Pith. sign in

Paper Citation Record · LEDGER

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval

As of 15 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2412.16615.

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

pith.paper-citation-record.v1
2412.16615 v2

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T10:29:26.692223Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

34 of 34 outbound references displayed

  • verified exact2
  • verified fuzzy8
  • unresolved23
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d678a930-2a0b-48d5-9b96-c90e9e849a04 · outbound

This paper cites Do As I Can, Not As I Say: Grounding Language in Robotic Affordances.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval Do As I Can, Not As I Say: Grounding Language in Robotic Affordances

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-11T10:29:26.590411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:29:26.590411Z digest=sha256:72e921117519db588ee450cd3db767207ef53ecdae5c75350e2a56840c1d1ced

Observation 1ffa4063-9398-489f-bfed-b09b5de3694d · outbound

This paper cites In: Rogers, A., Boyd-Graber, J., Okazaki, N.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval In: Rogers, A., Boyd-Graber, J., Okazaki, N

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T10:29:27.004849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T10:29:26.594247Z digest=sha256:3a80e70aac62050675aa31a617c09712295d492ee14a58b88c79b86fe1aa1146

Observation f5e686b1-969e-4f2b-914f-300a2c3cd781 · outbound

This paper cites In: Goldberg, Y., Kozareva, Z., Zhang, Y.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval In: Goldberg, Y., Kozareva, Z., Zhang, Y

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T10:29:26.996736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T10:29:26.600616Z digest=sha256:9eb11a336896685d45ea955d2ec40c36d20b8dcab544710e8c33111981b5504a

Observation c07f2001-f069-4322-a589-d90d02f2cea5 · outbound

This paper cites In: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval In: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-11T10:29:26.606629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:29:26.606629Z digest=sha256:8d28e41b6b72af65aed7b1c0b9940c7dc8c23015d5f4dc705bce2c16c1493c85

Observation ceac468d-4236-475e-a44b-1a487edc857e · outbound

This paper cites Retrieval-Augmented Generation for Large Language Models: A Survey.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-11T10:29:26.609284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:29:26.609284Z digest=sha256:c797dd695a08e807fe27df204fd4d369721449808dd06f24f1f431059f570dca

Observation 699995a9-d7b1-4fc1-ac08-7db2a20a6f36 · outbound

This paper cites Inner Monologue: Embodied Reasoning through Planning with Language Models.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval Inner Monologue: Embodied Reasoning through Planning with Language Models

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-11T10:29:26.612271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:29:26.612271Z digest=sha256:4d4d141a9a72f10406fae7646689f0611433adfe84af44232d037f1a6870d917

Observation e9d5810f-61e7-4d88-b826-b6c071225b7d · outbound

This paper cites In: Proceedings of the ACM SIGOPS 29th Symposium on Operating Systems Principles (2023).

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval In: Proceedings of the ACM SIGOPS 29th Symposium on Operating Systems Principles (2023)

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-11T10:29:26.615563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:29:26.615563Z digest=sha256:85690f4d036575522b0adf92f5bd2efb4be775bf95d8ed3b816ff6f9c54fcd9d

Observation 207398fd-464c-4499-a26b-7504cff5ac7f · outbound

This paper cites In: Ku, L.W., Martins, A., Srikumar, V.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval In: Ku, L.W., Martins, A., Srikumar, V

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T10:29:26.984606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T10:29:26.618565Z digest=sha256:730839d04cd064fcb519155260717b911a23f7380a399ca5c64a7a011e303a39

Observation 50d24880-cb13-4b03-b9bd-a46af7c6e711 · outbound

This paper cites From Matching to Generation: A Survey on Generative Information Retrieval.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval From Matching to Generation: A Survey on Generative Information Retrieval

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-11T10:29:26.621515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:29:26.621515Z digest=sha256:3b3f301989e03b46e0a02afca91f8f464e6164eec4175e58810d7119ad7e5345

Observation 064bc8ac-bc6b-470c-b11c-e8762a9eb55b · outbound

This paper cites In: Zong, C., Xia, F., Li, W., Navigli, R.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval In: Zong, C., Xia, F., Li, W., Navigli, R

Reference 10

Resolution
malformed identifier
no resolver link, observed 2026-08-11T10:29:26.625310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:29:26.625310Z digest=sha256:e26672315a81420808c8f96a35eb61bf9defaa5d90dbaa93919fee199e627e0a

Observation 22c023fa-05e5-4118-b149-5e4012416881 · outbound

This paper cites In: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval In: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-11T10:29:26.628190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:29:26.628190Z digest=sha256:6e873d9d0b91d9901217ec1c0c454a429fe5971a0abd74354374c884d3715dbe

