Pith. sign in

Paper Citation Record · LEDGER

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks

As of 15 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2411.19689.

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

pith.paper-citation-record.v1
2411.19689 v1

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T05:58:26.955510Z

measured 53 of 53 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

53 of 53 outbound references displayed

  • verified exact2
  • verified fuzzy18
  • unresolved32
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 576df5ef-aac9-4c9f-8e19-5c6a6191d2c2 · outbound

This paper cites Synthetic Dialogue Dataset Generation using LLM Agents.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Synthetic Dialogue Dataset Generation using LLM Agents

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-12T05:58:26.123358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T05:58:26.123358Z digest=sha256:494ef4665e65ba89b99fe4de9f38c34e501c1b71b367a4ccb22d57cfed84cc7a

Observation 1484ac39-c9fc-4e15-a26e-188c1bc2e1c0 · outbound

This paper cites an unresolved cited work.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-08-12T05:58:29.360498Z

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=arxiv_source observed=2026-08-12T05:58:26.176067Z digest=sha256:1ec19bc6b9af01d07b78585df6fe4ca691c179bf1fc25ec64fceab46178c0815

Observation 7a37b881-2a50-40be-9ad9-3ceac81b00fd · outbound

This paper cites and Clarke, V.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks and Clarke, V

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:58:29.346980Z

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=arxiv_source observed=2026-08-12T05:58:26.197078Z digest=sha256:1ed9891b084333bb43596757e3034a6c9f0936dfd4cd447bba24a94333839789

Observation 1635f366-7f3c-4589-b9aa-d11793b14c6a · outbound

This paper cites Taskmaster-1: Toward a Realistic and Diverse Dialog Dataset.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Taskmaster-1: Toward a Realistic and Diverse Dialog Dataset

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-12T05:58:26.202538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T05:58:26.202538Z digest=sha256:bca912010c90e8babc8ae30e77d29e777f323b3ab287d8c287b1e997a3c90285

Observation 59ca0fc6-34d2-46f6-8c11-535fa034bfd0 · outbound

This paper cites and Davidson, T.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks and Davidson, T

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:58:29.332728Z

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=arxiv_source observed=2026-08-12T05:58:26.207915Z digest=sha256:a81a3a9fc2f3bd9a9d49921628a56ab7a6affaecdd5544d1730e9d1459555408

Observation 0bbc3fb3-20ac-412d-b636-61745c4e9e2c · outbound

This paper cites Scaling Synthetic Data Creation with 1,000,000,000 Personas.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Scaling Synthetic Data Creation with 1,000,000,000 Personas

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-12T05:58:26.212367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T05:58:26.212367Z digest=sha256:bc9ef15b2e5ab6347a30204037d7dc0f87c497e6fff1378d866dc2593a3e6350

Observation 1688e8e2-1285-4065-a3a7-39286dfe81ba · outbound

This paper cites and Mago, V.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks and Mago, V

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:58:29.317408Z

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=arxiv_source observed=2026-08-12T05:58:26.217506Z digest=sha256:68cb02eaf5d7586183e92777a153378ee20f5b5fd9e1d69243d71c4fc18e3a29

Observation 3ba0a2e6-e0fa-4c44-8302-76655805b921 · outbound

This paper cites S., Ceder, G., Persson, K.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks S., Ceder, G., Persson, K

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:58:29.206086Z

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=arxiv_source observed=2026-08-12T05:58:26.222423Z digest=sha256:03787d114db5cb9f7bdf7ab826c50b30e98ba014f2774a3c45a8cc1bd128d5e2

Observation 124f7fcb-7e9b-41f5-b1c8-181aff81d874 · outbound

This paper cites LLM-in-the-loop: Leveraging Large Language Model for Thematic Analysis.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks LLM-in-the-loop: Leveraging Large Language Model for Thematic Analysis

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-12T05:58:26.227286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T05:58:26.227286Z digest=sha256:a7ea07eac9d6756931e63914f4d28ec0c94056c381145aa93a60b93ebe4b8d3d

Observation 56171602-bf22-4ade-a07c-ff75364099f3 · outbound

This paper cites Structured information extraction from complex scientific text with fine-tuned large language models.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Structured information extraction from complex scientific text with fine-tuned large language models

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-12T05:58:26.232538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T05:58:26.232538Z digest=sha256:6f90bf640670583aaf44be1393723938b31fbaf81d882112435c029362f7503f

