Paper Citation Record · LEDGER

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources

As of 20 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2502.05944.

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

pith.paper-citation-record.v1
2502.05944 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:22:30.820579Z

measured 31 of 31 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 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 exact6
verified fuzzy8
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch6

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f8a785ca-0445-43fa-b4e5-33056c2860fe · outbound

This paper cites In: Findings of the Associ ation for Computational Linguistics: ACL 2023.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources In: Findings of the Associ ation for Computational Linguistics: ACL 2023

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:22:31.555252Z

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 7620b040-2bb3-41ad-bcee-268c4eb20bbd · outbound

This paper cites In : Proceedings of the AAAI Conference on Artiﬁcial Intelligence.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources In : Proceedings of the AAAI Conference on Artiﬁcial Intelligence

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:22:31.543487Z

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 59a7b7c0-a5c6-428a-8a88-29e940a36ba2 · outbound

This paper cites In: Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K., Oh, A.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources In: Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K., Oh, A

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:22:31.531791Z

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 9d22901a-f537-42f3-92f6-dfb4f9b55db0 · outbound

This paper cites Findings of the Association for Computational Linguistics: ACL-IJCNLP 20 21 (2021).

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources Findings of the Association for Computational Linguistics: ACL-IJCNLP 20 21 (2021)

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:22:31.518195Z

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 c92a6160-50a3-4bfb-8075-c98e7d611d56 · outbound

This paper cites TTQA-RS- A break-down prompting approach for Multi-hop Table-Text Question Answering with Reasoning and Summarization.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources TTQA-RS- A break-down prompting approach for Multi-hop Table-Text Question Answering with Reasoning and Summarization

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d65a3995-e35e-4557-86fa-76ddc471beb9 · outbound

This paper cites CoCoT: Contrastive Chain-of-Thought Prompting for Large Multimodal Models with Multiple Image Inputs.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources CoCoT: Contrastive Chain-of-Thought Prompting for Large Multimodal Models with Multiple Image Inputs

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-08T17:22:30.735595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5ca4fed-d5bc-434f-98ee-6d04cc85bfe9 · outbound

This paper cites In: Carpuat, M., de Marneﬀe, M., Ruíz, I.V.M.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources In: Carpuat, M., de Marneﬀe, M., Ruíz, I.V.M

Reference 7

Resolution: verified exact; doi, observed 2026-08-08T17:22:31.506117Z

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 f3aad98c-4770-4cca-83d0-ed1583730c2f · outbound

This paper cites InsectMamba: Insect Pest Classification with State Space Model.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources InsectMamba: Insect Pest Classification with State Space Model

Reference 8

Resolution: metadata mismatch; local_arxiv, observed 2026-08-08T17:22:31.420392Z

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 7cebfcb4-e61b-4981-bd6d-a425f8416baf · outbound

This paper cites In: Proceedings of the 60th Annual Meeting o f the Association for Computational Linguistics (Volume 1: Long Papers).

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources In: Proceedings of the 60th Annual Meeting o f the Association for Computational Linguistics (Volume 1: Long Papers)

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:22:31.494862Z

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 0e47bac0-c811-43ad-bee0-5377c24ab740 · outbound

This paper cites Lost in Translation: Large Language Models in Non-English Content Analysis.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources Lost in Translation: Large Language Models in Non-English Content Analysis

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-08T17:22:30.748135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 587b347a-e31d-4f9a-87ea-4c1b323d6d46 · outbound

This paper cites Rethinking Visual Dependency in Long-Context Reasoning for Large Vision-Language Models.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources Rethinking Visual Dependency in Long-Context Reasoning for Large Vision-Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-08T17:22:30.752198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46bc6a26-9f45-432d-a01c-d83a2f1f97d2 · outbound

This paper cites Cedille: A large autoregressive French language model.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources Cedille: A large autoregressive French language model

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-08T17:22:30.755887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7060ac6-8a04-4ef7-a844-700bbf7ecdee · outbound

This paper cites arXiv preprint arXiv:2501.0137 7 (2025).

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources arXiv preprint arXiv:2501.0137 7 (2025)

Reference 13

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-08T17:22:31.382509Z

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 3e2c5a64-e0cd-4908-a6fd-100ad374b9ea · outbound

This paper cites Goldfish: Monolingual Language Models for 350 Languages.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources Goldfish: Monolingual Language Models for 350 Languages

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-08T17:22:30.763275Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6130db1c-6f35-40fe-906b-17b8910b6c16 · outbound

This paper cites an unresolved cited work.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-08-08T17:22:31.482097Z

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 46ec6c12-4843-4a28-bc64-eb996ba1ae36 · outbound

This paper cites Advancing bioinformatics with large language models: components, applications and perspectives.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources Advancing bioinformatics with large language models: components, applications and perspectives

Reference 16

Resolution: metadata mismatch; local_arxiv, observed 2026-08-08T17:22:30.964187Z

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 66fd453b-ac10-4ae9-aa9a-653dcd591742 · outbound

This paper cites LLaMA-Reg: Using LLaMA 2 for Unsupervised Medical Image Registration.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources LLaMA-Reg: Using LLaMA 2 for Unsupervised Medical Image Registration

Reference 17

Resolution: metadata mismatch; local_arxiv, observed 2026-08-08T17:22:30.948303Z

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 f1588644-42aa-4f4a-bac6-c3ec7fb508dc · outbound

This paper cites A Precis of Language Models are not Models of Language.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources A Precis of Language Models are not Models of Language

Reference 18

Resolution: metadata mismatch; local_arxiv, observed 2026-08-08T17:22:30.933983Z

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 0bc6b8ff-8fe6-4210-9edd-182e6404bf7b · outbound

This paper cites ICT Express 5(3), 182–186 (2019).

