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Paper Citation Record · LEDGER

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs

As of 15 August 2026, this Paper Citation Record lists 100 of 117 outbound references and 0 inbound Pith citation observations for arXiv:2607.27379.

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

pith.paper-citation-record.v1
2607.27379 v1

Coverage vector

measured 100 of 117 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T08:29:33.483389Z

measured 100 of 100 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

100 of 117 outbound references displayed

  • verified exact2
  • verified fuzzy0
  • unresolved98
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 62272663-766c-4014-9e26-4ae274633c72 · outbound

This paper cites Transactions on Machine Learning Research , issn=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Transactions on Machine Learning Research , issn=

Reference 1

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source=arxiv_source observed=2026-08-01T08:29:21.831034Z digest=sha256:1396337b12ee74e32abc3a79ffb408c3b9688276fb345ccb944f94a6139d5cde

Observation e6b467a0-a609-44f6-8521-d38b8b0cb59a · outbound

This paper cites The Thirteenth International Conference on Learning Representations , year=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs The Thirteenth International Conference on Learning Representations , year=

Reference 2

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source=arxiv_source observed=2026-08-01T08:29:21.917747Z digest=sha256:1a0018b8e360b25f1cd7c2406389470c1f9debe60de4530f66ab9241c975d252

Observation 6452919f-36dd-42e7-ae39-f0a71ec02f92 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Advances in Neural Information Processing Systems , volume=

Reference 3

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Observation 29c84ae0-5b17-46b3-96a6-e060d2862654 · outbound

This paper cites First Conference on Language Modeling , year=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs First Conference on Language Modeling , year=

Reference 4

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Observation 89b4404c-fd04-458f-8e7d-454174037bf6 · outbound

This paper cites an unresolved cited work.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Unresolved cited work

Reference 5

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source=arxiv_source observed=2026-08-01T08:29:22.260715Z digest=sha256:623b4ca5a01a88aa7124a00d9831c826fcde1f2ce97f0720dbf0dd676bd5bad7

Observation b9f7f34d-a7bb-41a0-bc47-fa4cf4d286c8 · outbound

This paper cites Proceedings of the National Academy of Sciences , volume =.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Proceedings of the National Academy of Sciences , volume =

Reference 6

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Observation d85cee3f-bbbf-4acd-95ab-f352e566edc7 · outbound

This paper cites and Khashabi, Daniel and Hajishirzi, Hannaneh.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs and Khashabi, Daniel and Hajishirzi, Hannaneh

Reference 7

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Observation 15fb249d-7f2c-43ea-ad3a-6491c9c55cff · outbound

This paper cites an unresolved cited work.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Unresolved cited work

Reference 8

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source=arxiv_source observed=2026-08-01T08:29:22.626225Z digest=sha256:7f93b0eaa03faeb594b0bd708141010dbbbd784ab6d3b96169a87389efef84e9

Observation 46006bb2-ca04-4d32-8219-2f51dc89a483 · outbound

This paper cites Phi-4 Technical Report.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Phi-4 Technical Report

Reference 9

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source=arxiv_source observed=2026-08-01T08:29:22.804839Z digest=sha256:41ba1ecd1dc44f1d941949158f120de94157717fd0396850be2520609dbbdcd3

Observation 99974530-3104-4b72-ae1b-9ca9e0a5758a · outbound

This paper cites Behavior research methods , volume=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Behavior research methods , volume=

Reference 10

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Observation db9bc54e-dd32-40b7-b983-ac6b42223c9a · outbound

This paper cites Transactions on machine learning research , year=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Transactions on machine learning research , year=

Reference 11

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Observation bde2ab1c-5228-4e5f-aa3b-f2829f8f4838 · outbound

This paper cites Biochemia medica , volume=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Biochemia medica , volume=

Reference 12

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Observation 0c335ba3-c705-43bc-99d2-934f9c562b14 · outbound

This paper cites The Twelfth International Conference on Learning Representations , year=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs The Twelfth International Conference on Learning Representations , year=

Reference 13

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Observation 4aa0d755-d0a5-439b-9913-b09bf5df004f · outbound

This paper cites Program Synthesis with Large Language Models.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Program Synthesis with Large Language Models

Reference 14

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source=arxiv_source observed=2026-08-01T08:29:23.246352Z digest=sha256:a0893069add30f84e536a116a73009ec1ad3d6e9af2eff46b8391c9d78b8cd32

Observation ef68a31d-885e-413b-a914-ae55506515c3 · outbound

This paper cites Large Language Models as Tool Makers.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Large Language Models as Tool Makers

Reference 15

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Observation 292a3dfb-5fb4-4208-ae54-333ef4ff8a28 · outbound

