Pith. sign in

Paper Citation Record · LEDGER

Foundations of GenIR

As of 13 August 2026, this Paper Citation Record lists 100 of 152 outbound references and 1 inbound Pith citation observation for arXiv:2501.02842.

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

pith.paper-citation-record.v1
2501.02842 v1

Coverage vector

measured 100 of 152 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:06:05.124717Z

measured 101 of 101 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T21:20:42.329518Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T20:16:12.141701Z

Reference resolution

100 of 152 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved98
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a66084a9-73c4-4a0c-bc22-bc425e42c47d · outbound

This paper cites GPT-4 Technical Report.

Foundations of GenIR GPT-4 Technical Report

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.622430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.622430Z digest=sha256:7f4aaeb6c061067d8a30a04ae0ce9aea106a3bc429358eade901b8c0ae243036

Observation d1a95302-f577-4b6a-99e5-24bdbbf3919d · outbound

This paper cites A Survey of Large Language Models.

Foundations of GenIR A Survey of Large Language Models

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.628213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.628213Z digest=sha256:f5958e56ac6ad11af2c7896efda367d300ae8280471f2fee5ffb3234555e7b82

Observation 7d0a19cc-bb2f-44ec-a247-16f4b0d571f3 · outbound

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

Foundations of GenIR LLaMA: Open and Efficient Foundation Language Models

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.633352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.633352Z digest=sha256:634d565f2671de666024f3f87255261f5e875557492e0d235908704906f0db46

Observation df349f15-9f83-43e6-878f-6182e7cb317b · outbound

This paper cites In: Guyon, I., Luxburg, U.V., Bengio, S., Wallach, H., Fergus, R., Vishwanathan, S., Garnett, R.

Foundations of GenIR In: Guyon, I., Luxburg, U.V., Bengio, S., Wallach, H., Fergus, R., Vishwanathan, S., Garnett, R

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.638181Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.638181Z digest=sha256:18fc21ab1c621f058c568da62d5c21ae54274eb9b6c5dc8a692d9b823b9546b4

Observation 49ba7816-98b1-45df-8de9-a4c3c7fc69af · outbound

This paper cites IEEE transactions on Signal Processing 45(11), 2673–2681 (1997).

Foundations of GenIR IEEE transactions on Signal Processing 45(11), 2673–2681 (1997)

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.643102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.643102Z digest=sha256:3ebfe4a706f797fab32c3855d4c808cbea7b4eec4d020534416f85c3e18dc6a4

Observation 207257f2-5c1e-4d59-b9c5-94302ccae827 · outbound

This paper cites GLM-130B: An Open Bilingual Pre-trained Model.

Foundations of GenIR GLM-130B: An Open Bilingual Pre-trained Model

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.647910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.647910Z digest=sha256:17e75823acc209da489c969b1eb80b8da0fadbcf01732145d75575dfcf138eca

Observation 594a498b-5ade-47a0-a2da-a0b12328b07c · outbound

This paper cites an unresolved cited work.

Foundations of GenIR Unresolved cited work

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.653224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.653224Z digest=sha256:4932563fe900ae60d4c4ad6aab62495eed8d2bbe4a0f18346b3369030ea2c422

Observation cdf474d4-b11b-42d3-89ed-e68a38b506d9 · outbound

This paper cites In: NAACL-HLT (1), pp.

Foundations of GenIR In: NAACL-HLT (1), pp

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.657792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.657792Z digest=sha256:d970b9dc63c657f6e9aefb35b55549d3b87c42a6040d772fa3c137d5625d31ef

Observation 28606025-6e2e-4f93-aa19-762f9032e05a · outbound

This paper cites an unresolved cited work.

Foundations of GenIR Unresolved cited work

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.662704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.662704Z digest=sha256:7fde953415da9316b5301a486295f3be20b6054d087161a25ea68f892e3c0f41

Observation 21a28681-bcc6-4e1e-b3db-6c939df5ffc9 · outbound

This paper cites Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation.

Foundations of GenIR Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.667710Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.667710Z digest=sha256:15b6f028119c182ac95c74e55f92d032b4548517583a477cfc84b089bb7f8b02

Observation 240f47f1-1924-46ce-8304-d4aa7c388085 · outbound

This paper cites DOI: https://doi.

Foundations of GenIR DOI: https://doi

Reference 11

Resolution
malformed identifier
no resolver link, observed 2026-08-10T22:06:04.673137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.673137Z digest=sha256:7b8c88cf1a1394197da6876877a738e2c9237b5ca2f1e1fccdd51dc8392932d2

Observation c4d16eb3-21b7-4a90-8541-228304bfa19e · outbound

This paper cites GPT-NeoX-20B: An Open-Source Autoregressive Language Model.

