Paper Citation Record · LEDGER

An Uncertainty-Driven Adaptive Self-Alignment Framework for Large Language Models

As of 7 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2507.17477.

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

pith.paper-citation-record.v1
2507.17477 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:51:53.952177Z

measured 16 of 16 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

16 of 16 outbound references displayed

verified exact1
verified fuzzy1
unresolved13
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d9f452de-6484-4650-8ac8-4dc432d20603 · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

An Uncertainty-Driven Adaptive Self-Alignment Framework for Large Language Models Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T14:51:53.876730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ec1677e-173c-4452-ab99-ce10bfeee767 · outbound

This paper cites AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback.

An Uncertainty-Driven Adaptive Self-Alignment Framework for Large Language Models AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T14:51:53.887056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 127026c0-8cac-4e56-8dab-bc8135c815b9 · outbound

This paper cites A Survey on LLM-as-a-Judge.

An Uncertainty-Driven Adaptive Self-Alignment Framework for Large Language Models A Survey on LLM-as-a-Judge

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T14:51:53.897189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67fc20bf-b56c-4f14-b0af-09e89d27fd30 · outbound

This paper cites In Findings of the Association for Computational Linguistics: EMNLP 2023, 1827–1843.

An Uncertainty-Driven Adaptive Self-Alignment Framework for Large Language Models In Findings of the Association for Computational Linguistics: EMNLP 2023, 1827–1843

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:51:54.262964Z

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.

Observation 6382da76-56cf-4159-8dc2-1212cab5262a · outbound

This paper cites Self-Alignment with Instruction Backtranslation.

An Uncertainty-Driven Adaptive Self-Alignment Framework for Large Language Models Self-Alignment with Instruction Backtranslation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T14:51:53.906648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24dd0aff-eef4-4a8e-96b9-7f80e2cecc0e · outbound

This paper cites Direct Large Language Model Alignment Through Self-Rewarding Contrastive Prompt Distillation.

An Uncertainty-Driven Adaptive Self-Alignment Framework for Large Language Models Direct Large Language Model Alignment Through Self-Rewarding Contrastive Prompt Distillation

Reference 8

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T14:51:54.133971Z

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.

Observation f33b3faf-0178-4336-88d6-54b15dfb402f · outbound

This paper cites Introspection of Thought Helps AI Agents.

An Uncertainty-Driven Adaptive Self-Alignment Framework for Large Language Models Introspection of Thought Helps AI Agents

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-06T14:51:54.094232Z

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.

Observation 0bf4edc5-10f1-4229-9d4b-44e5c765679f · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

An Uncertainty-Driven Adaptive Self-Alignment Framework for Large Language Models LLaMA: Open and Efficient Foundation Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T14:51:53.926789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 683d0c86-dafd-4339-a684-3a392aceb7fc · outbound

This paper cites Aligning Large Language Models with Human: A Survey.

An Uncertainty-Driven Adaptive Self-Alignment Framework for Large Language Models Aligning Large Language Models with Human: A Survey

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T14:51:53.937236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a825a60e-9c20-484b-8f8e-b275348c27c4 · outbound

This paper cites WizardLM: Empowering large pre-trained language models to follow complex instructions.

An Uncertainty-Driven Adaptive Self-Alignment Framework for Large Language Models WizardLM: Empowering large pre-trained language models to follow complex instructions

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T14:51:53.942106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 15544518-1539-46af-8437-ddc700acba52 · outbound

This paper cites Is DPO Superior to PPO for LLM Alignment? A Comprehensive Study.

An Uncertainty-Driven Adaptive Self-Alignment Framework for Large Language Models Is DPO Superior to PPO for LLM Alignment? A Comprehensive Study

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T14:51:53.947284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ef33d82-3afb-4942-8a18-8c3bbd3e0cd9 · outbound

This paper cites Universal and Transferable Adversarial Attacks on Aligned Language Models.

An Uncertainty-Driven Adaptive Self-Alignment Framework for Large Language Models Universal and Transferable Adversarial Attacks on Aligned Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T14:51:53.952177Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c91da848-c265-490a-b8c8-6d22233cf1e0 · outbound

This paper cites Self-Instruct: Aligning Language Models with Self-Generated Instructions.

An Uncertainty-Driven Adaptive Self-Alignment Framework for Large Language Models Self-Instruct: Aligning Language Models with Self-Generated Instructions

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-06T14:51:53.931911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ba2da3a-e755-45ca-9dc8-d23e961b9887 · outbound

This paper cites CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing.

An Uncertainty-Driven Adaptive Self-Alignment Framework for Large Language Models CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-06T14:51:53.891871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5cfc4125-e680-40b5-a92e-460c7f25c0e2 · outbound

This paper cites Towards Scalable Automated Alignment of LLMs: A Survey.

An Uncertainty-Driven Adaptive Self-Alignment Framework for Large Language Models Towards Scalable Automated Alignment of LLMs: A Survey

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-06T14:51:53.882193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a2c7525e-f57a-4177-8dbb-6d34d5c89c49 · outbound

This paper cites DatasetAgent: A Novel Multi-Agent System for Auto-Constructing Datasets from Real-World Images.

An Uncertainty-Driven Adaptive Self-Alignment Framework for Large Language Models DatasetAgent: A Novel Multi-Agent System for Auto-Constructing Datasets from Real-World Images

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-06T14:51:53.917494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.