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Paper Citation Record · LEDGER

LLM Augmentations to support Analytical Reasoning over Multiple Documents

As of 15 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 1 inbound Pith citation observation for arXiv:2411.16116.

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

pith.paper-citation-record.v1
2411.16116 v1

Coverage vector

measured 69 of 69 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:34:49.122694Z

measured 70 of 70 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T15:22:12.675862Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T15:24:49.881819Z

Reference resolution

69 of 69 outbound references displayed

  • verified exact2
  • verified fuzzy38
  • unresolved29
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 97178d7d-8756-4e3e-a338-464128b1d4dc · outbound

This paper cites Large lan- guage models are zero-shot reasoners,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Large lan- guage models are zero-shot reasoners,

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-12T13:34:48.740889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:48.740889Z digest=sha256:c376e4cb783625382abf6119d611005b03c23e48368bf4ca2a7ca5876272ca88

Observation 64d9c953-5c5d-42e7-a1f6-cc217d326d91 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Chain-of-thought prompting elicits reasoning in large language models,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:50.381337Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:48.746849Z digest=sha256:b5222d3a45a3de926385ae6bd4f0f8ff6ee7c11ef362b66484dd43b1bded13b5

Observation 358dd735-0dd2-4521-956c-0fb90f65e394 · outbound

This paper cites Sparks of Artificial General Intelligence: Early experiments with GPT-4.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Sparks of Artificial General Intelligence: Early experiments with GPT-4

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-12T13:34:48.752271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:48.752271Z digest=sha256:ec2f77e6f4c94f0f91314ee2bdf2372c704fce7cb0d7e6ae2a7841512b1a6219

Observation 5c4dc8c7-d336-4a1f-8e4e-6c368f3b3d71 · outbound

This paper cites Large Language Models Humanize Technology.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Large Language Models Humanize Technology

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-08-12T13:34:49.658375Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:48.758497Z digest=sha256:48b6dede36bfb57e9b59b5fd545f040d3a55916172796df19a54573ea4ab3540

Observation afff1e5f-ada3-448e-a55e-b07ba8eb229e · outbound

This paper cites Challenges and Applications of Large Language Models.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Challenges and Applications of Large Language Models

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-12T13:34:48.764730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:48.764730Z digest=sha256:3c3c65ac3cc0deb1d9bca091ff9130b660516394e981ed4254f6248bcdfe4934

Observation f267b369-17e8-4961-a4c7-d63691428185 · outbound

This paper cites The role of large language models in medical education: applications and implications,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents The role of large language models in medical education: applications and implications,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:50.364321Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:48.770484Z digest=sha256:f1b5ace35dc7cf86eaef49c778cee8257ddac3a3ae545882d13e074067f3cc62

Observation 58f9f135-aaa9-48b5-8d0b-6c64059e82ae · outbound

This paper cites Neural methods for data-to-text generation,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Neural methods for data-to-text generation,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:50.346789Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:48.776434Z digest=sha256:8e50ae681c1c284abd693b2fd849bd9b1e2a69ef4d94a70a861b7a24d6674580

Observation 83492a82-13d6-4ad9-9fa6-c7bec95bd61f · outbound

This paper cites Characterizing the intelligence analysis process: Informing visual analytics design through a longitudinal field study,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Characterizing the intelligence analysis process: Informing visual analytics design through a longitudinal field study,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:50.328724Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:48.781848Z digest=sha256:3c9a01c2b0f9f87fc0d49036c0728228d16f761b749f93f5c090ac157245b18f

Observation 3b074f95-4d4b-463e-ab41-e9a6bfad3af6 · outbound

This paper cites Exploring the evolution of sensemaking strategies in immersive space to think,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Exploring the evolution of sensemaking strategies in immersive space to think,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:50.311179Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:48.786904Z digest=sha256:7e76818c1126e71de449481662d0f15eff149298519acfa3420c2444f87a21c1

Observation 22d4b373-c3ac-4f38-8320-f47950eeb560 · outbound

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

LLM Augmentations to support Analytical Reasoning over Multiple Documents LLaMA: Open and Efficient Foundation Language Models