Foundations of GenIR GPT-NeoX-20B: An Open-Source Autoregressive Language Model

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.678036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.678036Z digest=sha256:2e8b7db308605477b7c1211b339d8fccb13ad98d28de4801979c84aef7f24974

Observation 3af50368-935c-40df-bcc5-21ac506dd455 · outbound

This paper cites Generating Long Sequences with Sparse Transformers.

Foundations of GenIR Generating Long Sequences with Sparse Transformers

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.683348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.683348Z digest=sha256:d5e919c6328f6ee1e2ada232f4a3f03f0e35384758df3c50a0d4f5e51339f66a

Observation 84b656ed-37a5-4a0f-b9e8-b58371eedce0 · outbound

This paper cites Reformer: The Efficient Transformer.

Foundations of GenIR Reformer: The Efficient Transformer

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.688290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.688290Z digest=sha256:c1660a458e8aece646ec8a5d40d076d5acfe770a3678021f903fc18f9f7a57fc

Observation 96f68a58-24d1-4c94-af5b-10453ffedaf0 · outbound

This paper cites Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention.

Foundations of GenIR Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.693212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.693212Z digest=sha256:53b961aef3691afcd4f44c4dd3f5010ebab0436f869363e419d54096fc7fdccd

Observation 91656d45-ac62-46f5-b49f-1020c31661bd · outbound

This paper cites Improving Neural Language Models with a Continuous Cache.

Foundations of GenIR Improving Neural Language Models with a Continuous Cache

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.698124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.698124Z digest=sha256:57dc31a32e21df33e64f8cdf0b4b85c6c15a866c43d1addaa3b3aa1b78f0e47b

Observation 69d5a45c-cc4e-4608-8d1d-9a03a6ee5512 · outbound

This paper cites arXiv (2020).

Foundations of GenIR arXiv (2020)

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.703162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.703162Z digest=sha256:70052e81ebd8f3b2ce1d7cc44ac4081ce2f3bccf0336bb0c64f272033c18f8ad

Observation 4005c333-9cd1-4706-b7ce-7470dec18b08 · outbound

This paper cites Fast Transformer Decoding: One Write-Head is All You Need.

Foundations of GenIR Fast Transformer Decoding: One Write-Head is All You Need

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.708093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.708093Z digest=sha256:4cac8174a6e71c7d51e434c42d10938e627480906a1f5fbd89f299ed7eb74979

Observation d0828694-c963-448b-a25a-867ed6cc8f60 · outbound

This paper cites GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints.

Foundations of GenIR GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.712899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.712899Z digest=sha256:2c966f66cfca851f71926d63c08613c02121b387e723f408dccb5e0baab4ab02

Observation 8d0fe2bf-07cb-4853-8d38-68b7a19ca759 · outbound

This paper cites an unresolved cited work.

Foundations of GenIR Unresolved cited work

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.718058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.718058Z digest=sha256:886ff4862798f29917f54058a5ccaad8d1fa80701bec11f975795fbee4d251ba

Observation 60664f72-0238-4d7d-b8e5-30959c172b1e · outbound

This paper cites In: International Conference on Machine Learning, pp.

Foundations of GenIR In: International Conference on Machine Learning, pp

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.722619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.722619Z digest=sha256:042d2c2f61bc4e21e29bf4a920622c8ccff780cf530b45c305fe10400be7457e

Observation 09a98b2f-d3bb-43b6-83c9-b8ff0211d868 · outbound

This paper cites Advances in Neural Information Processing Systems 34, 19822– 19835 (2021).

Foundations of GenIR Advances in Neural Information Processing Systems 34, 19822– 19835 (2021)

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.727584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.727584Z digest=sha256:05f977a2ad5ceeba01d5c43431cf3f3488286ee84d474849c6de3ee1db2393d9

Observation ac08013b-12e0-45fb-8435-f4471b0b3ae5 · outbound

This paper cites IEEE Transactions on Pattern Analysis and Machine Intelligence (2024).

Foundations of GenIR IEEE Transactions on Pattern Analysis and Machine Intelligence (2024)

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.732558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.732558Z digest=sha256:73a80ebe4644030b968f434942586405829f14d512c454538da3f01dbf14ea97

Observation 1d3a710f-f639-4a7c-ba4d-b890d71d38ba · outbound

This paper cites Scaling Laws for Neural Language Models.

Foundations of GenIR Scaling Laws for Neural Language Models

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.736857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.736857Z digest=sha256:1b6c60597c366440ae0b50c18c4500c1b2ce37904177316fc44df8e9a39c2cd5

Observation 33e61d43-a6bb-48c0-b924-73d3a269abb5 · outbound

This paper cites Training Compute-Optimal Large Language Models.

Foundations of GenIR Training Compute-Optimal Large Language Models

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.741659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.741659Z digest=sha256:e0e79487b7d6fd120ede9a414147c07503985240da315ed3879eaa2075f607dc

Observation 8fc469a8-3efa-48fb-9b30-85ab60163464 · outbound

This paper cites Data Mixing Laws: Optimizing Data Mixtures by Predicting Language Modeling Performance.

