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Paper Citation Record · LEDGER

AbstRAG: Learning to Abstract for Retrieval Problems

As of 14 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2606.09459.

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

pith.paper-citation-record.v1
2606.09459 v1

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-27T16:41:47.653574Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 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

51 of 51 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved50
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d587cc39-bd7c-4454-b504-62f28490f7d4 · outbound

This paper cites 2026 , eprint =.

AbstRAG: Learning to Abstract for Retrieval Problems 2026 , eprint =

Reference 1

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:2e535604d06106381a4d8d8c83e990ec30db60e52aa709112a8b67b2d12cb3ff

Observation f1793db3-b361-4153-a024-8aa07a357d4c · outbound

This paper cites Findings of EMNLP , year =.

AbstRAG: Learning to Abstract for Retrieval Problems Findings of EMNLP , year =

Reference 2

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:4b724b1f9c7fc42b54fbaa91db6fa080e0514c1e8bfb40e86b0126a06d595268

Observation 5e037917-9590-4a6c-8fd0-afd3fc7e4c42 · outbound

This paper cites NAACL , year =.

AbstRAG: Learning to Abstract for Retrieval Problems NAACL , year =

Reference 3

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:a4bc6fe4eb3f3522d1ef6b460891bfe23cf4c376d216be81f6da820f1b6cd3c0

Observation d6602ebb-3368-4370-978c-32e4e31d716c · outbound

This paper cites Findings of EMNLP , year =.

AbstRAG: Learning to Abstract for Retrieval Problems Findings of EMNLP , year =

Reference 4

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:972ec4d727251909d7f2bcf66cbcefd76ec9e6980b6216eb8606a3e6a5a8c204

Observation 0ec679f4-7e88-4c65-ae60-332c37ca8e57 · outbound

This paper cites EMNLP , year =.

AbstRAG: Learning to Abstract for Retrieval Problems EMNLP , year =

Reference 5

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:013dbd6d15ea47b9bc71b116a5658c39e58ad14596dc13365636c3dafcc1da5d

Observation b702c7dc-c287-48f9-8e9f-0f7fe913c516 · outbound

This paper cites Proceedings of the Fourth Workshop on Fact Extraction and.

AbstRAG: Learning to Abstract for Retrieval Problems Proceedings of the Fourth Workshop on Fact Extraction and

Reference 6

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:1b7e5686c157f5910ac035aeea5f548e982bb0d5d4aeb1842defb06d80322c0f

Observation 31a07ca1-bd79-4746-ad28-a85ed0a1d033 · outbound

This paper cites Findings of EMNLP , year =.

AbstRAG: Learning to Abstract for Retrieval Problems Findings of EMNLP , year =

Reference 7

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:efe9ed3543c0b78f1584007d6642ee690384efda031eaa2c4b74b3c08b78ae82

Observation 930e6f3c-dff8-446d-b39f-804bb88c1051 · outbound

This paper cites EMNLP , year =.

AbstRAG: Learning to Abstract for Retrieval Problems EMNLP , year =

Reference 8

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:e8369360939bc1d8c9d72c64d930a4c3b750b1e8fb782d45f79f02d002619c1b

Observation b0c27dcc-10ab-4eb3-b4f7-2fdcd1692eb2 · outbound

This paper cites Carvalho and Dhairya Dalal and Andre Freitas , title =.

AbstRAG: Learning to Abstract for Retrieval Problems Carvalho and Dhairya Dalal and Andre Freitas , title =

Reference 9

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:f6a6ebdf5932d87c0f4d9648d7ac9984dfd9dbda700f2faa1956b8afa39e4d9a

Observation 8cdf8811-da57-4898-90a5-5d9ff2e2cd40 · outbound

This paper cites NAACL , year =.

AbstRAG: Learning to Abstract for Retrieval Problems NAACL , year =

Reference 10

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:4a91b897f01f98f8973614d5b0e6ce07731657257ac408cef9d0abe3b00a9f02

Observation ad7f4606-b3ec-4cf3-9aac-318b85338d98 · outbound

This paper cites Retrieval-Augmented Generation for Knowledge-Intensive.

AbstRAG: Learning to Abstract for Retrieval Problems Retrieval-Augmented Generation for Knowledge-Intensive

Reference 11

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:16d352599d4cc4bd5c5dff7d9c8e4e46b3e190b902b0274a1a1381332cc53638

Observation a1330671-cd45-4c8e-8c60-7d6aa50b4f8e · outbound

This paper cites Dense Passage Retrieval for Open-Domain Question Answering , booktitle =.

AbstRAG: Learning to Abstract for Retrieval Problems Dense Passage Retrieval for Open-Domain Question Answering , booktitle =

Reference 12

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:d87127c70292fe6df53ca46090e5aa1d33f91a61ddb31c671d1a7135390f30bf

Observation d1ce177d-47a6-401f-93a3-5d1407167e37 · outbound

This paper cites SIGIR , year =.