Reference 10

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unresolved
no resolver link, observed 2026-08-12T13:34:48.792341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:48.792341Z digest=sha256:5f5ec97a15487b5c0bb94771d928482e224fa4adc364d810b94f2e722cd5088f

Observation c092dab2-e69c-4484-a89b-282f5c4dfed2 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-12T13:34:48.797767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:48.797767Z digest=sha256:00f2bb0db64260a7f520bdc3e17753f4a51e41a807410b6d17719abc5dc3ed70

Observation 7a32c34b-499d-469f-bbb3-b5d5af95fcbd · outbound

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

LLM Augmentations to support Analytical Reasoning over Multiple Documents Training language models to follow instructions with human feedback,

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-12T13:34:48.803478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:48.803478Z digest=sha256:d9bc6696a9e3ebdef87316062cf20a1a1a8dbb17c8991a1779839e2c2f089360

Observation 56789b4d-0082-42d3-9ea4-c2c75309d9ee · outbound

This paper cites Tree of thoughts: Deliberate problem solving with large language models,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Tree of thoughts: Deliberate problem solving with large language models,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:50.281874Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:48.809555Z digest=sha256:c5c79b46103f6956a6cb13da6918bf123f8f9c111e4fa076db9ee712ddbfb01e

Observation 1bd5fd97-578e-4299-88f2-df64ecd5d902 · outbound

This paper cites Graph of thoughts: Solving elaborate problems with large language models,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Graph of thoughts: Solving elaborate problems with large language models,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:50.264650Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:48.815031Z digest=sha256:0a712205bff790eaeed1ab755992164fdc3036abfaff2cce1b947c99b4f67efa

Observation 17ad4d8c-999e-4894-ad17-a56c569c54af · outbound

This paper cites Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models

Reference 15

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unresolved
no resolver link, observed 2026-08-12T13:34:48.820114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:48.820114Z digest=sha256:0dfab047d4c4dd9120b3325c96fb641b5d1a8919b785cad9b51466ab72d6cc49

Observation fb33b116-7a0c-4d09-add2-bb487ab5108c · outbound

This paper cites Generative agents: Interactive simulacra of human behavior,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Generative agents: Interactive simulacra of human behavior,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:50.246456Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:48.825331Z digest=sha256:6d7b773f1f4cd4feda50da12657f09d4168b5fbe93f5011f5469ef876714668e

Observation d3dde1d2-ef27-4354-9940-409087c6d7d1 · outbound

This paper cites MTEB: Massive Text Embedding Benchmark.

LLM Augmentations to support Analytical Reasoning over Multiple Documents MTEB: Massive Text Embedding Benchmark

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-12T13:34:48.830797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:48.830797Z digest=sha256:2b1ba5966838c123737fa54f9fa6d44e19e925acb73d007963aad793d5b3dc62

Observation feba8d01-9de9-46eb-8ea3-1372e9003797 · outbound

This paper cites Embedding-based retrieval in facebook search,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Embedding-based retrieval in facebook search,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:50.229053Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:48.836410Z digest=sha256:55fbf152ac6d9a77d627614c28efb63533ea1ae92c06aa8ac0590805a82d34f1

Observation b3b3829f-4abd-44d6-a50c-1c44437fcf8c · outbound

This paper cites One embedder, any task: Instruction-finetuned text embeddings,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents One embedder, any task: Instruction-finetuned text embeddings,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:50.211906Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:48.841748Z digest=sha256:8b8aabdf2c1d9b542973fd0a4fe9c63e3a714758c52317f3ead4830ed16126a8

Observation 4284f062-152c-4ad8-8450-d152679c6498 · outbound

This paper cites Mistral 7B.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Mistral 7B

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-12T13:34:48.847447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:48.847447Z digest=sha256:7102cdf27957fc5e231f6520afc4242c30c7fdfdbb7db4274b4357ca3cbdf796

Observation 7927ed40-1018-4e97-ba40-c9aa4b5ff48c · outbound

This paper cites Gemma: Open Models Based on Gemini Research and Technology.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Gemma: Open Models Based on Gemini Research and Technology