Observation 034e44b8-85ed-4cec-b30b-f3e4f0254cf7 · outbound

This paper cites SGPT: GPT Sentence Embeddings for Semantic Search.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval SGPT: GPT Sentence Embeddings for Semantic Search

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-11T10:29:26.630537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:29:26.630537Z digest=sha256:6a7d561ac1cd94576a083d66b4ba32e75ec1a0afc2d7fa1914c79a8f5f18e14d

Observation 93a2fee3-308d-49ca-8dd8-e2c20cd0a156 · outbound

This paper cites an unresolved cited work.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-08-11T10:29:26.977374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T10:29:26.633536Z digest=sha256:46ddd9c9dd1a7c388fe0f990dcd1d9b2889d959dbf5aee3b891b358ca694b6a2

Observation 5c7f3277-df6f-4512-9da7-4e7a1138c81d · outbound

This paper cites SFR-RAG: Towards Contextually Faithful LLMs.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval SFR-RAG: Towards Contextually Faithful LLMs

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-11T10:29:26.635690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:29:26.635690Z digest=sha256:fac1a11db1d98f0896757580c07f10bdc87f2ec6e74c1eb652ed427ed1545e7d

Observation 279be85c-c87e-4000-aa6c-63835fef8039 · outbound

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

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval Training language models to follow instructions with human feedback

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-11T10:29:26.638453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:29:26.638453Z digest=sha256:ff8277d1adc7168ba4d6536cee8e86dc11d9b074f2e1c96d72b2a26fd7a74ac0

Observation 08b231f2-3f4a-4c8e-85b1-9cf3a009f1fb · outbound

This paper cites PsyChat: A Client-Centric Dialogue System for Mental Health Support.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval PsyChat: A Client-Centric Dialogue System for Mental Health Support

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-11T10:29:26.641902Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:29:26.641902Z digest=sha256:7e077cb61b13b5695a39360de6aa0fa3791a180982b857c73746968a35e6a833

Observation 13e85227-157f-4f13-a7af-018eb8fb6259 · outbound

This paper cites Technical report, Alibaba Group (2024).

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval Technical report, Alibaba Group (2024)

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T10:29:26.969468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T10:29:26.645437Z digest=sha256:d600177139110e0b92b11e7a7f5f366edbd0d7ded5406740c690575bfc5be962

Observation 2a66b505-b860-4e39-8c5c-4d9e37d09950 · outbound

This paper cites In: Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M., Levine, S.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval In: Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M., Levine, S

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-11T10:29:26.648148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:29:26.648148Z digest=sha256:9135ab3ceb4e9bb30dc51c91ce025af4464654704e309ed50725bba042b69e41

Observation 198bad72-99b7-4b03-ae47-447f3644a452 · outbound

This paper cites In: Proceedings of the Conference on Robot Learning (CoRL) (2023).

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval In: Proceedings of the Conference on Robot Learning (CoRL) (2023)

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T10:29:26.957681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T10:29:26.650650Z digest=sha256:ea9d6d0fc3354589ca9fc7d2244fc9cc883d8caab1150e28c79d42d97e262306

Observation baae172f-53e7-44c4-9e2d-cbd3393e6ab9 · outbound

This paper cites an unresolved cited work.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval Unresolved cited work

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-11T10:29:26.653836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:29:26.653836Z digest=sha256:d58b6382e84213f35fc9b59f05bbda7a702242f656dd197ae9f733c54a9c1f34

Observation 1e358e2c-11b3-4edd-988f-57e104f600b7 · outbound

This paper cites In: Rogers, A., Boyd-Graber, J., Okazaki, N.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval In: Rogers, A., Boyd-Graber, J., Okazaki, N

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-11T10:29:26.657068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:29:26.657068Z digest=sha256:64c28ca443729d140c36499180443d9d207eb13fb74cc651edac49bdc1e97e1a

Observation 32771eaf-e19f-4a22-9e54-b5f94ba50361 · outbound

This paper cites In: Zong, C., Xia, F., Li, W., Navigli, R.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval In: Zong, C., Xia, F., Li, W., Navigli, R

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-11T10:29:26.660413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:29:26.660413Z digest=sha256:fa5f459d1624e811a26ad6c9e8407728316d015e88b4114890ad6a6e3d4effae

Observation fd795886-da69-416d-bae7-398f155fc51a · outbound

This paper cites In: Ku, L.W., Martins, A., Srikumar, V.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval In: Ku, L.W., Martins, A., Srikumar, V