This paper cites Pacific-Asia Conference on Knowledge Discovery and Data Mining , pages=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Pacific-Asia Conference on Knowledge Discovery and Data Mining , pages=

Reference 16

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Observation 22c80ace-f64c-4166-9946-16809d9d8cca · outbound

This paper cites Weaver: Foundation Models for Creative Writing.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Weaver: Foundation Models for Creative Writing

Reference 17

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source=arxiv_source observed=2026-08-01T08:29:23.511545Z digest=sha256:a6f1fdb519cf0f9b0e0a5a53f1cbdc834a93be29e8000dc4444ad6ad72eb1067

Observation a91449c5-1892-46f5-8b34-df48d72d1213 · outbound

This paper cites Bottom-Up Synthesis of Knowledge-Grounded Task-Oriented Dialogues with Iteratively Self-Refined Prompts.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Bottom-Up Synthesis of Knowledge-Grounded Task-Oriented Dialogues with Iteratively Self-Refined Prompts

Reference 18

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source=arxiv_source observed=2026-08-01T08:29:23.584140Z digest=sha256:a77e1049a992378c7789d6a57701a1e0e6df9b9b498ec019aa81c21a181f808a

Observation 1287fa7e-b81b-4b83-baa7-37bd24bc6c74 · outbound

This paper cites Advances in Neural Information Processing Systems , year=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Advances in Neural Information Processing Systems , year=

Reference 19

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Observation 37e1d918-8be5-4f96-9789-90adfe07deb9 · outbound

This paper cites ACM Transactions on Intelligent Systems and Technology , volume=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs ACM Transactions on Intelligent Systems and Technology , volume=

Reference 20

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source=arxiv_source observed=2026-08-01T08:29:23.775093Z digest=sha256:d05af434c6e41a22563d43fa7a7d1887b3f83c6b1859b7f3c558b52ebfa1364f

Observation 0240814e-cbe7-4593-a414-5e87f1277293 · outbound

This paper cites Large Language Models Can Self-Improve.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Large Language Models Can Self-Improve

Reference 21

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source=arxiv_source observed=2026-08-01T08:29:23.866629Z digest=sha256:760e6fb7a3be02efea0d7438b71241206ff7d53553f2f7aa9aae5f498bc206fa

Observation a10d0778-edd4-41ae-8250-648514badfce · outbound

This paper cites Instruction-Tuning Data Synthesis from Scratch via Web Reconstruction.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Instruction-Tuning Data Synthesis from Scratch via Web Reconstruction

Reference 22

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source=arxiv_source observed=2026-08-01T08:29:23.988683Z digest=sha256:b9c9e535ba59eb0566b048a6b18c3ebc7c71bbe24204fc2742e8317fe3da7ffa

Observation 740a9d76-eba2-4146-9d92-c955a196ad6e · outbound

This paper cites an unresolved cited work.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Unresolved cited work

Reference 23

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source=arxiv_source observed=2026-08-01T08:29:24.093736Z digest=sha256:de734801175fa3079671983e5d226abf425449df85713f3108310b81f337fb87

Observation 833b4808-5bd3-4bb3-9813-0b1c8aa47fdd · outbound

This paper cites Scaling Language Models: Methods, Analysis & Insights from Training Gopher.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Scaling Language Models: Methods, Analysis & Insights from Training Gopher

Reference 24

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Observation 5c6f5a28-7397-4829-bec9-f2509fe6e468 · outbound

This paper cites Journal of machine learning research , volume=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Journal of machine learning research , volume=

Reference 25

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source=arxiv_source observed=2026-08-01T08:29:24.267374Z digest=sha256:01f161a4683b254b7aefbcf34826180802156687a1a7756bb157c292738ece49

Observation a22ca195-5770-4d8b-8435-3742e8064db2 · outbound

This paper cites FastText.zip: Compressing text classification models.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs FastText.zip: Compressing text classification models

Reference 26

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source=arxiv_source observed=2026-08-01T08:29:24.371466Z digest=sha256:1b85b2abe1abdf0f8a39a123489eab50fcbaac77b3557a5f96f47934ad592155

Observation 016cd3fc-66a5-45a7-a73a-9df09e164f51 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Advances in Neural Information Processing Systems , volume=

Reference 27

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Observation 184f7734-68b8-4d96-8362-7da285e3e8b6 · outbound

This paper cites Proceedings.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Proceedings

Reference 28

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Observation 45287f15-ef99-4a39-bb40-d718d7d2f04a · outbound

This paper cites Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies , pages=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies , pages=