Foundations of GenIR Data Mixing Laws: Optimizing Data Mixtures by Predicting Language Modeling Performance

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.746436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.746436Z digest=sha256:0a70d02a2768ceb44c97ad7e11dfbbb181a565a1b0480f0a8f13efefc6c09196

Observation daad05c8-594c-44db-80c1-e730ddb80296 · outbound

This paper cites Scaling Laws for Autoregressive Generative Modeling.

Foundations of GenIR Scaling Laws for Autoregressive Generative Modeling

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.751269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.751269Z digest=sha256:7f816f82c7e92f52cd750eebf97a289f3f04e356b55ea4f1f73fa81a6bd0ada0

Observation b335f1ac-5630-4d74-ade4-2497e46f55d3 · outbound

This paper cites Emergent Abilities of Large Language Models.

Foundations of GenIR Emergent Abilities of Large Language Models

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.760751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.760751Z digest=sha256:35185de025c8f814083324c52c00c9277e08c4d8ffc46edf5eb0b59835e17226

Observation 1016a9c1-1dfb-4190-b32a-2ad2ae58bb95 · outbound

This paper cites Understanding Emergent Abilities of Language Models from the Loss Perspective.

Foundations of GenIR Understanding Emergent Abilities of Language Models from the Loss Perspective

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.765458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.765458Z digest=sha256:7a5228d89ba36566cb633e87fb04a9f66cd0508f7a09fc80f33c61e9bc305e43

Observation 1999e124-e187-477c-956c-ccd75d0e80d3 · outbound

This paper cites Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets.

Foundations of GenIR Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.770297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.770297Z digest=sha256:b6beebb94786151fc8ac2afaae2fd76d9cb1839a333854748b3a9dbca2413414

Observation 11295a71-2381-417a-b900-8b2d4434eeb0 · outbound

This paper cites NIPS ’23, pp.

Foundations of GenIR NIPS ’23, pp

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.774961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.774961Z digest=sha256:fc5451638f8c9812ecee4eb7ac9f0d9591ac8710f40ef2101d415470ad10941a

Observation ebcf4630-1db2-46a4-b850-138f27146c93 · outbound

This paper cites Inverse Scaling: When Bigger Isn't Better.

Foundations of GenIR Inverse Scaling: When Bigger Isn't Better

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.779585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.779585Z digest=sha256:b3b238a05b4c8c03767a232cc20b8da233d10c189bcfeaf1e676cf74505985b1

Observation 731ac2d3-ff3d-4849-bbed-b1727d88cc57 · outbound

This paper cites Bigger is not Always Better: Scaling Properties of Latent Diffusion Models.

Foundations of GenIR Bigger is not Always Better: Scaling Properties of Latent Diffusion Models

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.784343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.784343Z digest=sha256:f681f00d51be7317a20088d163f543524771b8b286985c137143435ef2573042

Observation 93dfcfb5-f55c-4792-9778-0082d98916ca · outbound

This paper cites MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies.

Foundations of GenIR MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.788989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.788989Z digest=sha256:84d726a359f8b612d0b3c1c61e990697ecd93325d25bf76ecd45d03a567e4cda

Observation d7837f91-02cb-42a2-866d-1ecae2b160fc · outbound

This paper cites OpenAI blog 1(8), 9 (2019).

Foundations of GenIR OpenAI blog 1(8), 9 (2019)

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.793921Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.793921Z digest=sha256:bbc24c4edfffb1fbb7501ea3b048c19178eebef725ae80aa04fbba8c00dacbd8

Observation 63ebac41-ac1b-4f9e-bd07-d920dd25bb71 · outbound

This paper cites OPT: Open Pre-trained Transformer Language Models.

Foundations of GenIR OPT: Open Pre-trained Transformer Language Models

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.798494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.798494Z digest=sha256:1e27e5eca471a8d1bc4a314e20716383eb423f394f6ec22dcb99dbacad56edcd

Observation 9c5b579d-2734-4e70-ba89-1d859efae8ca · outbound

This paper cites Journal of Machine Learning Research 24(240), 1–113 (2023).

Foundations of GenIR Journal of Machine Learning Research 24(240), 1–113 (2023)

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.803171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.803171Z digest=sha256:4cca9d581264bacdc66a98046ea39e2f20a369a80c74640c001fffcc52ef66f1

Observation 0c5876ef-a2c2-4f44-bb9f-b4d6949f63e1 · outbound

This paper cites Textbooks Are All You Need.

Foundations of GenIR Textbooks Are All You Need

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.807581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.807581Z digest=sha256:01885427ebb2184454ee5e10b30115178c65ced019c299e3acd31442c6ea7c63

Observation 200d7491-3256-4c59-887f-76120ec11497 · outbound

This paper cites Baichuan 2: Open Large-scale Language Models.