Reference 21

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unresolved
no resolver link, observed 2026-08-12T13:34:48.853835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:48.853835Z digest=sha256:97be8c62aefd76d338dba05108fa3ff921e02ed92914cb7a90800107e91ab491

Observation 5af7f5a4-a2e0-4fb7-920e-ae6e1cbd8340 · outbound

This paper cites Where do i start? algorithmic strategies to guide intelligence analysts,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Where do i start? algorithmic strategies to guide intelligence analysts,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:50.194192Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:48.859629Z digest=sha256:c8c5022cfd2ce63fb169328365791151ab674bacfcd56281660cb9c72d6aa4ac

Observation 9723589d-8ff1-48f0-b25f-f012717ddb8a · outbound

This paper cites Principles and tools for collaborative entity-based intelligence analysis,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Principles and tools for collaborative entity-based intelligence analysis,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:50.176169Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:48.869452Z digest=sha256:b9c5319a85d994afe01d743151f1a2156e566545f6697708c3404da4dc6e112c

Observation b6acc5fa-b08f-4a75-a970-b6f5c85259ae · outbound

This paper cites Storytelling in entity networks to support intelligence analysts,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Storytelling in entity networks to support intelligence analysts,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:50.157323Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:48.875083Z digest=sha256:45be4eeafd4e6352026d623a89e380b251f9504b2a2a161d8464ed924038cbb2

Observation 38b40cec-7ef0-4823-bf82-dc017afe84b6 · outbound

This paper cites Entity workspace: An evidence file that aids memory, inference, and reading,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Entity workspace: An evidence file that aids memory, inference, and reading,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:50.137434Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:48.884236Z digest=sha256:96ff677c96f633bea800367e7c83ababdf873ed894c58e00d429115aba91c1cf

Observation 548b0295-14a2-4c0f-9a71-87dccead26ff · outbound

This paper cites Combining computational analyses and interactive visualization for document exploration and sensemaking in jigsaw,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Combining computational analyses and interactive visualization for document exploration and sensemaking in jigsaw,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:50.119113Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:48.891335Z digest=sha256:858ed8ec0410696523ef58a909c2b423c23e5c2fab8e2a5fcebb714f80bc2ec4

Observation ba90782f-f9db-43b2-81a1-6f061f9cd7b2 · outbound

This paper cites Jigsaw: supporting investiga- tive analysis through interactive visualization,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Jigsaw: supporting investiga- tive analysis through interactive visualization,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:50.100092Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:48.898085Z digest=sha256:9e722b91cf27a15b5df301d8c8cd3754ae945afeb21e8bbb8e0e57a740424797

Observation 08116e0a-9341-4843-89fa-86d61077aa77 · outbound

This paper cites Modern hierarchical, agglomerative clustering algorithms,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Modern hierarchical, agglomerative clustering algorithms,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:50.082102Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:48.904315Z digest=sha256:107fda03c28bdf66f5aab31e866cb770995f428445def91e4a436530610b1ab0

Observation edede713-ddd6-47cd-bff8-dd4f9ec28cd0 · outbound

This paper cites Birch: an efficient data clustering method for very large databases,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Birch: an efficient data clustering method for very large databases,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:50.064128Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:48.910567Z digest=sha256:9c95964b74bd5c142b9d3f7c6f7de3fd11423d25c3e9f6fbcaa86147623610fd

Observation 8b516e60-e880-46a1-9cb5-4c2a29da89b9 · outbound

This paper cites Rouge: A package for automatic evaluation of summaries,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Rouge: A package for automatic evaluation of summaries,

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-12T13:34:48.916289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:48.916289Z digest=sha256:1a69d61edd31550cd17e642e3c5ee8e50ef0f9fa31e462c38a482e0193c0a7b3

Observation f5f2a334-77e7-4425-98c6-ddbae986cc8b · outbound

This paper cites Meteor: an automatic metric for mt evaluation with high levels of correlation with human judgments,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Meteor: an automatic metric for mt evaluation with high levels of correlation with human judgments,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:50.034790Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:48.921467Z digest=sha256:580b06d4d31d7a459880c498e9dd53d92798988284ffe3bc72d46e0dd3efaa21

Observation d6930612-c5ad-4e84-9031-c9db5ff16bf5 · outbound

This paper cites GPT-4 Technical Report.