Reference 29

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Observation c46523c9-d3f2-47b8-9a0a-0f4186444fb2 · outbound

This paper cites D o G -Instruct: Towards Premium Instruction-Tuning Data via Text-Grounded Instruction Wrapping.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs D o G -Instruct: Towards Premium Instruction-Tuning Data via Text-Grounded Instruction Wrapping

Reference 30

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

source=arxiv_source observed=2026-08-01T08:29:24.766672Z digest=sha256:34dce8ed6cab6f7d6ab187633fffad90a8b205ad83a917b4e3d4b981788a2004

Observation 027c4a64-f8f8-4936-a053-98d5e6a02c25 · outbound

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HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs arXiv preprint arXiv:2504.12563 , year=

Reference 31

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Observation e835633b-d574-490a-83f9-421c3c6b087c · outbound

This paper cites LongForm: Effective Instruction Tuning with Reverse Instructions.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs LongForm: Effective Instruction Tuning with Reverse Instructions

Reference 32

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Observation db56c2a8-ce78-4023-b8a8-94406781eb39 · outbound

This paper cites The Twelfth International Conference on Learning Representations , year=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs The Twelfth International Conference on Learning Representations , year=

Reference 33

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source=arxiv_source observed=2026-08-01T08:29:25.179555Z digest=sha256:44aa34d7dd05a1f7342af32673267d26e3326c9726ed8802c4ab467eef3d4370

Observation 64541786-994b-4dd2-9e61-723b495f2370 · outbound

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

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Scaling Synthetic Data Creation with 1,000,000,000 Personas

Reference 34

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Observation 2a521d71-510a-40a0-b92c-d0ab076ca402 · outbound

This paper cites Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 35

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Observation 808cf4fb-badd-45d7-8f65-3b8326106b25 · outbound

This paper cites Learning to Generate Instruction Tuning Datasets for Zero-Shot Task Adaptation.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Learning to Generate Instruction Tuning Datasets for Zero-Shot Task Adaptation

Reference 36

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Observation 48978e7f-c215-4b5a-aa46-1cd1d3149551 · outbound

This paper cites Advances in neural information processing systems , volume=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Advances in neural information processing systems , volume=

Reference 37

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Observation 2e513a0b-9e32-4fa0-957b-167a352e75c2 · outbound

This paper cites WildChat: 1M Chat.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs WildChat: 1M Chat

Reference 38

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Observation 61858c3f-df48-4ecf-844c-3db5c342e6c3 · outbound

This paper cites 2023 , publisher =.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs 2023 , publisher =

Reference 39

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source=arxiv_source observed=2026-08-01T08:29:25.844565Z digest=sha256:e6c7e5eb58cb5cafe0fc952a9d711af5259daa6db96b77507184ff18db6a2869

Observation cd3966c5-b897-4617-86bc-ef896c3dffe2 · outbound

This paper cites Mutual Reinforcement of LLM Dialogue Synthesis and Summarization Capabilities for Few-Shot Dialogue Summarization.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Mutual Reinforcement of LLM Dialogue Synthesis and Summarization Capabilities for Few-Shot Dialogue Summarization

Reference 40

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source=arxiv_source observed=2026-08-01T08:29:25.935349Z digest=sha256:c7b81bcdc9e30cef2e01dd9ef036d387f1b76691ff5b67babc0567c44d01a1b0

Observation fba02383-15f4-46f1-a590-b1f60af61ed8 · outbound

This paper cites Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators

Reference 41

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source=arxiv_source observed=2026-08-01T08:29:26.001955Z digest=sha256:0a59fd30d296d40ca5ca00145ad9fd7920e56dc724f3d5dd5bd2c6c61f3f5a10

Observation 418dbcb1-e9c9-41db-a481-f0e5e0ea8caa · outbound

This paper cites DocTalk: Scalable Graph-based Dialogue Synthesis for Enhancing LLM Conversational Capabilities.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs DocTalk: Scalable Graph-based Dialogue Synthesis for Enhancing LLM Conversational Capabilities

Reference 42

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source=arxiv_source observed=2026-08-01T08:29:26.083292Z digest=sha256:96c219c469042006eff69e89652eb98757d8e34d945bf98abb75f28d77021696

Observation 484ada2a-a105-4872-9173-3efaf884f419 · outbound

This paper cites Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 43

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source=arxiv_source observed=2026-08-01T08:29:26.146791Z digest=sha256:f918cfc48579a4c2c1efa1e78e9735680202354e7fad796cf954dae4a8a680eb

Observation 4a907bb1-770b-4eb2-96b4-380e30bd78cf · outbound

This paper cites Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing

Reference 44

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source=arxiv_source observed=2026-08-01T08:29:26.194485Z digest=sha256:c2f45ca477f3714c8af766eeb81ff8d3521fc154fd52b82949377a2dd7d448c7