Foundations of GenIR Baichuan 2: Open Large-scale Language Models

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.812265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.812265Z digest=sha256:85b72bc8bb9bb98ea6f96930464590a106c3fdc3afb23bf4c202ba707974fcbc

Observation 0a99902e-8f85-4581-8247-0435100155c1 · outbound

This paper cites DeepSeek LLM: Scaling Open-Source Language Models with Longtermism.

Foundations of GenIR DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.817170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.817170Z digest=sha256:5f4a7bb66754f9342168864f18e5351b6e049ff8ca9bdba0f127e8ff4ef91a7f

Observation 6f5ba00f-7b7b-4449-bccd-9f764765d133 · outbound

This paper cites Scaling Instruction-Finetuned Language Models.

Foundations of GenIR Scaling Instruction-Finetuned Language Models

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.822044Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.822044Z digest=sha256:d302c97167c765b6bd2742e513ee0efb2c9f5c76df98802455f97da87988a9f0

Observation 0dad47f7-ac73-4b84-984f-cd1bd147c63e · outbound

This paper cites Advances in neural information processing systems 35, 27730–27744 (2022).

Foundations of GenIR Advances in neural information processing systems 35, 27730–27744 (2022)

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.826691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.826691Z digest=sha256:f8e48df6e353727c9b6801cfe2ad803c8c7d9a1033144dbed26634ab1a22b4ee

Observation fc5e72b5-f2b8-4244-8884-60d6520e6a28 · outbound

This paper cites an unresolved cited work.

Foundations of GenIR Unresolved cited work

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.831005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.831005Z digest=sha256:51ba00123c2e0628b361f6ba475826fb4f1c03ab171f3ae34234961de468a21c

Observation 67812bbb-964d-45df-9d69-263008ce6e61 · outbound

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

Foundations of GenIR In: Oh, A., Neumann, T., Globerson, A., Saenko, K., Hardt, M., Levine, S

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.835609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.835609Z digest=sha256:9b9b5a4776e36de6d052e370ae0001592e2d9981b92938dfbaaf822f22876705

Observation bf9ea554-ffe1-41c4-9b47-64b64a269d0e · outbound

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

Foundations of GenIR Is DPO Superior to PPO for LLM Alignment? A Comprehensive Study

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.840129Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.840129Z digest=sha256:fae8b080f37dd2c873b06ef04388b8d1f60dddfcb199a3c7fd987c1da3ecf7f4

Observation 3333a79d-66ca-4e97-800f-b3e0a2b5e082 · outbound

This paper cites ACM Computing Surveys 55(9), 1–35 (2023).

Foundations of GenIR ACM Computing Surveys 55(9), 1–35 (2023)

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.844841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.844841Z digest=sha256:fcc52963133a33763723ba2988affd689836e8029d60aec0e3f6d5be86fc36f0

Observation 1feb1c92-edb2-49f7-b04a-afc187dc5e03 · outbound

This paper cites Advances in neural information processing systems 35, 24824–24837 (2022).

Foundations of GenIR Advances in neural information processing systems 35, 24824–24837 (2022)

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.849586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.849586Z digest=sha256:f6ff90542c5977e7d84063f03242d451061b6022f0185a4244bb15fb9afb6b36

Observation 8faa9a04-8576-41f8-92cc-271731c8c533 · outbound

This paper cites In: Proceedings of the 37th International Conference on Neural Information Processing Systems.

Foundations of GenIR In: Proceedings of the 37th International Conference on Neural Information Processing Systems

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.854546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.854546Z digest=sha256:b5aa8a7210b95f593d3fc49687b91df15b8f78f852ba268c4608091a04962779

Observation 6add293f-b88b-45e7-a4de-a30451aa2027 · outbound

This paper cites In: 11th International Conference on Learning Representations, ICLR 2023, pp.

Foundations of GenIR In: 11th International Conference on Learning Representations, ICLR 2023, pp

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.859217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.859217Z digest=sha256:a3723e3cad95383e3d8a3c518c019a95e9e8f00f2e696246bfbebeacb0a490f2

Observation e6cfeabb-b79f-470b-b132-b0b131ab5acb · outbound

This paper cites Large Language Models Are Human-Level Prompt Engineers.

Foundations of GenIR Large Language Models Are Human-Level Prompt Engineers

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.863785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.863785Z digest=sha256:cdc99cb4e5a679bf2a04078c11d8ca25cbb0cb7ea23c6ee12aff199d061c3610

Observation 51277ad3-6fdb-475d-82a2-7796d331f113 · outbound

This paper cites Large Language Models as Optimizers.