LLM Augmentations to support Analytical Reasoning over Multiple Documents GPT-4 Technical Report

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-12T13:34:48.926920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:48.926920Z digest=sha256:2a165d5c867405a16d09964c4560358d0739cebbfd31f4ec77a58501cb857af7

Observation 3c473a1a-6788-482a-84d6-dfd371f60537 · outbound

This paper cites Judging llm-as-a-judge with mt-bench and chatbot arena,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Judging llm-as-a-judge with mt-bench and chatbot arena,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:50.017871Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:48.932275Z digest=sha256:b6e2160bae42e66298b68e2edb8a1e2135f761ad5d8d37abf2a1c3bae94329fc

Observation 555a7169-3c26-42c0-adad-edb59dc0fff4 · outbound

This paper cites GPTScore: Evaluate as You Desire.

LLM Augmentations to support Analytical Reasoning over Multiple Documents GPTScore: Evaluate as You Desire

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-12T13:34:48.937727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:48.937727Z digest=sha256:5354587d168ee8391ef95308203f0f11683269201b294d2430e4481aafc5c004

Observation 3c8bd8cb-bfd3-46f0-ae0f-743a82667f17 · outbound

This paper cites Generative Judge for Evaluating Alignment.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Generative Judge for Evaluating Alignment

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-12T13:34:48.943276Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:48.943276Z digest=sha256:fe58d7eee90bd76b083654324b6a00a347286269ee5103f5330c105069639611

Observation 5761062c-4fdb-49db-8c14-245720ef9903 · outbound

This paper cites An Empirical Study of LLM-as-a-Judge for LLM Evaluation: Fine-tuned Judge Model is not a General Substitute for GPT-4.

LLM Augmentations to support Analytical Reasoning over Multiple Documents An Empirical Study of LLM-as-a-Judge for LLM Evaluation: Fine-tuned Judge Model is not a General Substitute for GPT-4

Reference 36

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no resolver link, observed 2026-08-12T13:34:48.948723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:48.948723Z digest=sha256:aacf1a75257cf87db6f5a60c0858eb583abf4992e69b60b2e32ea827a3aace51

Observation 75ac56b7-dcb6-4e3b-a2a5-33bde934c0b3 · outbound

This paper cites Is gpt-4 a reliable rater? evaluating consistency in gpt-4’s text ratings,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Is gpt-4 a reliable rater? evaluating consistency in gpt-4’s text ratings,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:50.001341Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:48.954571Z digest=sha256:c68e4fc46f32f69e5c28fa246eea97b28f04c44684d49c9b6651924ce5dca7c7

Observation e68ac3ed-5b32-44f7-8074-b137d0eeeedd · outbound

This paper cites Self-Instruct: Aligning Language Models with Self-Generated Instructions.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Self-Instruct: Aligning Language Models with Self-Generated Instructions

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-12T13:34:48.959701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:48.959701Z digest=sha256:002a581bb59280955075c3283d11b41053404a62db8b87942f183c48713cb62a

Observation 1b5bb2c8-2174-4ea5-a394-f1f6a68db120 · outbound

This paper cites LMFlow: An Extensible Toolkit for Finetuning and Inference of Large Foundation Models.