Observation adc4d625-b378-4cfa-b170-31c5521d5fc2 · outbound

This paper cites and Caragea, C.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks and Caragea, C

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:58:29.098188Z

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=arxiv_source observed=2026-08-12T05:58:26.237781Z digest=sha256:c7c11795f956c517b5895fd82f97e5824eab8b8eb084d33b4622803ad552fb53

Observation 7f89a95a-2295-43f8-bb8e-430d3bfe71dd · outbound

This paper cites M., and Katz, A.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks M., and Katz, A

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:58:29.082310Z

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=arxiv_source observed=2026-08-12T05:58:26.242773Z digest=sha256:2d22ee7c85d2469c64739886401e82c2c593259f26aabb2c9bcc1fc54c6c329a

Observation 07d6eac2-01a3-452c-9684-e47677ce17fb · outbound

This paper cites A., Montiel, R., Ledeneva, Y., Rend \'o n, E., Gelbukh, A., and Cruz, R.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks A., Montiel, R., Ledeneva, Y., Rend \'o n, E., Gelbukh, A., and Cruz, R

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:58:29.058713Z

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=arxiv_source observed=2026-08-12T05:58:26.247384Z digest=sha256:b8221306aab38baa772b4b1e861f63a8a21a986b0ce6cc3d7b1a80ac7bec2ffe

Observation 1c80c45b-d215-4ad1-a85b-d91854228580 · outbound

This paper cites Text Encoders Lack Knowledge: Leveraging Generative LLMs for Domain-Specific Semantic Textual Similarity.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Text Encoders Lack Knowledge: Leveraging Generative LLMs for Domain-Specific Semantic Textual Similarity

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-12T05:58:26.252109Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T05:58:26.252109Z digest=sha256:5b3e401b18a730ddd50d0f5ef892249f5cf4be85221ee10270dd88653d60545b

Observation e17c056c-fc25-4fc8-a48c-eafa9e9879f9 · outbound

This paper cites an unresolved cited work.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Unresolved cited work

Reference 15

Resolution
unresolved
raw_fallback, observed 2026-08-12T05:58:28.864469Z

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=arxiv_source observed=2026-08-12T05:58:26.257084Z digest=sha256:5a1d868ad87b09d39cf65b667bc57e0f552275885f085c28db8c8848a32ec4b1

Observation 53bb719b-c06a-43af-bd25-5f8fbdef6e0b · outbound

This paper cites H., Hao, X., Jaber, B., Reddy, S., Kartha, R., et al.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks H., Hao, X., Jaber, B., Reddy, S., Kartha, R., et al

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:58:28.850334Z

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=arxiv_source observed=2026-08-12T05:58:26.261352Z digest=sha256:c827614f3864a193847d9160d94d2ed11d4452778022196c4e625be737371199

Observation 6c77f10d-477f-465f-a189-bc1c128fdeab · outbound

This paper cites Generative AI for Synthetic Data Generation: Methods, Challenges and the Future.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Generative AI for Synthetic Data Generation: Methods, Challenges and the Future

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-12T05:58:26.266074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T05:58:26.266074Z digest=sha256:0916b449aaf067fe42be1dd3f9d4047ab143ea78a3f7aba6237ee4ad6f39b035

Observation 2f90153c-e495-49ce-a588-017474831660 · outbound

This paper cites an unresolved cited work.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Unresolved cited work

Reference 18

Resolution
unresolved
raw_fallback, observed 2026-08-12T05:58:28.835777Z

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=arxiv_source observed=2026-08-12T05:58:26.270704Z digest=sha256:0384b519e5559fd440e1225c6a9c1a9c81edbc9fadfbd0864b001473a1bea939

Observation baf36683-c305-42aa-83fe-af7f255510c0 · outbound

This paper cites and He, G.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks and He, G

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-12T05:58:26.275166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T05:58:26.275166Z digest=sha256:b58b09a10519bbad8c1eb3bc08b895fffcd69068177c61b2c4722dc6d30f0117

Observation 4cb18787-85d4-4b7a-afd6-2e490d798c2f · outbound

This paper cites an unresolved cited work.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Unresolved cited work

Reference 20

Resolution
unresolved
raw_fallback, observed 2026-08-12T05:58:28.752697Z

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=arxiv_source observed=2026-08-12T05:58:26.279539Z digest=sha256:7b70fb7969e86b91f350358370c9dbe59bc9cf8de7965290a2406551edfff8de

Observation a5fe8c68-063c-4304-98b6-d5726b565a2b · outbound

This paper cites Synthetic Data -- what, why and how?.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Synthetic Data -- what, why and how?