Foundations of GenIR Large Language Models as Optimizers

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.868280Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.868280Z digest=sha256:f7a5213a46aee20e891df4c7b71accd71a0eeeed934c3dc83c824a9fde7ff026

Observation 3e9ecaca-1f38-41b5-998e-c57079cb1ed1 · outbound

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

Foundations of GenIR In: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Infor- mation Retrieval

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.873099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.873099Z digest=sha256:ca1e52afaef26f5e2ab2b4e22989ed1a0e00c6e243bb173af6f6ee19e3d84646

Observation 02d0b51a-d479-448f-980b-3991912ad76e · outbound

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

Foundations of GenIR In: Ku, L.-W., Martins, A., Srikumar, V

Reference 54

Resolution
verified exact
doi, observed 2026-08-10T22:06:05.497189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T22:06:04.878120Z digest=sha256:5b50ee17ad3242bfdf43ffcaf190052fafbd90edbb2d108fef97c408568dde7a

Observation 1ecaa240-7588-4e43-a896-51f6232e526c · outbound

This paper cites Advances in neural information processing systems 32 (2019) 26.

Foundations of GenIR Advances in neural information processing systems 32 (2019) 26

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.882871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.882871Z digest=sha256:dc4995e23b9e4896637d50ad757fd093d4b4fbf28eaeaec3ea14e0249aaa7d58

Observation 0ba36f72-0ce3-4a21-bd1d-a766dc29f1a4 · outbound

This paper cites In: European Conference on Computer Vision, pp.

Foundations of GenIR In: European Conference on Computer Vision, pp

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.887652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.887652Z digest=sha256:0ed707d9df4f964b1a9ad8bb43ac87f2a0af8b4e07912077de1eee6824d8632b

Observation df65f2e9-2856-4d1d-9b55-89350183965f · outbound

This paper cites Pixel-BERT: Aligning Image Pixels with Text by Deep Multi-Modal Transformers.

Foundations of GenIR Pixel-BERT: Aligning Image Pixels with Text by Deep Multi-Modal Transformers

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.892482Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.892482Z digest=sha256:179683143e7899a31298ef7aa685ce1352d6f8c0ceff7413339599a5b922b8df

Observation f65e688e-c8b4-45e9-9365-9b17c87b69b6 · outbound

This paper cites In: International Conference on Machine Learning, pp.

Foundations of GenIR In: International Conference on Machine Learning, pp

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.897163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.897163Z digest=sha256:ea19f2166f3247cfe3cf677dfae00af2c6aa4bd2327f84966ba36d6190bcd3b8

Observation 48089086-0d27-4dae-a327-8a20981b63e6 · outbound

This paper cites Advances in neural information processing systems 35, 23716–23736 (2022).

Foundations of GenIR Advances in neural information processing systems 35, 23716–23736 (2022)

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.901970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.901970Z digest=sha256:0f818881cbd67941a18b7de4de8465e78597221916e015b8b033c91e328ce2c5

Observation dcb7a881-5241-43e7-84da-9e2fcf6fb8b1 · outbound

This paper cites CogVLM: Visual Expert for Pretrained Language Models.

Foundations of GenIR CogVLM: Visual Expert for Pretrained Language Models

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.907190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.907190Z digest=sha256:9087c349033ad4de3f25bb5bcd83150118f04ba1da64f59b2f222a8c25d10a17

Observation d472bfcd-86fa-483b-9134-b5cfda66ccb4 · outbound

This paper cites In: International Conference on Machine Learning, pp.

Foundations of GenIR In: International Conference on Machine Learning, pp

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.912127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.912127Z digest=sha256:38bfd67e578ddb455eca13f2a4198648fbd75682a69f528c40eb099594300bd5

Observation 6d7129e1-528f-430a-b8d2-f3c96de080f4 · outbound

This paper cites In: International Conference on Machine Learning, pp.

Foundations of GenIR In: International Conference on Machine Learning, pp

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.916946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.916946Z digest=sha256:74a82d5359e570bae4089125307c35581a536ef56fc05e443dbb4ce5df8a1fe8

Observation 6bd32134-add5-40b1-9b6a-976a24e19ee4 · outbound

This paper cites Advances in neural information processing systems 34, 9694–9705 (2021).

Foundations of GenIR Advances in neural information processing systems 34, 9694–9705 (2021)

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.921840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.921840Z digest=sha256:717ec51d3d8c1a53ccea7c10bd47462b772f9f13cba0a35b964c1de67ca33126

Observation 27a0baee-eb7b-4f6f-8596-e97db868cabe · outbound

This paper cites In: International Conference on Machine Learning, pp.

Foundations of GenIR In: International Conference on Machine Learning, pp

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.926925Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.926925Z digest=sha256:4e7ac55a3c770ed14488365795aa8c5618472aeccde23b30d01ddf5634301d94

Observation 4889149e-8464-40f9-893e-5f20b3552c8b · outbound

This paper cites RLHF-V: Towards Trustworthy MLLMs via Behavior Alignment from Fine-grained Correctional Human Feedback.