AbstRAG: Learning to Abstract for Retrieval Problems SIGIR , year =

Reference 13

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:0594f3f032876d2f51e6969778f8f8c31c16533fbf2d9f692eca7723714663dd

Observation 59a6f103-00e8-4b33-8d7a-2b06730546af · outbound

This paper cites ACL , year =.

AbstRAG: Learning to Abstract for Retrieval Problems ACL , year =

Reference 14

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:fc854376950695f7d64eaca9b220ca528b0ce987a47d061dc1f8d499079e5925

Observation f6b7ec84-6ec2-4b73-b9a5-ffdb3f3bf42b · outbound

This paper cites EMNLP , year =.

AbstRAG: Learning to Abstract for Retrieval Problems EMNLP , year =

Reference 15

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:d1e4120786083b6f035172b531b550b96d7864120bff44543f4fba2d25fbcaa7

Observation f44adff0-0790-43a3-91b6-d45e5837c7b7 · outbound

This paper cites ACL , year =.

AbstRAG: Learning to Abstract for Retrieval Problems ACL , year =

Reference 16

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:79863485196278ec90cd59ca1280b67d0c787f4ef8469c999bf05bb502b00e16

Observation a5b37e23-22ff-4498-b20c-ef99e35561d9 · outbound

This paper cites Xu and Luyu Gao and Zhiqing Sun and Qian Liu and Jane Dwivedi-Yu and Yiming Yang and Jamie Callan and Graham Neubig , title =.

AbstRAG: Learning to Abstract for Retrieval Problems Xu and Luyu Gao and Zhiqing Sun and Qian Liu and Jane Dwivedi-Yu and Yiming Yang and Jamie Callan and Graham Neubig , title =

Reference 17

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:d89804210e32008c8daf5158f5921bb207f4b8f0341f49f1e4f9798589b6ca1f

Observation d0ae76c8-fc93-4809-a99c-b52fd0397e6c · outbound

This paper cites NeurIPS , year =.

AbstRAG: Learning to Abstract for Retrieval Problems NeurIPS , year =

Reference 18

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:6745cb8bee5c3b8005699ca49f46ffcf51c69fa6cef754e4351b31924d9b7baa

Observation fdf96a27-c5b7-4637-9f7a-5314c3bc5cf0 · outbound

This paper cites ICLR , year =.

AbstRAG: Learning to Abstract for Retrieval Problems ICLR , year =

Reference 19

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:7605588dbd31047d6ea069167b7bccabb83280c6bfc8e7ea3f8c50e699933cd1

Observation d15562c3-eff2-4f85-9712-822464ef424b · outbound

This paper cites 2024 , eprint =.

AbstRAG: Learning to Abstract for Retrieval Problems 2024 , eprint =

Reference 20

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:753610dc05c13bd5e5e409887d792b51cbe6f907a10008d3aefcb99c68bed610

Observation a731c48b-e602-41c2-80de-875c022da3f2 · outbound

This paper cites Dennis and Andre Freitas , title =.

AbstRAG: Learning to Abstract for Retrieval Problems Dennis and Andre Freitas , title =

Reference 21

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:8487e72d1fb07a648d4f6504a4474845c4272a53b58b5742267021f1c6064eb4

Observation e5e30993-fafb-4387-8c26-783ac13d574a · outbound

This paper cites EMNLP , year =.

AbstRAG: Learning to Abstract for Retrieval Problems EMNLP , year =

Reference 22

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:f8930c7b14b776e8af8bf6391953820811598b4f27d1cfc1a1b304d1aded62a8

Observation 91212674-1395-41fb-a2dd-fd78de713bf9 · outbound

This paper cites 2024 , eprint =.

AbstRAG: Learning to Abstract for Retrieval Problems 2024 , eprint =

Reference 23

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:0a5a78dc8971bbb502a6dfd49d20ea66906b1dd7817d5779d754c5dbc74ce161

Observation b9a88cd2-5e39-47e5-bb72-df69c011e570 · outbound

This paper cites NeurIPS Datasets and Benchmarks Track , year =.

AbstRAG: Learning to Abstract for Retrieval Problems NeurIPS Datasets and Benchmarks Track , year =

Reference 24

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:35fd343f920b61dc142f7ef621a3c488705a1ec431b3e1c6de4376eadd3eea60

Observation e42af5ad-bc72-4344-a6b2-9dd89335224d · outbound

This paper cites Transactions of the Association for Computational Linguistics , year =.