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-12T05:58:26.343484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T05:58:26.343484Z digest=sha256:dd44959146cf27844b78b7583fbbe021e008c643ac0fed7775ef7d3ea5186b22

Observation 547a9ec9-01ca-4e5f-9657-9ad615ece09b · outbound

This paper cites an unresolved cited work.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Unresolved cited work

Reference 22

Resolution
unresolved
raw_fallback, observed 2026-08-12T05:58:28.615182Z

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=arxiv_source observed=2026-08-12T05:58:26.396124Z digest=sha256:6c63fe0e47d116349afa937648fb3ae9e6ecaa1ede2fc7f7e3d57acc0a5b1a2f

Observation 8ff5d0f5-9044-4bb5-9932-7362d4aaef59 · outbound

This paper cites an unresolved cited work.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Unresolved cited work

Reference 23

Resolution
unresolved
raw_fallback, observed 2026-08-12T05:58:28.600898Z

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=arxiv_source observed=2026-08-12T05:58:26.510445Z digest=sha256:744a16fd3a6ce277734c5fe0939a3ac205f03394b8f0f4adea712492c0554eaa

Observation 99a74ebc-c930-4c6f-8784-5164734e276f · outbound

This paper cites and Nithya, M.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks and Nithya, M

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:58:28.585838Z

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=arxiv_source observed=2026-08-12T05:58:26.641576Z digest=sha256:aad9773e4e2a21ce9125341d6fcd8d3cd7ba12078e280597e8d8d5eb9b75ee77

Observation 55e657a7-dbef-491c-9090-9b8a5d388cf9 · outbound

This paper cites Do Question Answering Modeling Improvements Hold Across Benchmarks?.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Do Question Answering Modeling Improvements Hold Across Benchmarks?

Reference 25

Resolution
metadata mismatch
local_arxiv, observed 2026-08-12T05:58:27.504028Z

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=arxiv_source observed=2026-08-12T05:58:26.680734Z digest=sha256:322122b9a255b329aa3eaa140c1fb991ac94ce9d1ac32aacb46e1479cb56ee22

Observation 7f1f29c6-02e5-4fc7-91af-49baa34c7824 · outbound

This paper cites Section 4: Consulting residents.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Section 4: Consulting residents

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:58:28.378191Z

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=arxiv_source observed=2026-08-12T05:58:26.686100Z digest=sha256:a64ac5ba645a35fca24a77a08bb69b26f914d903bd048047163041e49e6d060c

Observation 3baed309-86e8-4011-a4a8-a0ea6718f783 · outbound

This paper cites CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-12T05:58:26.690826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T05:58:26.690826Z digest=sha256:3af598ecc305bbadffa57a8a897b715510cae262485cd36a8e1de966e0dac6aa

Observation 43c7f018-0e87-4bc6-93c5-7ddc85afd744 · outbound

This paper cites an unresolved cited work.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Unresolved cited work

Reference 28

Resolution
verified exact
raw_fallback, observed 2026-08-12T05:58:27.425764Z

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=arxiv_source observed=2026-08-12T05:58:26.695212Z digest=sha256:20014284a5340127afde0ef904de2fb1d1611920721b1cee6d2dcd78ee37ae26

Observation 6fa5b1bc-74dd-43d8-b718-822eef78aaac · outbound

This paper cites and Tarau, P.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks and Tarau, P

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:58:28.362061Z

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=arxiv_source observed=2026-08-12T05:58:26.699896Z digest=sha256:a9b1fd41f06b918b44109270dfe3c2c5fadcd6c6d55c97d0612ac70776e067ef

Observation 88890d1d-e8e1-4eb1-ad1d-27a139b58bb5 · outbound

This paper cites W., Abdi, A., and Amrit, C.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks W., Abdi, A., and Amrit, C

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:58:28.346792Z

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=arxiv_source observed=2026-08-12T05:58:26.704490Z digest=sha256:ffc595f5ae85a1ba30e383db2a700fb3fdbf8ab70de0e69c2dec8bc53562eda4

Observation 7aa55df6-4a20-4013-8bb8-3d2e8b02689b · outbound

This paper cites D., Wibawa, A.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks D., Wibawa, A

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:58:28.331833Z

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=arxiv_source observed=2026-08-12T05:58:26.708765Z digest=sha256:62ce357868be68a446fd4b333bed6a23ff364f2a59bc4fec3b598e83e2800bb3