LLM Augmentations to support Analytical Reasoning over Multiple Documents LMFlow: An Extensible Toolkit for Finetuning and Inference of Large Foundation Models

Reference 39

Resolution
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no resolver link, observed 2026-08-12T13:34:48.965055Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:48.965055Z digest=sha256:3b2d66779b070f9c6b11551abc6466d8220fc49edd6d64cd90f0d659afbe3761

Observation c4a211ed-c134-4ee7-b3ce-9864ab9dcd76 · outbound

This paper cites Automatic Story Generation: Challenges and Attempts.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Automatic Story Generation: Challenges and Attempts

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-12T13:34:48.970516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:48.970516Z digest=sha256:7c699c8f8338ed3ed8c69cd19d8384c26ea1c1dd444774dc8e4893fa98f6f2d3

Observation f0fc34a7-8fb8-4989-bc97-84d36df7d236 · outbound

This paper cites gkamradt/LLMTest needleinahaystack,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents gkamradt/LLMTest needleinahaystack,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:49.984947Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:48.976076Z digest=sha256:bd2cb84f160304b2433a0cf608b3bf282058201a2481ebfa8733b1f61239dc07

Observation 95630ef9-7b12-44e1-bae4-fb204437ef6d · outbound

This paper cites Lost in the middle: How language models use long contexts,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Lost in the middle: How language models use long contexts,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:49.968831Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:48.981164Z digest=sha256:1eec1ecdc5fd22f5ef0458906367a885bcba99588187f3329cb277e5934e7cb3

Observation c1b8f89f-985a-4bf8-ab6d-58947229a7f2 · outbound

This paper cites Learning to Reason with LLMs.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Learning to Reason with LLMs

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:49.951796Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:48.986047Z digest=sha256:1bd86fbbeb1358a18d16086312dcf649fc3824a416ebfb3a225bf1ab7cb3323f

Observation f294a0ac-badc-4789-8893-9242fc83857a · outbound

This paper cites BERTScore: Evaluating Text Generation with BERT.

LLM Augmentations to support Analytical Reasoning over Multiple Documents BERTScore: Evaluating Text Generation with BERT

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-12T13:34:48.991342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:48.991342Z digest=sha256:58f580e5faccb424ecabfc24158a7da66924cd20414d8a32f5c75d714c043063

Observation 46de8d41-b5b3-4b2e-897d-ba747a1720ef · outbound

This paper cites G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment.

LLM Augmentations to support Analytical Reasoning over Multiple Documents G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-12T13:34:48.996642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:48.996642Z digest=sha256:008336e2aac1e12c413764623bc6513436294dc1ad03ddd0260c5b16297df835

Observation 41352ee6-33dd-438d-ad80-d43e9dfffd17 · outbound

This paper cites Crescent Train New York, Atlanta, New Orleans | Amtrak.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Crescent Train New York, Atlanta, New Orleans | Amtrak

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:49.935351Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:49.001738Z digest=sha256:bf43abd1f77a96eac246b9fa82ed3476d0cc81f1672706755221c7c1ccec02a5

Observation 62ccd8f8-422b-4ecd-867e-7ded7f50f0df · outbound

This paper cites The flan collection: Designing data and methods for effective instruction tuning,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents The flan collection: Designing data and methods for effective instruction tuning,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:49.918275Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:49.006766Z digest=sha256:2ec4705bcb30256238332bbb17c2f7bdaaaca72e52d2edf91d03a6d117afa84a

Observation f6e6c9c3-3b77-4d83-a15a-4e7e70ad4dbc · outbound

This paper cites PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts.

LLM Augmentations to support Analytical Reasoning over Multiple Documents PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-12T13:34:49.011810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:49.011810Z digest=sha256:399c58cb8458f35f6feb5c7385a919c8b3314fe7fd165fb6c76d762816c23a98

Observation 5ac1c42e-44e1-4d5d-acbd-659913e2d962 · outbound

This paper cites Voyager: An Open-Ended Embodied Agent with Large Language Models.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Voyager: An Open-Ended Embodied Agent with Large Language Models

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-12T13:34:49.017021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:49.017021Z digest=sha256:761a533c88bf2ebe5a3d3d2c054454b5361a0cc84800256a649f4de8c32b47e0

Observation 94b067a7-b2f0-4b75-bbf0-43f83a4364b0 · outbound

This paper cites Mathematical discoveries from program search with large language models,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Mathematical discoveries from program search with large language models,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:49.900423Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:49.023148Z digest=sha256:57c7305524842ea9bdb648ecff93e682f181336d19e7abb86e36607ea7db83b2