Observation 5630ac1b-8e16-4566-8c3c-34955054e99b · outbound

This paper cites Nemotron-CC: Transforming Common Crawl into a Refined Long-Horizon Pretraining Dataset.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Nemotron-CC: Transforming Common Crawl into a Refined Long-Horizon Pretraining Dataset

Reference 45

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source=arxiv_source observed=2026-08-01T08:29:26.275192Z digest=sha256:deb8dd9e0354727fc2ba9f4275e6d3e1a73c0c9e11769125fab295893d9216a6

Observation 56b4b924-e18e-4cd9-a987-f96799109279 · outbound

This paper cites Reformulation for Pretraining Data Augmentation.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Reformulation for Pretraining Data Augmentation

Reference 46

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source=arxiv_source observed=2026-08-01T08:29:26.385256Z digest=sha256:a1e0f3dd212c0dec4e0178047ba079d94550d3dff913a7b95bf183df8e65de4e

Observation 4a8cd1a4-89c4-4913-ae09-c3f9c2b139a2 · outbound

This paper cites Towards General Text Embeddings with Multi-stage Contrastive Learning.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Towards General Text Embeddings with Multi-stage Contrastive Learning

Reference 47

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source=arxiv_source observed=2026-08-01T08:29:26.446342Z digest=sha256:0573d428ce5e3b593e4e50ac6539b92e0431d7bacaab670656c32d1bc18a1e24

Observation a13627c0-5efb-46d7-bf49-413eaf7737ec · outbound

This paper cites an unresolved cited work.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Unresolved cited work

Reference 48

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source=arxiv_source observed=2026-08-01T08:29:26.495804Z digest=sha256:b490389e841a0122282e1985ed0c9a876aaf3448d35f3a831656c4236dc36a48

Observation a144f285-6d21-41aa-ac63-58e149511a35 · outbound

This paper cites From Real to Synthetic: Synthesizing Millions of Diversified and Complicated User Instructions with Attributed Grounding.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs From Real to Synthetic: Synthesizing Millions of Diversified and Complicated User Instructions with Attributed Grounding

Reference 49

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source=arxiv_source observed=2026-08-01T08:29:26.548534Z digest=sha256:c41a0f96e78e823c11f4e967aa6e8ad1164ce3582d0198e6fb00aeb8fc44f2e8

Observation b75240b9-135d-4616-b91a-6ea97b98dd9e · outbound

This paper cites LongWriter: Unleashing 10,000+ Word Generation from Long Context LLMs.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs LongWriter: Unleashing 10,000+ Word Generation from Long Context LLMs

Reference 50

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source=arxiv_source observed=2026-08-01T08:29:26.621629Z digest=sha256:8072fb712beb69eb9ccfee0795a68387ff8bf46d2824672054dac1cb4e9d46cb

Observation bc510ba5-6af0-4849-a58c-eb4c82a52661 · outbound

This paper cites Self-Alignment with Instruction Backtranslation.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Self-Alignment with Instruction Backtranslation

Reference 51

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source=arxiv_source observed=2026-08-01T08:29:26.695939Z digest=sha256:9eaef6f6547ec473ff5ef5665d333118078cdee5f98ddc0e654708668585ed2c

Observation 952fae32-79f9-482f-92fe-af7c96805414 · outbound

This paper cites Condor: Enhance LLM Alignment with Knowledge-Driven Data Synthesis and Refinement.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Condor: Enhance LLM Alignment with Knowledge-Driven Data Synthesis and Refinement

Reference 52

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source=arxiv_source observed=2026-08-01T08:29:26.740357Z digest=sha256:e1b121f883db2e3e5785009e5169c7d1f9411ed3468a2d8c05cbda2edac6b730

Observation 719b0ce5-ab37-48fb-a935-0b4a4539c1ce · outbound

This paper cites Qwen3 Technical Report.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Qwen3 Technical Report

Reference 53

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source=arxiv_source observed=2026-08-01T08:29:26.789704Z digest=sha256:b19b3bdd2e239994a34b31197e8a9c118094e4b9e5003be974644e43064f2b85

Observation 6963adc0-52a6-43e4-ba91-b2c32c3756b8 · outbound

This paper cites an unresolved cited work.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Unresolved cited work

Reference 54

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source=arxiv_source observed=2026-08-01T08:29:26.860299Z digest=sha256:ab281249bcef90a0402ea081118fee47e65b8143aecd5b263beabf220883579f