Observation 03c1267c-266f-44e9-b357-b2c3bea3a218 · outbound

This paper cites Summarization is (Almost) Dead.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Summarization is (Almost) Dead

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-12T05:58:26.713267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T05:58:26.713267Z digest=sha256:1a9732a2e4d7825b07dfb10197ec04916de8fe61ad64985c6b2ad0ba16eef410

Observation 30c0c86b-7d8e-46d5-841f-18db388c22d5 · outbound

This paper cites Large Language Models Meet NLP: A Survey.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Large Language Models Meet NLP: A Survey

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-12T05:58:26.717679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T05:58:26.717679Z digest=sha256:48dbfbbc141050979b915d31f39f656c69d5434dd8df15039eb6516cce378df9

Observation d3391d3c-6b36-410a-8d08-41f1782449a1 · outbound

This paper cites an unresolved cited work.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Unresolved cited work

Reference 34

Resolution
unresolved
raw_fallback, observed 2026-08-12T05:58:28.221645Z

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=arxiv_source observed=2026-08-12T05:58:26.724956Z digest=sha256:7255870b21b24915c2b1b97da0be4d1e898b374a9b7e31699616a0ff7ff6a0a0

Observation f9216f90-26d6-47e5-af1a-cabf805ecc91 · outbound

This paper cites SQuAD: 100,000+ Questions for Machine Comprehension of Text.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks SQuAD: 100,000+ Questions for Machine Comprehension of Text

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-12T05:58:26.729742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T05:58:26.729742Z digest=sha256:7f620c44aad225e6fd571690710ec3cc7802632a4c48293a7148678eb8dbe598

Observation 98ab8399-e878-43ba-a809-3b395bc37eac · outbound

This paper cites an unresolved cited work.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-12T05:58:28.173123Z

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=arxiv_source observed=2026-08-12T05:58:26.734853Z digest=sha256:7fb5a74f815dbe5b6053a1f4d3a063b0f063b6eaea5c34497a122ef429be39c6

Observation d4c604b8-f3ab-445d-a657-35c96d2a0755 · outbound

This paper cites an unresolved cited work.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Unresolved cited work

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-12T05:58:26.739219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T05:58:26.739219Z digest=sha256:46e48a777dcbb958ce214dd1b0deacd83ec5008b03d53c68ca2a7b118eaab130

Observation a2e3ab1d-f39a-4d14-b09c-0c38292992fc · outbound

This paper cites an unresolved cited work.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Unresolved cited work

Reference 38

Resolution
unresolved
raw_fallback, observed 2026-08-12T05:58:28.146796Z

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=arxiv_source observed=2026-08-12T05:58:26.743482Z digest=sha256:fac729edaf7e0e1c53791da2c6a5721d02451133c1aff76bd23cb988ee750a28

Observation 319a0d42-af36-4a07-b6f6-561d06a63386 · outbound

This paper cites and Goharian, N.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks and Goharian, N

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:58:28.131075Z

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=arxiv_source observed=2026-08-12T05:58:26.748492Z digest=sha256:b74149d05ba53b2da303ee58b57271fe097dac555fca07e6ff1c12adc6a4dbd4

Observation 13f2b232-0428-4e83-9830-547a5af3d64d · outbound

This paper cites G., and Parai, G.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks G., and Parai, G

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:58:28.115347Z

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=arxiv_source observed=2026-08-12T05:58:26.753226Z digest=sha256:da42886ee6d9c060beca06656443ae165844005a5e3a5eede31d6a1a5c557746

Observation f1dae7af-ba3f-46c5-a214-5f967a7184fd · outbound

This paper cites Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-12T05:58:26.757810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T05:58:26.757810Z digest=sha256:a36445cb3d5b77bf4a80c7a696111fde43c5e82e95b53f02ef4979499b22d530

Observation 6de524ee-6073-4176-aad4-858d8a337195 · outbound

This paper cites TrustLLM: Trustworthiness in Large Language Models.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks TrustLLM: Trustworthiness in Large Language Models

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-12T05:58:26.869399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T05:58:26.869399Z digest=sha256:c2dbb3b30900530567dfa46c3b4f0e97a39672b399948e49e85ca7d7ce4b517e

Observation 03ee9cf2-57c0-4197-a214-fde9538c18e8 · outbound

This paper cites Does Synthetic Data Generation of LLMs Help Clinical Text Mining?.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Does Synthetic Data Generation of LLMs Help Clinical Text Mining?