Observation b66efe88-ab80-4f5b-80bb-a16ed4af366e · outbound

This paper cites Pirolli and S.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Pirolli and S

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:49.881280Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:49.029119Z digest=sha256:c27d38e884fec77f183a1b054d5d0ab1eaec1d14e940dde28c6595c9ea6ce0e5

Observation fc1ed4a1-f5db-4c93-83e9-91b94d79ba62 · outbound

This paper cites A Data–Frame Theory of Sensemaking,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents A Data–Frame Theory of Sensemaking,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:49.863390Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:49.034699Z digest=sha256:a30bd0a7657022b9eb4c796ed6716e0d8e35d0d1b48d07610dc8b90b7e93869b

Observation e2c71018-363c-424a-a9dd-2b26f6329662 · outbound

This paper cites Model-guided information discovery for in- telligence analysis,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Model-guided information discovery for in- telligence analysis,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:49.845683Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:49.040390Z digest=sha256:cbe4b31d9f3f6264e247981fb88ccc51450e1e0774e17f81b69ab46f504c5059

Observation 8bf85aed-0161-4e5f-bbf6-472c22399b11 · outbound

This paper cites A multi-agent system of evidential reasoning for intelligence analyses,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents A multi-agent system of evidential reasoning for intelligence analyses,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:49.828427Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:49.045275Z digest=sha256:4d639d4ca125e356d288813c1fd2dba97bf0e9a957f9bffda4939979a00744e5

Observation f924c3e7-6c6e-4d1a-9a49-1885d036d37d · outbound

This paper cites Interactive Storytelling over Document Collections.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Interactive Storytelling over Document Collections

Reference 55

Resolution
verified exact
local_arxiv, observed 2026-08-12T13:34:49.298766Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:49.050445Z digest=sha256:200164e2933af7ddd29103e8415f719a8547ec2a9b3033bc3d29b7d045636a84

Observation f0856303-0f37-4d14-9e2f-fd6616ea418f · outbound

This paper cites The human is the loop: new directions for visual analytics,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents The human is the loop: new directions for visual analytics,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:49.811248Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:49.055699Z digest=sha256:a06b9bd9e304f9e272553f461ccd4e4124d0be5aa1604b02bc2e332f46546841

Observation d4923a11-e777-4d95-94e1-80604aaa8ef0 · outbound

This paper cites Helping intelligence analysts make connections,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Helping intelligence analysts make connections,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:49.793507Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:49.060644Z digest=sha256:eac984231cbf182c0db32e322f5712ac84ba64cd9bbecaabc5de2e512f1548b8

Observation 0d5a67bf-2324-427c-af8a-ecb387e6c17d · outbound

This paper cites Spaces to think: A comparison of small, large, and immersive displays for the sensemaking process,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Spaces to think: A comparison of small, large, and immersive displays for the sensemaking process,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:49.773853Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:49.065623Z digest=sha256:28b2766a76a789e16ac7d8dd6a6c1505f2adaa2600cc2cf2adee6e36db0ee8c8

Observation 7e4024f8-ddae-429f-82f8-75fa8825611e · outbound

This paper cites Retrieval-augmented generation for knowledge-intensive nlp tasks,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Retrieval-augmented generation for knowledge-intensive nlp tasks,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:49.755271Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:49.070442Z digest=sha256:1f7810bda9dc26f99738e546eb781974800ecbea5a5f01b7d7865327b049ec95

Observation 368a3979-523b-46e8-a559-b77a169afd17 · outbound

This paper cites Training Language Models with Memory Augmentation.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Training Language Models with Memory Augmentation

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-12T13:34:49.075229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:49.075229Z digest=sha256:e96334c225fb4badb871967608dde736c39a32e354ccadf9e175989cfd8f0d2a

Observation 03e88976-66df-431a-aa8c-3db6479191e8 · outbound

This paper cites Self-knowledge guided retrieval augmentation for large language models,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Self-knowledge guided retrieval augmentation for large language models,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:49.736478Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:49.080933Z digest=sha256:fe5717a4674eed458b85a68a69bdbeed9b3402949ba2bae68162d08c447915aa