Observation ca103a53-c300-4580-bab9-2693a2ade065 · outbound

This paper cites EQ-Bench: An Emotional Intelligence Benchmark for Large Language Models.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs EQ-Bench: An Emotional Intelligence Benchmark for Large Language Models

Reference 55

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source=arxiv_source observed=2026-08-01T08:29:26.917215Z digest=sha256:bd9339f56fcc592da12bbe378f997840aa3a8c0993063cd9d5d8db761b16c323

Observation 81c67c5f-9ca9-4d54-b2a7-8e08c397207b · outbound

This paper cites Measuring Massive Multitask Language Understanding.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Measuring Massive Multitask Language Understanding

Reference 56

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source=arxiv_source observed=2026-08-01T08:29:27.001209Z digest=sha256:b47884840723c0d966b9be1be98d924523cc668b8a767f716a33a790a75a663d

Observation 0761420b-b4fc-4e89-8e00-ceb619d0c0e6 · outbound

This paper cites A Corpus and Evaluation Framework for Deeper Understanding of Commonsense Stories.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs A Corpus and Evaluation Framework for Deeper Understanding of Commonsense Stories

Reference 57

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source=arxiv_source observed=2026-08-01T08:29:27.163932Z digest=sha256:a3664eac131bc015d526f75cb3079eec38c9978360e53204906b1de5ccbb6501

Observation 44a779d7-5e37-4a8f-a334-57bc0770d6bf · outbound

This paper cites Instruction-Following Evaluation for Large Language Models.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Instruction-Following Evaluation for Large Language Models

Reference 58

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source=arxiv_source observed=2026-08-01T08:29:27.351819Z digest=sha256:6a43069a0c62f18b0e55527e7e47b93d9121a968c703f321e8ab13eb7d894070

Observation 53db73af-42ea-4f19-afec-3501c5814bc3 · outbound

This paper cites COLLIE: Systematic Construction of Constrained Text Generation Tasks.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs COLLIE: Systematic Construction of Constrained Text Generation Tasks

Reference 59

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source=arxiv_source observed=2026-08-01T08:29:27.491383Z digest=sha256:fbc526108c73b4b9bb9a89c9df0a9bafa2888ee4b9c90023b32e506ef66a32f1

Observation 0be605e0-b7e8-44c3-ac9d-e95567a6d0d5 · outbound

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

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Transactions of the Association for Computational Linguistics , volume=

Reference 60

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source=arxiv_source observed=2026-08-01T08:29:27.628561Z digest=sha256:2b3c0ad45d963dd5c9c8942f3b3b888ab260ef2357c917a837a5d8ca6041b443

Observation 730cc371-7520-49ab-8fef-5c3ce219e023 · outbound

This paper cites Paech , title =.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Paech , title =

Reference 61

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source=arxiv_source observed=2026-08-01T08:29:27.783957Z digest=sha256:250ebedc46469c95a02f20f049aa8fc03eb74785763766d7bfddf2ffee1f7899

Observation 4e7600aa-0c77-4842-b31e-74063b2cde31 · outbound

This paper cites arXiv preprint arXiv:2503.05244 , year=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs arXiv preprint arXiv:2503.05244 , year=

Reference 62

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source=arxiv_source observed=2026-08-01T08:29:27.914701Z digest=sha256:f627b4c0fd167b51113f3bd20c0343054c7e99e2e7b6442631dfd7c74ba7f421

Observation 4bac48c7-c7f8-41e0-a004-cacdf84ab841 · outbound

This paper cites HellaSwag: Can a Machine Really Finish Your Sentence?.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs HellaSwag: Can a Machine Really Finish Your Sentence?

Reference 63

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source=arxiv_source observed=2026-08-01T08:29:28.067327Z digest=sha256:83e3764094d0b159e88a8e04f16636716abef9034882c4b72596522b276b0cc7

Observation f2090e34-a101-4ac7-a4f2-7efbd9179fd9 · outbound

This paper cites SCROLLS: Standardized CompaRison Over Long Language Sequences.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs SCROLLS: Standardized CompaRison Over Long Language Sequences

Reference 64

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source=arxiv_source observed=2026-08-01T08:29:28.180885Z digest=sha256:282af81a5f99383eb0f3bd977c95ea27ffe155968e59d28d461a79960a36b5de

Observation 6384d0e6-56ab-4c93-80ba-f2bdb4d88df8 · outbound

This paper cites SocialIQA: Commonsense Reasoning about Social Interactions.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs SocialIQA: Commonsense Reasoning about Social Interactions

Reference 65

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source=arxiv_source observed=2026-08-01T08:29:28.316294Z digest=sha256:a7c48880b16588fa5620c3ed24d56de7594ebc4706e41e793a7e5d07cc230e3c