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources ICT Express 5(3), 182–186 (2019)

Reference 19

Resolution: verified exact; doi, observed 2026-08-08T17:22:30.919436Z

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 c03d0314-f45f-4f6c-b6c5-77600384091a · outbound

This paper cites Beyond the limitations of any imaginable mechanism: large language models and psycholinguistics.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources Beyond the limitations of any imaginable mechanism: large language models and psycholinguistics

Reference 20

Resolution: metadata mismatch; local_arxiv, observed 2026-08-08T17:22:30.908911Z

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 05d89d69-609a-4108-b512-010a4e38f5af · outbound

This paper cites In: Findings of the Association for Comput ational Linguistics, ACL 2024, Bangkok, Thailand and virtual meeting, August 11- 16, 2024.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources In: Findings of the Association for Comput ational Linguistics, ACL 2024, Bangkok, Thailand and virtual meeting, August 11- 16, 2024

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:22:31.469149Z

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 30b1965d-a99f-4dc5-b240-30e22805efbd · outbound

This paper cites In: The Thir- teenth International Conference on Learning Representati ons (2025), https://openreview.net/forum?id=N1vYivuSKq.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources In: The Thir- teenth International Conference on Learning Representati ons (2025), https://openreview.net/forum?id=N1vYivuSKq

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:22:31.456987Z

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 c84cc5ab-2186-4a27-b11f-191e6f57993f · outbound

This paper cites Reverse Question Answering: Can an LLM Write a Question so Hard (or Bad) that it Can't Answer?.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources Reverse Question Answering: Can an LLM Write a Question so Hard (or Bad) that it Can't Answer?

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-08T17:22:30.794081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd0a4a08-8ed6-453e-af4a-59f7064615fe · outbound

This paper cites QAMPARI: An Open-domain Question Answering Benchmark for Questions with Many Answers from Multiple Paragraphs.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources QAMPARI: An Open-domain Question Answering Benchmark for Questions with Many Answers from Multiple Paragraphs

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-08T17:22:30.797337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7f2399f-e7b3-4d16-91ae-65c7f8c494af · outbound

This paper cites (eds.) Proceedings of the 16th Conference o f the European Chapter of the Association for Computational Linguistics: Main Volume, EACL 2021, Online, April 19 - 23, 2021.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources (eds.) Proceedings of the 16th Conference o f the European Chapter of the Association for Computational Linguistics: Main Volume, EACL 2021, Online, April 19 - 23, 2021

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-08T17:22:30.800461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a3e24c8-57b3-4e0e-a4fb-da15619fc662 · outbound

This paper cites In: Muresan, S., Nakov, P., Villavicencio, A.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources In: Muresan, S., Nakov, P., Villavicencio, A

Reference 26

Resolution: verified exact; doi, observed 2026-08-08T17:22:30.869215Z

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 4225d0ca-af78-4ee7-b2c3-061aa7acd7a5 · outbound

This paper cites an unresolved cited work.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources Unresolved cited work

Reference 27

Resolution: unresolved; raw_fallback, observed 2026-08-08T17:22:31.443831Z

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 20e2a793-a698-4edf-b994-b8c248998c6e · outbound

This paper cites In: 5th International Conference on Behavi oral, Economic, and Socio-Cultural Computing, BESC 2018, Kaohsiung, Taiwan, N ovember 12-14,.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources In: 5th International Conference on Behavi oral, Economic, and Socio-Cultural Computing, BESC 2018, Kaohsiung, Taiwan, N ovember 12-14,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:22:31.431938Z

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 be4a0c13-0da7-4f1e-be83-2bcea8fc2cc3 · outbound

This paper cites Enhancing Answer Selection in Community Question Answering with Pre-trained and Large Language Models.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources Enhancing Answer Selection in Community Question Answering with Pre-trained and Large Language Models

Reference 29

Resolution: metadata mismatch; local_arxiv, observed 2026-08-08T17:22:30.858884Z

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 44b23a4b-5250-46d1-b96b-4a9e718bd4a9 · outbound

This paper cites In: Hutte r, F., Kersting, K., Lijf- 14 J.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources In: Hutte r, F., Kersting, K., Lijf- 14 J

Reference 30

Resolution: verified exact; doi, observed 2026-08-08T17:22:30.844384Z

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 00c6eea9-139b-4b2e-85c7-f75e4fb6ee9e · outbound

This paper cites an unresolved cited work.

Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources Unresolved cited work

Reference 2018

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-08T17:22:31.194248Z

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.

Pith citing papers

No inbound Pith citation observations are available.