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-12T05:58:26.908417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T05:58:26.908417Z digest=sha256:3a36777f5c26ebe020082535937b1a0e1aa0750161f836ad197d9c359e904d08

Observation 891eb302-6cd7-489b-9296-aaf1707b94d4 · outbound

This paper cites Y., and Wang, H.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Y., and Wang, H

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:58:28.051655Z

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=arxiv_source observed=2026-08-12T05:58:26.912681Z digest=sha256:68ff074e515b0f7162fe0f6eaeacc55d916c20e647fe5aeda167a5ea5d1446be

Observation 05f463ab-d05e-45a5-b8b7-fce1b9dad6ec · outbound

This paper cites an unresolved cited work.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-08-12T05:58:28.017889Z

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=arxiv_source observed=2026-08-12T05:58:26.916799Z digest=sha256:8978ad672b2bac1b4b3426e1e3111b1278b0ac9bdddd67754fae85a5069c91bf

Observation e82b3afb-fc08-46f6-8198-de5a5d0db3a7 · outbound

This paper cites an unresolved cited work.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Unresolved cited work

Reference 46

Resolution
unresolved
raw_fallback, observed 2026-08-12T05:58:28.000539Z

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=arxiv_source observed=2026-08-12T05:58:26.921907Z digest=sha256:73e2c51edcbbdcbc40c2839f0222a48a3f792c4057af89f711fc45928fb207d4

Observation a050d5f0-cb72-438c-a80a-b24597d427fd · outbound

This paper cites Large Language Models Enable Few-Shot Clustering.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Large Language Models Enable Few-Shot Clustering

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-12T05:58:26.926479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T05:58:26.926479Z digest=sha256:29fd0cf5c5cf60497a2d234664447bc9705ed197b31cc9ea6a56401cebbe132d

Observation 8afdeabe-42ec-43c9-97c3-e896fe139b3b · outbound

This paper cites an unresolved cited work.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Unresolved cited work

Reference 48

Resolution
unresolved
raw_fallback, observed 2026-08-12T05:58:27.983803Z

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=arxiv_source observed=2026-08-12T05:58:26.931613Z digest=sha256:d7cdaf730a8138c96be7c0d8da462f5e8de06708af31b205486b47da76b27142

Observation 0f691d46-0a13-45ee-811a-06a55d95a949 · outbound

This paper cites A., Ceder, G., and Jain, A.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks A., Ceder, G., and Jain, A

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:58:27.898269Z

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=arxiv_source observed=2026-08-12T05:58:26.936621Z digest=sha256:c273ab1678514e9fbc02d4a67c8723504468fed05bfa5ea3f9446f0735475a07

Observation 602d089d-efd0-480e-904a-631eefee2e3c · outbound

This paper cites an unresolved cited work.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Unresolved cited work

Reference 50

Resolution
unresolved
raw_fallback, observed 2026-08-12T05:58:27.839190Z

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=arxiv_source observed=2026-08-12T05:58:26.941392Z digest=sha256:9dfe4fec31af2ec1a9449ef0665b3bdb69dd9b3f117b72a886d6e0102d47e055

Observation 16685722-1eda-4118-bf20-988848eca9ab · outbound

This paper cites and Bo, L.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks and Bo, L

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:58:27.823251Z

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=arxiv_source observed=2026-08-12T05:58:26.946156Z digest=sha256:6235121c323b2824927b1402af92477b4b11820cd3fc7fdfaecc64f693ba20d3

Observation 3830c7e8-b4a8-4ea2-8e4d-e98746d0f966 · outbound

This paper cites Sentiment Analysis in the Era of Large Language Models: A Reality Check.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Sentiment Analysis in the Era of Large Language Models: A Reality Check

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-12T05:58:26.950731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T05:58:26.950731Z digest=sha256:e131f10a894350f3f9ab2f63315b6ce9719a573bbf10256fae957b6484b00a4e

Observation ab67b0e8-8c95-4530-b789-782946afb80a · outbound

This paper cites Zero-Shot Dialog Generation with Cross-Domain Latent Actions.

MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks Zero-Shot Dialog Generation with Cross-Domain Latent Actions

Reference 53

Resolution
verified exact
local_arxiv, observed 2026-08-12T05:58:27.062833Z

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=arxiv_source observed=2026-08-12T05:58:26.955510Z digest=sha256:a8085d37448d772e25561e429b29ebb7172a1bcf30f9eb9dd08ce871b4064986

Pith citing papers

No inbound Pith citation observations are available.