Observation fc95790e-f7d9-4e0d-9e5c-169a9cf7e6ee · outbound

This paper cites Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization

Reference 66

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source=arxiv_source observed=2026-08-01T08:29:28.516455Z digest=sha256:5fce7cfd53f33054167d362302caf4086c9e8ae55502cbe5c42e1f11ee45844f

Observation d3a680ec-9131-4f06-a6db-f72d6e4beca6 · outbound

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

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Transactions of the Association for Computational Linguistics , volume=

Reference 67

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source=arxiv_source observed=2026-08-01T08:29:28.678993Z digest=sha256:da019041ec44d60f2ba4c4a9f8d7653c3ce1bac4966447b1dedc115470ae779f

Observation d91f4ac1-41c4-40cc-9663-ba1306916aa7 · outbound

This paper cites RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models

Reference 68

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source=arxiv_source observed=2026-08-01T08:29:28.888679Z digest=sha256:605a47edc5b6a0272b6a31c5a7ea167ba5742a159569f4027648525b1f92e8a2

Observation 1d3a5ffb-3472-4559-8c2a-53f637b92169 · outbound

This paper cites ToMBench: Benchmarking Theory of Mind in Large Language Models.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs ToMBench: Benchmarking Theory of Mind in Large Language Models

Reference 69

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source=arxiv_source observed=2026-08-01T08:29:29.096107Z digest=sha256:dcdf7116adc7915ed70ccd80199edfa09b49e47c25aa0ac384641a21eb423ad7

Observation 3affc1ce-7f17-4a37-a3a5-5e3f7910d61f · outbound

This paper cites TinyStories: How Small Can Language Models Be and Still Speak Coherent English?.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs TinyStories: How Small Can Language Models Be and Still Speak Coherent English?

Reference 70

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source=arxiv_source observed=2026-08-01T08:29:29.239104Z digest=sha256:391e64384a83863f0f6550ae9cb48c736c2cbb4a5aa65fcf78ffff3b7de352d0

Observation 792be82f-6ff5-44b5-bac7-a35135352564 · outbound

This paper cites Qwen2 Technical Report.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Qwen2 Technical Report

Reference 71

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source=arxiv_source observed=2026-08-01T08:29:29.411455Z digest=sha256:020f8552d6278c9223bd7dad38327b285ed4433710595cb143b2881666329bcb

Observation 2df35343-8023-4db6-949f-b1d2684842c9 · outbound

This paper cites Qwen2.5-Coder Technical Report.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Qwen2.5-Coder Technical Report

Reference 72

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source=arxiv_source observed=2026-08-01T08:29:29.606833Z digest=sha256:dc5f033dceba92b5b93268434c84acac177629dd4a13ba840ae2760fb15e0cd1

Observation bb422173-53b2-4df1-8dc9-7830e374a48b · outbound

This paper cites Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement

Reference 73

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source=arxiv_source observed=2026-08-01T08:29:29.780668Z digest=sha256:7f8d5fda0ef5366386bf7490fbf9be10e2a9fbdf0a79402db8cddb9d68cf1e23

Observation 3c9b140f-03f6-4bdc-a5c5-7b1cadc9e332 · outbound

This paper cites Textbooks Are All You Need.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Textbooks Are All You Need

Reference 74

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source=arxiv_source observed=2026-08-01T08:29:30.001250Z digest=sha256:658225f5d83702c058fe2a68866ab3f64a20ed1c897561d393e6d68a5dc26ee1

Observation 28751814-ad7f-45d2-8cfd-73d116758bb0 · outbound

This paper cites Textbooks Are All You Need II: phi-1.5 technical report.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Textbooks Are All You Need II: phi-1.5 technical report

Reference 75

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source=arxiv_source observed=2026-08-01T08:29:30.169366Z digest=sha256:3d4a24320c304e9e488c28dc695275b719c3f45d294dd4c6c77b1ba5492458ca

Observation 5cfb2f9e-fabb-46fa-9b2d-47eb743a9b69 · outbound

This paper cites The Claude 3 Model Family: Opus, Sonnet, Haiku , url =.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs The Claude 3 Model Family: Opus, Sonnet, Haiku , url =

Reference 76

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source=arxiv_source observed=2026-08-01T08:29:30.399829Z digest=sha256:7e8b2055d93dca48f6a97d6895b250c5558cae393db96c0788dcfbc2bd9764f3

Observation 6b42b1b5-4b1c-4f95-a6f3-0192248a144b · outbound

This paper cites an unresolved cited work.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Unresolved cited work