Foundations of GenIR RLHF-V: Towards Trustworthy MLLMs via Behavior Alignment from Fine-grained Correctional Human Feedback

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.932107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.932107Z digest=sha256:8812caa06ff393f21c9477d4f92e0efca5af4621c0c8a2cc0d8bf4da06bfcc18

Observation dde5d4cf-dadb-4cd4-81ff-b1716797495f · outbound

This paper cites BEiT: BERT Pre-Training of Image Transformers.

Foundations of GenIR BEiT: BERT Pre-Training of Image Transformers

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.937061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.937061Z digest=sha256:81a3fd758a9ddf81663d53e948a5a7abb095d82b3fb6244140bfa8b8b2241651

Observation 0fcd6d22-ed33-4cf2-a5b6-d6b0b1510421 · outbound

This paper cites In: International Conference on Machine Learning, pp.

Foundations of GenIR In: International Conference on Machine Learning, pp

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.943588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.943588Z digest=sha256:0f08d65a072576f8003a68916455cd8864a24623043a0e64d1994841b4ec481f

Observation f82815f2-f411-4471-9a86-42974f588557 · outbound

This paper cites In: International Conference on Machine Learning, pp.

Foundations of GenIR In: International Conference on Machine Learning, pp

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.948165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.948165Z digest=sha256:f12a270064ad072a0590684443bc2e069c8ced7b533f7fde40d218075237ee3f

Observation b71eb7f9-1b28-479f-b452-f0f052e753c6 · outbound

This paper cites GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models.

Foundations of GenIR GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.953078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.953078Z digest=sha256:43d90b9921516d48d5082265f78e312eba76b4b44952fbfbb0a05bc2f453683b

Observation 0c4fe324-42ee-437d-89c5-2ee35cd312d1 · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

Foundations of GenIR In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.959120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.959120Z digest=sha256:6498bb27ad54ee13fb723c18820448ce6180566d3b7153fc8b3efa1fd66ed389

Observation f7f55a41-1150-43e9-a914-748c28dbe2bb · outbound

This paper cites Advances in neural information processing systems 33, 6840–6851 (2020).

Foundations of GenIR Advances in neural information processing systems 33, 6840–6851 (2020)

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.963941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.963941Z digest=sha256:9c36754a8f268e002839287f4c81355974387eeacd95fbcfe2cc9cc0125705e5

Observation fac1c525-d397-483c-8662-ee557582483e · outbound

This paper cites Text-to-image Diffusion Models in Generative AI: A Survey.

Foundations of GenIR Text-to-image Diffusion Models in Generative AI: A Survey

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.968981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.968981Z digest=sha256:44d7f6cc5bcbc2114276ef43162ead49c8ae78a599b5a14efc99931a08a2d1fa

Observation 2662fbe3-1963-4db8-880d-02573e5b2472 · outbound

This paper cites In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp.

Foundations of GenIR In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.974145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.974145Z digest=sha256:ddd71dca7bfe086ff2cb771666b08af56f49b8672832d7307bc7aa4836ea7e50

Observation f911f27e-daaa-4374-a6ff-619d41d4f172 · outbound

This paper cites In: 2023 4th International Conference on Artificial Intelligence, Robotics and Control (AIRC), pp.

Foundations of GenIR In: 2023 4th International Conference on Artificial Intelligence, Robotics and Control (AIRC), pp

Reference 74

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.978972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.978972Z digest=sha256:db7a940e9836f23f21636b502d35db05258cb09d7e078c9536fdb9fcb2192c63

Observation 5ce090da-e4e6-494b-a5ac-0c585eb4eff8 · outbound

This paper cites Computer Science.

Foundations of GenIR Computer Science

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.983707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.983707Z digest=sha256:9c575944882c5ecaa4f23e879aea3e67dc1a57daeb51ecde8e3b4a33fd347e4e

Observation df1bfd63-9478-4e67-a04b-c0d27e5c419c · outbound

This paper cites an unresolved cited work.

Foundations of GenIR Unresolved cited work

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.988281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.988281Z digest=sha256:b6d3ee059c835ed88263967b960a0e6af56654cecafe6b0d8fec04b90a4caba9

Observation f50ed4d1-97eb-4483-8cd0-e447c8202798 · outbound

This paper cites Behaviour & Information Technology, 1–14 (2023).

Foundations of GenIR Behaviour & Information Technology, 1–14 (2023)

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.994380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.994380Z digest=sha256:e7dbb65b1cafaa5d5ad3a69c9d614cf1dad3ffef5d29f4d1c7c84decb8be7b4f

Observation 450e57c7-6c74-4151-9669-f247042d0646 · outbound

This paper cites In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp.

Foundations of GenIR In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:04.999319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:04.999319Z digest=sha256:0f3b3cd363be2bd30dc7eeda9cd78f91ed24aec3b2c0b9b73c3996861289bbc8

Observation d5859a09-29db-4d81-9a38-81d92d27d1f4 · outbound

This paper cites an unresolved cited work.

