Paper Citation Record · LEDGER

Revisiting Compositional Generalization Capability of Large Language Models Considering Instruction Following Ability

As of 14 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 1 inbound Pith citation observation for arXiv:2506.15629.

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

pith.paper-citation-record.v1
2506.15629 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:57:40.694596Z

measured 15 of 15 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T04:30:43.189580Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T04:30:48.754585Z

Reference resolution

14 of 14 outbound references displayed

verified exact0
verified fuzzy3
unresolved9
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0076b84d-9800-459d-bfb0-e891237f7221 · outbound

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

Revisiting Compositional Generalization Capability of Large Language Models Considering Instruction Following Ability DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T23:57:40.032102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69c3db94-30a5-4a9c-b9b2-b7832dff1810 · outbound

This paper cites The Flan Collection: Designing Data and Methods for Effective Instruction Tuning.

Revisiting Compositional Generalization Capability of Large Language Models Considering Instruction Following Ability The Flan Collection: Designing Data and Methods for Effective Instruction Tuning

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T23:57:40.162587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76f9fbe1-bc22-419c-87c7-f008cc97567d · outbound

This paper cites Qwen2.5 Technical Report.

Revisiting Compositional Generalization Capability of Large Language Models Considering Instruction Following Ability Qwen2.5 Technical Report

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T23:57:40.298421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5812209e-114e-4228-8f7f-ae839b172c2d · outbound

This paper cites In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: Industry Track, pages 294– 305, Abu Dhabi, UAE.

Revisiting Compositional Generalization Capability of Large Language Models Considering Instruction Following Ability In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: Industry Track, pages 294– 305, Abu Dhabi, UAE

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:57:41.843620Z

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.

Observation bbcb41cf-a78a-41b6-8a4f-bab3058c77d5 · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

Revisiting Compositional Generalization Capability of Large Language Models Considering Instruction Following Ability Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T23:57:40.424363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f78eb45-bea9-4bee-8e5f-e7f0d1fcce30 · outbound

This paper cites an unresolved cited work.

Revisiting Compositional Generalization Capability of Large Language Models Considering Instruction Following Ability Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-06T23:57:41.627954Z

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.

Observation e84dfed7-6421-47f1-b79a-88ffa776968d · outbound

This paper cites Marco-o1: Towards Open Reasoning Models for Open-Ended Solutions.

Revisiting Compositional Generalization Capability of Large Language Models Considering Instruction Following Ability Marco-o1: Towards Open Reasoning Models for Open-Ended Solutions

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T23:57:40.532308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78c0ee75-25f8-41ed-934a-03fa27939abd · outbound

This paper cites Due to variations in CoT reasoning, unified evaluation is challenging; therefore, we evaluated using reasoning models.

Revisiting Compositional Generalization Capability of Large Language Models Considering Instruction Following Ability Due to variations in CoT reasoning, unified evaluation is challenging; therefore, we evaluated using reasoning models

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:57:41.346694Z

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.

Observation 4c753744-d9a9-4c67-a2f4-bcc20dfbfd54 · outbound

This paper cites in the specified order.

Revisiting Compositional Generalization Capability of Large Language Models Considering Instruction Following Ability in the specified order

Reference 2004

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:57:41.496800Z

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.

Observation 31bd9282-8065-42c7-bf52-79b39fbe1247 · outbound

This paper cites an unresolved cited work.

Revisiting Compositional Generalization Capability of Large Language Models Considering Instruction Following Ability Unresolved cited work

Reference 2021

Resolution: unresolved; raw_fallback, observed 2026-08-06T23:57:42.071807Z

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.

Observation 6ba05634-7b53-4ab3-a68a-26b8a9270f49 · outbound

This paper cites 2 OLMo 2 Furious.

Revisiting Compositional Generalization Capability of Large Language Models Considering Instruction Following Ability 2 OLMo 2 Furious

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-06T23:57:40.233595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6cd6dcf-85fe-4af9-a139-7f7494b74107 · outbound

This paper cites Generalization without systematicity: On the compositional skills of sequence-to-sequence recurrent networks.

Revisiting Compositional Generalization Capability of Large Language Models Considering Instruction Following Ability Generalization without systematicity: On the compositional skills of sequence-to-sequence recurrent networks

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-06T23:57:40.101494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c97b84d-a993-49bd-a8c5-25085914a22a · outbound

This paper cites Interpreting token compositionality in LLMs: A robustness analysis.

Revisiting Compositional Generalization Capability of Large Language Models Considering Instruction Following Ability Interpreting token compositionality in LLMs: A robustness analysis

Reference 2024

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T23:57:41.174227Z

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.

Observation fa9898c5-f805-4ab0-923e-25cf1f84c653 · outbound

This paper cites CARMA: Enhanced Compositionality in LLMs via Advanced Regularisation and Mutual Information Alignment.

Revisiting Compositional Generalization Capability of Large Language Models Considering Instruction Following Ability CARMA: Enhanced Compositionality in LLMs via Advanced Regularisation and Mutual Information Alignment

Reference 2025

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T23:57:41.005243Z

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.

Pith citing papers

Observation 10a0be47-6ecc-48d0-9f7c-af1da1abf9c6 · inbound

Toward Skill-Native LLMs: Skill Entropy for Benchmarking and Training Long-Horizon Reasoning cites this paper.

Toward Skill-Native LLMs: Skill Entropy for Benchmarking and Training Long-Horizon Reasoning Revisiting Compositional Generalization Capability of Large Language Models Considering Instruction Following Ability

Reference 42

Resolution: verified exact; local_arxiv, observed 2026-08-06T04:30:48.758172Z

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.