Reference 77

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source=arxiv_source observed=2026-08-01T08:29:30.656370Z digest=sha256:76d74417cbbc224d52a788c94b40c9d8b009d6c7f3884cdc8690d09c0b79c9fc

Observation 6ff5f60d-185b-4839-8dbf-c8c2fe89e65a · outbound

This paper cites an unresolved cited work.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Unresolved cited work

Reference 78

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source=arxiv_source observed=2026-08-01T08:29:30.814668Z digest=sha256:66a80e1f6f86c3442309dc7668fa0eb3dc6d9ebab82889d331bd498b9d02a18c

Observation 320bf15e-5bda-48d0-bc7e-19595f0c5c10 · outbound

This paper cites Gonzalez and Ion Stoica , booktitle=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Gonzalez and Ion Stoica , booktitle=

Reference 79

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source=arxiv_source observed=2026-08-01T08:29:31.007022Z digest=sha256:6ba71b8bb572a71b75515bee29a7b3d653613d6fe002ba74cefa66a181b665f8

Observation da14ce4b-6911-4e95-a4ef-d27db5e6b551 · outbound

This paper cites The Llama 3 Herd of Models.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs The Llama 3 Herd of Models

Reference 81

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source=arxiv_source observed=2026-08-01T08:29:31.338370Z digest=sha256:4c1000134b2ca46a4bfbafd3e38dc984d9dfbf67d7a98992cc45282bbf2cd329

Observation 6bdb1820-9176-47ad-bdd2-2bba4eb00469 · outbound

This paper cites GPT-4 Technical Report.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs GPT-4 Technical Report

Reference 82

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source=arxiv_source observed=2026-08-01T08:29:31.398809Z digest=sha256:0aa41fcfe9d5ee301ecddcc881fbc1e0c269dc1c631f18124fe0656656680ecc

Observation b665910e-85c3-423c-be2a-cc331420d759 · outbound

This paper cites L lama F actory: Unified Efficient Fine-Tuning of 100+ Language Models.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs L lama F actory: Unified Efficient Fine-Tuning of 100+ Language Models

Reference 83

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source=arxiv_source observed=2026-08-01T08:29:31.494849Z digest=sha256:9cd27fb49582293815367035de008435a07bc0cb3913e75875ac996baf948986

Observation b797c275-f594-4faa-b739-38317ed89e09 · outbound

This paper cites Advances in neural information processing systems , volume=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Advances in neural information processing systems , volume=

Reference 84

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source=arxiv_source observed=2026-08-01T08:29:31.667898Z digest=sha256:642b9ff0811f02317667943c1af19b0e887783b919c8f044333fc451fc848dda

Observation 99afb858-a7f1-46dc-8076-30639a2ff214 · outbound

This paper cites Hashimoto , title =.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Hashimoto , title =

Reference 85

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source=arxiv_source observed=2026-08-01T08:29:31.759589Z digest=sha256:0f8895ca0410ab68d9938b41de29a80509eed3dfa8d23331e2626ec6fb4209ef

Observation 4327c0d9-0f27-4a62-8175-eec209580725 · outbound

This paper cites Enhancing Chat Language Models by Scaling High-quality Instructional Conversations.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Enhancing Chat Language Models by Scaling High-quality Instructional Conversations

Reference 86

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source=arxiv_source observed=2026-08-01T08:29:31.925399Z digest=sha256:4e38e545a5f20cd5f7195feaf085c5a54528c7f1a6be09943bf9c98c2118d72a

Observation 78c67acc-fcea-4421-b9cd-fd8d995df930 · outbound

This paper cites 2024 , eprint=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs 2024 , eprint=

Reference 87

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source=arxiv_source observed=2026-08-01T08:29:32.086304Z digest=sha256:84a84fd8700907464276a9bdedf2a3139f0970cd87698a754acc550777000ee9

Observation 30258145-b5c2-429f-a923-dc8a3ea5bc44 · outbound

This paper cites Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models

Reference 88

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source=arxiv_source observed=2026-08-01T08:29:32.254286Z digest=sha256:0f401f89382f23ce5f74518b4557a9df4fe2c0bc7403865be09c094f2c927dad

Observation cad8bbff-a75b-4e52-92e5-f67c90e0a367 · outbound

This paper cites Applied Sciences , volume=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Applied Sciences , volume=

Reference 89

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source=arxiv_source observed=2026-08-01T08:29:32.420180Z digest=sha256:933c77df13971d39afbd54c40f40e6cbd4f7027157b5c4214dcfb3b00fc6b3e8

Observation ba095836-95d4-4854-8d6c-be73cf0ab1e9 · outbound

This paper cites The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track , year=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track , year=