AbstRAG: Learning to Abstract for Retrieval Problems Transactions of the Association for Computational Linguistics , year =

Reference 25

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:8e8cc546c7c5433c9b3d9ebd3a3491809e843f915aeb31c4b97860e51031a00f

Observation b0369323-7210-43c4-ada3-33d5fdcdf3c2 · outbound

This paper cites NAACL , year =.

AbstRAG: Learning to Abstract for Retrieval Problems NAACL , year =

Reference 26

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:38c71625f53bee4c1db6085ffecfd55853ef343152401c74cfb0dcb76449230d

Observation 75d9be7b-dcea-4133-aa9b-fa3ac7ac1eee · outbound

This paper cites NAACL , year =.

AbstRAG: Learning to Abstract for Retrieval Problems NAACL , year =

Reference 27

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:382364bc206d0651ba466195ada1e592fafb4173b576629696abb61225159417

Observation 2538f7cd-4e04-46fe-9838-96d7e267d8f9 · outbound

This paper cites Proceedings of the 1st Workshop on Towards Knowledgeable Language Models (KnowLLM 2024) , year =.

AbstRAG: Learning to Abstract for Retrieval Problems Proceedings of the 1st Workshop on Towards Knowledgeable Language Models (KnowLLM 2024) , year =

Reference 28

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:10ea9b8898b1e1ddba9e717cad72c65279d134666badf5d762cb18c8b4e58c95

Observation d1d832ba-7bb7-41b9-af87-6302269eec24 · outbound

This paper cites 2024 , eprint =.

AbstRAG: Learning to Abstract for Retrieval Problems 2024 , eprint =

Reference 29

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:d43f9ef3836565bc73455c7003f6b21e064e1190e843d82a5c73ac4d7bb929c7

Observation a715f77f-2889-46cb-8ef2-11a993715446 · outbound

This paper cites NeurIPS , year =.

AbstRAG: Learning to Abstract for Retrieval Problems NeurIPS , year =

Reference 30

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:1f048fd6b81d09724df9de43dd5bae5ba414801c0e42ee3240f1d677a284c07d

Observation f35e1509-f0f2-4176-9787-f192afab1104 · outbound

This paper cites ACL , year =.

AbstRAG: Learning to Abstract for Retrieval Problems ACL , year =

Reference 31

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:bbebc1d04e44e40ef09757f3ca198a00abbd3e6c4d14b03666e6b1ff4416a717

Observation 8c4ac76c-f044-4eae-b7c3-54347e6db064 · outbound

This paper cites Findings of EMNLP , year =.

AbstRAG: Learning to Abstract for Retrieval Problems Findings of EMNLP , year =

Reference 32

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:b3665d2563867549744b6141437e3f59911066ef3d577e8f6e0388cedc824fc9

Observation ddb6a0fc-e167-41a8-9b0c-d33833bbd68d · outbound

This paper cites ACL , year =.

AbstRAG: Learning to Abstract for Retrieval Problems ACL , year =

Reference 33

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:74464b11f872f9b6975fc30eb2e3c4cb43a198b8697c8153146c259feb8dfbcc

Observation 6ffade46-2415-4328-b6c4-345a2202307b · outbound

This paper cites Pollock , title =.

AbstRAG: Learning to Abstract for Retrieval Problems Pollock , title =

Reference 34

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:a9027a6f98d7953dacf7f5ab500c873ee49e9b6794cc5f172d3fecfd9747173d

Observation 3d969a86-37c9-41ac-8882-07c407cf0ab2 · outbound

This paper cites Artificial Intelligence , volume =.

AbstRAG: Learning to Abstract for Retrieval Problems Artificial Intelligence , volume =

Reference 35

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:322cbbc12a16d49f2d6a3e2063f794f8f34b88015105495d762418cb523b7c8c

Observation b6b467bd-eb43-409f-862b-9a3a2f072f2a · outbound

This paper cites Handbook of Logic in Artificial Intelligence and Logic Programming, Vol.

AbstRAG: Learning to Abstract for Retrieval Problems Handbook of Logic in Artificial Intelligence and Logic Programming, Vol

Reference 36

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:780b2e0c15c39eb88359fce3065a8d1f29c325c46aa39cc3e1beb86500ed205a

Observation 7ea54576-a272-4785-ada0-efc5af6eda0a · outbound

This paper cites Nucleic Acids Research , volume =.

AbstRAG: Learning to Abstract for Retrieval Problems Nucleic Acids Research , volume =

Reference 37

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:8ed797e96f7c763abe5d56cb6f1a024448f2ecc0462fc82cb3688631dacbce36

Observation 69efb15c-1c24-48f8-a256-bd7eb201c2c6 · outbound

This paper cites Wikidata: A Free Collaborative Knowledgebase , journal =.