Observation 314f92ee-781d-4e81-808e-1cd14f1f3f76 · outbound

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

LLM Augmentations to support Analytical Reasoning over Multiple Documents Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-12T13:34:49.086245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:49.086245Z digest=sha256:fa45eaa1af886704430fc4a305fbcb7426571578d5ec8c3ec38949e04d36ce06

Observation 0385d6c4-bb41-4a1d-a67d-051051f96c78 · outbound

This paper cites Language Models that Seek for Knowledge: Modular Search & Generation for Dialogue and Prompt Completion.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Language Models that Seek for Knowledge: Modular Search & Generation for Dialogue and Prompt Completion

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-12T13:34:49.091963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:49.091963Z digest=sha256:0ae66d080347e8ffc1bf04579d72dc274578e5583aa5a59d21bab3b361bca080

Observation 9da933c3-b1c4-4508-930c-387fa9cd2e2b · outbound

This paper cites Chameleon: Plug-and-play compositional reasoning with large language models,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Chameleon: Plug-and-play compositional reasoning with large language models,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:49.717615Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:49.097052Z digest=sha256:c1ca8748e6a0725c8c0477408a2ad64435e7ed1c8200aeebad1acbcc4e29259f

Observation d4064868-eab1-4cb8-80f2-e5358369b8ea · outbound

This paper cites Toolformer: Language models can teach themselves to use tools,.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Toolformer: Language models can teach themselves to use tools,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:34:49.698425Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T13:34:49.101986Z digest=sha256:c2a9803d29c5b9477a3e1e49fd261b8494dc02f0a8416073040195884033ef38

Observation e4d0450f-5c5c-48d8-9efd-34db7aa40946 · outbound

This paper cites Graph-ToolFormer: To Empower LLMs with Graph Reasoning Ability via Prompt Augmented by ChatGPT.

LLM Augmentations to support Analytical Reasoning over Multiple Documents Graph-ToolFormer: To Empower LLMs with Graph Reasoning Ability via Prompt Augmented by ChatGPT

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-12T13:34:49.106999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:49.106999Z digest=sha256:73cd29430ace908e47ecf85d8e870bbd27664e0fc9ccb06c581a23e64d289578

Observation f746a590-a00e-469f-8ebf-1556fb80beef · outbound

This paper cites MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning.

LLM Augmentations to support Analytical Reasoning over Multiple Documents MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-12T13:34:49.112329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:49.112329Z digest=sha256:c89731bf2a0c2ec85c0e005d4f1f64855abf7f3fa8194ba2c93003497bfa0795

Observation 237cf4e9-be7b-45c8-b820-9982811043af · outbound

This paper cites TALM: Tool Augmented Language Models.

LLM Augmentations to support Analytical Reasoning over Multiple Documents TALM: Tool Augmented Language Models

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-12T13:34:49.117354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:49.117354Z digest=sha256:bb1b449f31d8063024b54929404448ebccf9a08ee9b0fcaa97806729a7c6e294

Observation 29b1ed41-b315-4249-9634-c17f9cf28882 · outbound

This paper cites ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs.

LLM Augmentations to support Analytical Reasoning over Multiple Documents ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-12T13:34:49.122694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:34:49.122694Z digest=sha256:a88d0d46a4fce841c5f103a4554ded93575bfdcb0f5c1b601b6d15417cfbede8

Pith citing papers

Observation 0feb7a87-a5dd-421c-aabd-0fb3f736b6ea · inbound

Memento: Personalized RAG-Style Long-Retention Data Scaling for META Ads Recommendation cites this paper.

Memento: Personalized RAG-Style Long-Retention Data Scaling for META Ads Recommendation LLM Augmentations to support Analytical Reasoning over Multiple Documents

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-06-30T15:24:49.883214Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-06-30T15:22:12.675862Z digest=sha256:7e6645c5f3c3e103a8d0cca2aca297eb57a153281b42fad9819d9baff8e266a8