Reference 90

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source=arxiv_source observed=2026-08-01T08:29:32.631371Z digest=sha256:bfcfa2a9c1bdf74cb5450a83c581a7c22107ef5ae956ec25ed90789a9422ae05

Observation cdd8abc0-6158-4689-b76d-fd355cc234f2 · outbound

This paper cites 2018 , eprint=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs 2018 , eprint=

Reference 91

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source=arxiv_source observed=2026-08-01T08:29:32.767863Z digest=sha256:47f752e758d68b6a41721c8a91e440b462e0513c87f87f2b22a77db6fd9c9079

Observation d5f0aa5a-9f57-43a9-bdda-3251d39aad8d · outbound

This paper cites WinoGrande: An Adversarial Winograd Schema Challenge at Scale.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs WinoGrande: An Adversarial Winograd Schema Challenge at Scale

Reference 92

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source=arxiv_source observed=2026-08-01T08:29:32.826158Z digest=sha256:25aa3755cc770f409705a575a82b3a23d87ebba82db7d4ccab31ea90db90c56d

Observation 7bbf38e6-35b8-4610-88f4-bd57efb6fc57 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Training Verifiers to Solve Math Word Problems

Reference 93

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source=arxiv_source observed=2026-08-01T08:29:32.904555Z digest=sha256:cf26fff24267cf02c83de5a9a9952c9e81f1d3b7a25c103d64ba8e4c6205c51d

Observation 8891634a-3d04-420c-9fcb-e98b3db172f5 · outbound

This paper cites NeurIPS , year=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs NeurIPS , year=

Reference 94

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source=arxiv_source observed=2026-08-01T08:29:32.961614Z digest=sha256:c4aed403ab6216ec171ea60263d21e79a4e4c73f1d43826db776020714ef8dfd

Observation 9dddbdef-ca97-4d99-923b-9409f999a8d3 · outbound

This paper cites OpenAI , year=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs OpenAI , year=

Reference 95

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source=arxiv_source observed=2026-08-01T08:29:33.031847Z digest=sha256:83f9d91b145d8bb80dbe4f385366f215a072fd4873cf4117c60cb91a65bfe448

Observation d7675505-dc24-41de-aaf0-372c3cd0b35b · outbound

This paper cites 2021 , eprint=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs 2021 , eprint=

Reference 96

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source=arxiv_source observed=2026-08-01T08:29:33.109309Z digest=sha256:0b06d5e0a6856c807304295afa7088fa8c1923f39143cb814b8be1e20e783b84

Observation ee266cfe-758f-48ef-bd73-8a1648d77ef4 · outbound

This paper cites Learning from Task Descriptions.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Learning from Task Descriptions

Reference 97

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source=arxiv_source observed=2026-08-01T08:29:33.168238Z digest=sha256:5582cf66c8d31c10f41d55ecef79f868c3c354b44410741859b4df6df2b0a601

Observation ea44b24b-2726-41ee-9d9b-babbd3a7cd97 · outbound

This paper cites Multitask Prompted Training Enables Zero-Shot Task Generalization.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Multitask Prompted Training Enables Zero-Shot Task Generalization

Reference 98

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source=arxiv_source observed=2026-08-01T08:29:33.268430Z digest=sha256:56640fcd56eaa8f16168f6bf65edf69d8dd7e77a0171019feacec69e229e1bcc

Observation 44301e9d-2f24-4ba9-a17f-22b1a0c6f7d3 · outbound

This paper cites Cross-Task Generalization via Natural Language Crowdsourcing Instructions.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Cross-Task Generalization via Natural Language Crowdsourcing Instructions

Reference 99

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source=arxiv_source observed=2026-08-01T08:29:33.347662Z digest=sha256:6fe9b4583b34796de703b891ddde18c622e0ef7db0eabba68bbd3604deccedfd

Observation decb92ba-5137-4a82-925b-690a0555234a · outbound

This paper cites International Conference on Learning Representations , year=.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs International Conference on Learning Representations , year=

Reference 100

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source=arxiv_source observed=2026-08-01T08:29:33.428803Z digest=sha256:196123c421513cb93c6c1f674fb60641bffaaf581251eedc81b81ca370117da8

Observation fe881b27-cb9e-4c3c-a328-4ebcec8bbdfa · outbound

This paper cites FollowBench:.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs FollowBench:

Reference 101

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source=arxiv_source observed=2026-08-01T08:29:33.483389Z digest=sha256:5b86c1e3ff5b42f85be2a7e1a4f6c2c237dd1fa8510e95a4afa8104569e2a2dd

Pith citing papers

No inbound Pith citation observations are available.