AbstRAG: Learning to Abstract for Retrieval Problems Wikidata: A Free Collaborative Knowledgebase , journal =

Reference 38

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:759fa375d7749bc121ea8dd14c4a7c0a95b0a90deffd9dc87ee8d05e600c26d3

Observation d9739c2d-d725-4743-a10f-fac15e3cb4bc · outbound

This paper cites Levenshtein , title =.

AbstRAG: Learning to Abstract for Retrieval Problems Levenshtein , title =

Reference 39

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:f53e9f7a17ee7fec48f701c56c1f4b3bc6032bd3d1156ea46ecd9718d8307d37

Observation 4424c22a-1812-43b3-bcf2-a38d28a7cbb0 · outbound

This paper cites ACL , pages =.

AbstRAG: Learning to Abstract for Retrieval Problems ACL , pages =

Reference 40

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Observation d92aebed-1d1b-4850-9cea-8b20e6947f9a · outbound

This paper cites Miller , title =.

AbstRAG: Learning to Abstract for Retrieval Problems Miller , title =

Reference 41

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Observation 64376ae8-a823-4631-86ab-8f09304fe380 · outbound

This paper cites an unresolved cited work.

AbstRAG: Learning to Abstract for Retrieval Problems Unresolved cited work

Reference 42

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Observation d6feffbe-6899-433a-967a-e01803b12294 · outbound

This paper cites Shannon , title =.

AbstRAG: Learning to Abstract for Retrieval Problems Shannon , title =

Reference 43

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unresolved
no resolver link, observed 2026-06-27T16:41:47.653574Z

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Observation 879f63cf-481f-480c-85a6-32f08a02f58c · outbound

This paper cites Baker and Charles J.

AbstRAG: Learning to Abstract for Retrieval Problems Baker and Charles J

Reference 44

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no resolver link, observed 2026-06-27T16:41:47.653574Z

Source-reported events for the cited work

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Observation da1c25ad-7547-4b5b-bfc7-97707ed9016b · outbound

This paper cites Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference.

AbstRAG: Learning to Abstract for Retrieval Problems Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference

Reference 45

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verified exact
local_arxiv, observed 2026-07-03T01:17:30.873171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 95f1bfd7-760e-4bad-84f8-18cca03a4033 · outbound

This paper cites SIGIR , year =.

AbstRAG: Learning to Abstract for Retrieval Problems SIGIR , year =

Reference 46

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no resolver link, observed 2026-06-27T16:41:47.653574Z

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:a683a6069e1ed0196a3e82c4dbd332c82dd33bb4db6e44bb9c88dd5b5a3d5539

Observation e739dec0-0816-4e2a-ae82-7e97da7bdad7 · outbound

This paper cites Joshi and Hanna Moazam and Heather Miller and Matei Zaharia and Christopher Potts , title =.

AbstRAG: Learning to Abstract for Retrieval Problems Joshi and Hanna Moazam and Heather Miller and Matei Zaharia and Christopher Potts , title =

Reference 47

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no resolver link, observed 2026-06-27T16:41:47.653574Z

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:f982b3b7e851fc71876157cd849bf5cfdc0be1dfa55abe8453b34eaf214aef70

Observation f1edb1e6-bce1-4ac8-a12e-d5a99f23f53a · outbound

This paper cites Findings of EMNLP , year =.

AbstRAG: Learning to Abstract for Retrieval Problems Findings of EMNLP , year =

Reference 48

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no resolver link, observed 2026-06-27T16:41:47.653574Z

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Observation 0b7241e6-5af7-471c-8d89-4d3bb6b68c43 · outbound

This paper cites Foundations and Trends in Information Retrieval , volume=.

AbstRAG: Learning to Abstract for Retrieval Problems Foundations and Trends in Information Retrieval , volume=

Reference 49

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:011c58fa2fa2e4ce665af6ac67fbf516f48271a5d52a07b550528577b2d2db84

Observation a43e917e-30de-460e-b1bf-03679f9acac5 · outbound

This paper cites NAACL , year=.

AbstRAG: Learning to Abstract for Retrieval Problems NAACL , year=

Reference 50

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no resolver link, observed 2026-06-27T16:41:47.653574Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:fd05b29c8ce19444e2875ae7a903cfb8d960adf8047cdbbe0088f55a5661a94d

Observation b4ecb797-9213-4b7d-8fce-79aa2f58907a · outbound

This paper cites Cumulated Gain-Based Evaluation of.

AbstRAG: Learning to Abstract for Retrieval Problems Cumulated Gain-Based Evaluation of

Reference 51

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source=arxiv_source observed=2026-06-27T16:41:47.653574Z digest=sha256:e6346b651a7aff9194cbb30343b74db6881502a362eed7a42cc33825b291cb14

Pith citing papers

No inbound Pith citation observations are available.