Foundations of GenIR Unresolved cited work

Reference 79

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:05.004046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:05.004046Z digest=sha256:50b112d0582e4ddd5bc1cf54a6ce023f16ed693c34e0c683a56071105fe860de

Observation b6a907db-268f-4d09-bb29-f929cbdf904d · outbound

This paper cites ACM Computing Surveys 55(12), 1–38 (2023).

Foundations of GenIR ACM Computing Surveys 55(12), 1–38 (2023)

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:05.009489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:05.009489Z digest=sha256:0f9c6f48177ca1d7c5bc8bd3224b9ecdd996f1ddaf7aff8ba2c4ba8f37b9143c

Observation 84e76533-381c-4a24-8855-c67d94b05ff3 · outbound

This paper cites Natural Language Processing Journal 7, 100065 (2024).

Foundations of GenIR Natural Language Processing Journal 7, 100065 (2024)

Reference 81

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:05.015265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:05.015265Z digest=sha256:79681bb09ce9d941cd7679581e821e758b8beca1787a94b788cc49eab0971bdb

Observation 8d3c8ee6-ee71-4032-967f-a0d0bc431149 · outbound

This paper cites Unsupervised Domain Clusters in Pretrained Language Models.

Foundations of GenIR Unsupervised Domain Clusters in Pretrained Language Models

Reference 82

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:05.022736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:05.022736Z digest=sha256:306f0bfaaa2e150e770d90bc6f02b16dfe2f56964cd8a518adfb8f8ed0880f10

Observation 236f4df2-8587-4123-8364-636c7759d3af · outbound

This paper cites BLADE: Enhancing Black-box Large Language Models with Small Domain-Specific Models.

Foundations of GenIR BLADE: Enhancing Black-box Large Language Models with Small Domain-Specific Models

Reference 83

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:05.028210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:05.028210Z digest=sha256:7511dd7d27dff22452c44ae8d5ee875159ec47ff2a4b896b9d5f7c00edcb9bc9

Observation 41226567-e215-4db2-b1f2-93db4ca262c1 · outbound

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

Foundations of GenIR Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 84

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:05.033286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:05.033286Z digest=sha256:66c370815f72a25d3d5eb7bc2ab7f8db0e9a612a8362600d9bdc17beeda255e9

Observation c12fa4bb-d4bd-4822-bd6e-91bfd811267b · outbound

This paper cites Advances in Neural Information Processing Systems 33, 9459–9474 (2020).

Foundations of GenIR Advances in Neural Information Processing Systems 33, 9459–9474 (2020)

Reference 85

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:05.039408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:05.039408Z digest=sha256:84215ffc941cc7b5b2bc9e50cd053e70a1659c1a53f5376c28c054bcb3e9b5c7

Observation 3b6298ef-9223-4732-ad04-7b0ded99ead0 · outbound

This paper cites In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp.

Foundations of GenIR In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp

Reference 86

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:05.044132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:05.044132Z digest=sha256:1a3d37627081c7f49def427826f13ca2cf67e1324cfe11733f5e3fe40ec90cb7

Observation efe49e38-2a7c-4d96-b692-657cacbea97a · outbound

This paper cites In: 2017 International Conference on Computer, Communication and Signal Processing (ICCCSP), pp.

Foundations of GenIR In: 2017 International Conference on Computer, Communication and Signal Processing (ICCCSP), pp

Reference 87

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:05.050571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:05.050571Z digest=sha256:f5a33e2b828d87b8466017fb3cc1068ac38b4731e62eb7e15e4861b63923ec06

Observation a1411380-2a80-4dbe-abd2-e0c8147424b1 · outbound

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

Foundations of GenIR In: Proceedings of the AAAI Conference on Artificial Intelligence, vol

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:05.055353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:05.055353Z digest=sha256:b9d645e0eea3a77c2ead84e0e6ba831dd7f0558ef2b8e37beea4c58bcf8b48ca

Observation e8c2b3d6-71fb-4268-8187-aec761e9e73f · outbound

This paper cites an unresolved cited work.

Foundations of GenIR Unresolved cited work

Reference 89

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:05.060195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:05.060195Z digest=sha256:26b040ba55b21664dda9726013f27ede26c31794dd551189dff31ae2db1d4caf

Observation fa93e3b5-ffe8-4c7c-a968-0e931204b075 · outbound

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

Foundations of GenIR Retrieval-Augmented Generation for AI-Generated Content: A Survey

Reference 90

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:05.064755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:05.064755Z digest=sha256:ff8ef337b2089a7abc8bb359da608a6f4491f29b9d1793f40443151c59d40222

Observation c682de71-0f1e-4781-a61a-6929e423f513 · outbound

This paper cites In: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 6: Tutorial Abstracts), pp.

