving Code Generation by Training with Natural Language Feedback

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-07T10:58:19.978936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c685b43b-37b2-4958-a33b-ba51977c10ff · inbound

Dr. Boot: Bootstrapping Program Synthesis Language Models to Perform Repairing cites this paper.

Dr. Boot: Bootstrapping Program Synthesis Language Models to Perform Repairing Improving Code Generation by Training with Natural Language Feedback

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T15:52:20.360202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7732469c-31f4-4770-ba0e-a1552b7e2a56 · inbound

Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges cites this paper.

Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges Improving Code Generation by Training with Natural Language Feedback

Reference 167

Resolution: unresolved; no resolver link, observed 2026-08-06T14:13:06.545208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0cbd4b5-d7da-4869-870a-400d31c3d55f · inbound

Learning from Natural Language Feedback for Personalized Question Answering cites this paper.

Learning from Natural Language Feedback for Personalized Question Answering Improving Code Generation by Training with Natural Language Feedback

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-18T22:56:53.022819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c896e01c-6493-43a0-87f8-8d18a22b97b3 · inbound

ReCode: Improving LLM-based Code Repair with Fine-Grained Retrieval-Augmented Generation cites this paper.

ReCode: Improving LLM-based Code Repair with Fine-Grained Retrieval-Augmented Generation Improving Code Generation by Training with Natural Language Feedback

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T11:39:08.190656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73710828-578b-438d-a196-25e6e404d0f4 · inbound

Themis: Training Robust Multilingual Code Reward Models for Flexible Multi-Criteria Scoring cites this paper.

Themis: Training Robust Multilingual Code Reward Models for Flexible Multi-Criteria Scoring Improving Code Generation by Training with Natural Language Feedback

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-05-09T19:35:39.085995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8d0ff704-f2d6-40d3-a85d-fc7d912416ac · inbound

Themis: Training Robust Multilingual Code Reward Models for Flexible Multi-Criteria Scoring cites this paper.

Themis: Training Robust Multilingual Code Reward Models for Flexible Multi-Criteria Scoring Improving Code Generation by Training with Natural Language Feedback

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T02:15:52.415460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.