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T10:29:26.950229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T10:29:26.663940Z digest=sha256:2f41d3d8cb183b73d6eb2787681af6c439935ebc3912d6a2f5608a15735c7587

Observation 06a1aa67-e2fe-4962-af1f-ef4c4076c483 · outbound

This paper cites Promptriever: Instruction-Trained Retrievers Can Be Prompted Like Language Models.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval Promptriever: Instruction-Trained Retrievers Can Be Prompted Like Language Models

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-11T10:29:26.667371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:29:26.667371Z digest=sha256:ebb926fb13b25b2a1349fddaf2084e718e398d798fb5e6faeb1afc6132272100

Observation 0e3eeacd-ac6f-46e3-afb3-98b03bdfb126 · outbound

This paper cites Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-11T10:29:26.670410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:29:26.670410Z digest=sha256:63c2e1a7f1ef2065d29b3cecbd9608ad1c47ea86a9baffc167b6e8e28787844a

Observation c57abf5d-fdf5-4d64-8336-eb0331686ca1 · outbound

This paper cites NAACL-HLT pp.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval NAACL-HLT pp

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T10:29:26.942657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T10:29:26.673983Z digest=sha256:2d0be7db7fb9f489eb0da68b45092ff15ea05865d54d4f76b4b66b60a58c603c

Observation 83289109-4396-47d7-982b-d70935d16206 · outbound

This paper cites OneGen: Efficient One-Pass Unified Generation and Retrieval for LLMs.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval OneGen: Efficient One-Pass Unified Generation and Retrieval for LLMs

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-11T10:29:26.677143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:29:26.677143Z digest=sha256:68a06868875b85f8606cf0770e9bbfbb6508d25355a609b68fe94666a0d5a2da

Observation 503661fa-26e2-4ce7-9767-f1ee41cf719f · outbound

This paper cites Retrieval-Augmented Generation for AI-Generated Content: A Survey.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval Retrieval-Augmented Generation for AI-Generated Content: A Survey

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-11T10:29:26.680092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:29:26.680092Z digest=sha256:4b481d507520b64edc896bc541d76062bb12c7223b5f47f4963692920ae1d3df

Observation 3e22683c-34c5-4c5e-8f83-19b750fc404d · outbound

This paper cites Retrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval Retrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-11T10:29:26.683314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:29:26.683314Z digest=sha256:55f8ec3a404084dadeadde8b73173ef28824e4d9b22483e38018efa1759b9f48

Observation 3b7ceb45-17ab-485e-b566-e1770ebfb4af · outbound

This paper cites In: Rogers, A., Boyd-Graber, J., Okazaki, N.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval In: Rogers, A., Boyd-Graber, J., Okazaki, N

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T10:29:26.935070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T10:29:26.686230Z digest=sha256:8637c0c1eb4144187e818b33e9580c1554ad7f66b34f9dba3e9feaa7d4ad59da

Observation 269ae091-cd5f-442f-a07a-a44fdbcdf804 · outbound

This paper cites LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-11T10:29:26.692223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:29:26.692223Z digest=sha256:fc74489f752734f82196a567e0246efa1eafaad442151fc8e1a71894b7bb3e61

Observation 3072ebb2-2957-4fd5-945a-dac9b472fc8f · outbound

This paper cites 6725–6739.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval 6725–6739

Reference 33

Resolution
verified exact
doi, observed 2026-08-11T10:29:26.714701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T10:29:26.689165Z digest=sha256:70aae3978fa670b777ef88170c5870e5a6a48b7bb3ece2f91a0b9711ae062147

Observation 3548441c-aaba-4baa-8ee9-3d2a5421a285 · outbound

This paper cites 3650–3675.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval 3650–3675

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-11T10:29:26.597802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:29:26.597802Z digest=sha256:7ee6039e64a336f82acfa973c9943b0122476bae54d557fa413f25ab62245516

Observation dbe17d57-37cc-4233-a69f-ffcc2f97e888 · outbound

This paper cites https://doi.org/10.18653/v1/2022.emnlp-main.195, https: //aclanthology.org/2022.emnlp-main.195.

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval https://doi.org/10.18653/v1/2022.emnlp-main.195, https: //aclanthology.org/2022.emnlp-main.195

Reference 3026

Resolution
verified exact
doi, observed 2026-08-11T10:29:26.738717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T10:29:26.603424Z digest=sha256:0024b4a6a458bda6897d4eecab43458fae9bf78df8912e4dea2a149de206083b

Pith citing papers

No inbound Pith citation observations are available.