Foundations of GenIR In: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 6: Tutorial Abstracts), pp

Reference 91

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:05.069525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:05.069525Z digest=sha256:ab5f44c69b1a33045008ecb79c69d604a2258850c1c1a12145bda0be9dad560d

Observation e56cb818-4678-47a5-97f8-6e2ee4aa19f4 · outbound

This paper cites In: International Conference on Machine Learning, pp.

Foundations of GenIR In: International Conference on Machine Learning, pp

Reference 92

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:05.074138Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:05.074138Z digest=sha256:b0624864a080e65075b2985622ae502753c34f0b0a501db7e744c541aead4981

Observation 69c553ca-97e1-46b9-b06b-242b200c3685 · outbound

This paper cites Query Rewriting for Retrieval-Augmented Large Language Models.

Foundations of GenIR Query Rewriting for Retrieval-Augmented Large Language Models

Reference 93

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:05.079524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:05.079524Z digest=sha256:3546e6424342957fc2f9c58bed02cf844f3f7b0f373afbaac7f34c4760d739e7

Observation b56c2ec3-e013-45d0-a781-6e9baeab55c8 · outbound

This paper cites Frontiers of Computer Science 18(6), 186345 (2024).

Foundations of GenIR Frontiers of Computer Science 18(6), 186345 (2024)

Reference 94

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:05.084327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:05.084327Z digest=sha256:a7e296f53a601c303e5cf974ebac2d00b709f39a86e479f1d22cacac65344d70

Observation 478bfc3f-3903-48a7-a538-a240a5b36eeb · outbound

This paper cites an unresolved cited work.

Foundations of GenIR Unresolved cited work

Reference 95

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:05.089219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:05.089219Z digest=sha256:868aac0e89544a4c558a063add27578cd9858e10605e0fd1fe92ce12d1221b31

Observation 0fbb3a26-0b48-4dfd-93bc-1058f8c0afa7 · outbound

This paper cites In: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp.

Foundations of GenIR In: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp

Reference 96

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:05.094133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:05.094133Z digest=sha256:f1757eb2854aa7c4f0ab194de3b44c69132df095efd420ef16fae7791f2eaa4b

Observation 398b2800-6b3e-4b5a-91cd-23c6c5d30c4c · outbound

This paper cites Foundations and Trends® in Information Retrieval 3(4), 333–389 (2009).

Foundations of GenIR Foundations and Trends® in Information Retrieval 3(4), 333–389 (2009)

Reference 97

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:05.099364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:05.099364Z digest=sha256:1b1c4e5c685722c7ea3a5c6efb97e7279c6be71a2bc41fe887f66b0fd2eb465e

Observation 27eaf15c-2d18-4e15-a576-9270a14dc510 · outbound

This paper cites RaFe: Ranking Feedback Improves Query Rewriting for RAG.

Foundations of GenIR RaFe: Ranking Feedback Improves Query Rewriting for RAG

Reference 98

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:05.104308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:05.104308Z digest=sha256:efface7115883500e9537db7b1275cc1e977b66d88cacce350ef449e6f7d73d8

Observation e754233c-c76d-4af5-803f-dafb98fe59a0 · outbound

This paper cites RQ-RAG: Learning to Refine Queries for Retrieval Augmented Generation.

Foundations of GenIR RQ-RAG: Learning to Refine Queries for Retrieval Augmented Generation

Reference 99

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:05.109298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:05.109298Z digest=sha256:6326d204c48e3a492f2e9e437c7512ebdb9c250784ed0e5c3afb24bea64448d0

Observation bdaf84f7-c961-44a2-a4c3-fb640402abfa · outbound

This paper cites Long-context LLMs Struggle with Long In-context Learning.

Foundations of GenIR Long-context LLMs Struggle with Long In-context Learning

Reference 100

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:05.114246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:05.114246Z digest=sha256:78ba64d1c521c500c1fd23d067ff4aa4d8b4b55f0c352053ca43688802749627

Observation 330e1733-069d-4868-ae34-b09a9d6d312c · outbound

This paper cites Transactions of the Association for Computational Linguistics 12, 157–173 (2024).

Foundations of GenIR Transactions of the Association for Computational Linguistics 12, 157–173 (2024)

Reference 101

Resolution
unresolved
no resolver link, observed 2026-08-10T22:06:05.124717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:05.124717Z digest=sha256:a24aeb4cb136df895daa552b651142ea3205285b39867ad18a31efd29cecf9c0

Pith citing papers

Observation 993207e2-5210-4d40-9917-645e0b93b62e · inbound

UXR PoV for Neuroinclusive Emotion Regulation cites this paper.

UXR PoV for Neuroinclusive Emotion Regulation Foundations of GenIR

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-07-01T20:16:12.143281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-06-28T21:20:42.329518Z digest=sha256:84bc8be746d5b0580637e7c3046b4d64da1483cdfd22c00d270d695c1ec44773