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Paper Citation Record · LEDGER

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models

As of 9 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2607.27421.

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

pith.paper-citation-record.v1
2607.27421 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-31T01:27:16.249799Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

43 of 43 outbound references displayed

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  • verified fuzzy0
  • unresolved42
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

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Outbound references

Observation f7eb01fd-dee6-41b4-abb9-a81dbbbf9713 · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 1

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Observation 609eab5d-55d2-461f-a5c5-9ea8dacbfd61 · outbound

This paper cites SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model

Reference 2

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source=pdf_text observed=2026-07-31T01:27:12.034872Z digest=sha256:696e1e1f6fa639622be59761a69d2d0a0bdc3b0fa7952b045cae53f40d53bfef

Observation 99cb935d-8a34-4d25-a508-417e659b0802 · outbound

This paper cites Stable LM 2 1.6B Technical Report.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models Stable LM 2 1.6B Technical Report

Reference 3

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source=pdf_text observed=2026-07-31T01:27:12.091976Z digest=sha256:e1092123b716beeb36a42bff97112bee9dc18aa0eb31afd1f7ddcfaefc19665f

Observation 65404c41-f649-47d8-8a89-371012085d29 · outbound

This paper cites G.; Bradley, H.; O’Brien, K.; Hallahan, E.; Khan, M.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models G.; Bradley, H.; O’Brien, K.; Hallahan, E.; Khan, M

Reference 4

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source=pdf_text observed=2026-07-31T01:27:12.141975Z digest=sha256:f4504859068d30f403f3c5ea3e4d36438c3abd5caeb75d6b05f2becc7d71194a

Observation 853831f5-1d22-4164-b2b2-8a8abf617896 · outbound

This paper cites BLOOM: A 176B-Parameter Open-Access Multilingual Language Model.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Reference 5

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source=pdf_text observed=2026-07-31T01:27:12.226075Z digest=sha256:c13f2304c5ed8ab8b9b9d74c75fa5b4c04e7655dd9e325ea0e5fccf7d509c3b2

Observation 1b13cb8c-ae2e-4794-af67-a9e096ee4f76 · outbound

This paper cites D.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; et al.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models D.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; et al

Reference 6

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Observation 4698403b-eba8-4b09-b374-62cf01f163da · outbound

This paper cites an unresolved cited work.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models Unresolved cited work

Reference 7

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source=pdf_text observed=2026-07-31T01:27:12.508958Z digest=sha256:84b7455ecb6a91d1923741b45e0faec8816d101c53cd095ab8c60a8f89e7e25a

Observation 3842a522-706e-4648-94fb-97669441f81e · outbound

This paper cites an unresolved cited work.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models Unresolved cited work

Reference 8

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source=pdf_text observed=2026-07-31T01:27:12.765058Z digest=sha256:dbbf1320acc961c604e0ca8542b92e675f4542d61309534f50cc7207cfa30377

Observation 738c553d-f1d3-40b4-9cdf-fa26cc5bce1e · outbound

This paper cites Snips Voice Platform: an embedded Spoken Language Understanding system for private-by-design voice interfaces.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models Snips Voice Platform: an embedded Spoken Language Understanding system for private-by-design voice interfaces

Reference 9

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source=pdf_text observed=2026-07-31T01:27:12.874923Z digest=sha256:2e173cd9b4779fa46f57b6f6090316b9f3f809be4f66c3c9ccddc855be3b4575

Observation 66f8f756-927b-4099-905e-949bed9dfa25 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 10

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source=pdf_text observed=2026-07-31T01:27:13.002647Z digest=sha256:2ed672dfb46ec49a0fab83ed95c88a1f0b263379f72eda4f701c55f9f88640e3

Observation 6066659e-09f6-433a-ab74-53ebec17c718 · outbound

This paper cites MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages

Reference 11

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source=pdf_text observed=2026-07-31T01:27:13.123451Z digest=sha256:283e1ae5e46c3ce2b6b7c28e540ca63e0c534d50a1247db8c880e4d777aa7a57

Observation c3819625-3e36-4254-934d-90e7c543c9dc · outbound

This paper cites The Llama 3 Herd of Models.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models The Llama 3 Herd of Models

Reference 12

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Observation 0fd724ae-f190-4f4a-bfd4-7f9be5fee48b · outbound

This paper cites an unresolved cited work.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models Unresolved cited work

Reference 13

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source=pdf_text observed=2026-07-31T01:27:13.309046Z digest=sha256:5060356bf70d73b97f157398aba1f4da49846bf6ae1fab2eb15775e315abb18e

Observation 83dea56c-8168-4043-bf5e-7334971c0ca4 · outbound

This paper cites T.; Godfrey, J.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models T.; Godfrey, J

Reference 14

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source=pdf_text observed=2026-07-31T01:27:13.566435Z digest=sha256:7c8793b1e290234a1ab58ace04cef9677710b6ec5e94b307f2e9befc0e58aece

Observation db5a7eab-adb4-4dba-96a7-ffc4d4e05f32 · outbound

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

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

Reference 15

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source=pdf_text observed=2026-07-31T01:27:13.723217Z digest=sha256:18608c16941c821f41a878411ea0c07212dc2b5a46fbc9d7ac21b24ef144ccaf

Observation 8ed01634-9767-4f98-9394-e67f66b8ad85 · outbound

This paper cites Mistral 7B.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models Mistral 7B

Reference 16

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source=pdf_text observed=2026-07-31T01:27:13.807110Z digest=sha256:674a8430803d20e3d07e275f22b2d2aaae22a61fa541b58d8ddf99573a33591f

Observation 9bdb3dff-a445-4597-b786-2b98cb210f70 · outbound

This paper cites H.; Gonzalez, J.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models H.; Gonzalez, J

Reference 17

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source=pdf_text observed=2026-07-31T01:27:13.856631Z digest=sha256:c5be16ca27e0ec7e437da5bffb56222afc2e0985780d716f73a0154932f0e662

Observation 8f2ef8ca-71b0-4000-b1c5-93e26554f2b4 · outbound

This paper cites A Survey of Intent Classification and Slot-Filling Datasets for Task-Oriented Dialog.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models A Survey of Intent Classification and Slot-Filling Datasets for Task-Oriented Dialog

Reference 18

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source=pdf_text observed=2026-07-31T01:27:14.038284Z digest=sha256:2c4f4e65e035639ed757dc830bbe23cd779d6b0c9f0e63715cbe7f3128dd3b01

Observation f678d7e5-78be-49ec-b46f-3d1a91177e52 · outbound

This paper cites J.; Clarke, C.; Lee, A.; Hill, P.; Kummerfeld, J.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models J.; Clarke, C.; Lee, A.; Hill, P.; Kummerfeld, J

Reference 19

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Observation 28aa2544-eb0e-4005-bbe4-028c93438c6c · outbound

This paper cites an unresolved cited work.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models Unresolved cited work

Reference 20

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Observation 298e32b9-5e53-42a4-b335-cded187bace6 · outbound

This paper cites an unresolved cited work.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models Unresolved cited work

Reference 21

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source=pdf_text observed=2026-07-31T01:27:14.354752Z digest=sha256:a80948f9d90b94616644e45718e708833dab8387a6662c3065b4f6485ed0b3c2

Observation 24680ef2-e027-43b0-b97c-48f9fbc88191 · outbound

This paper cites HINT3: Raising the bar for intent detection in the wild.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models HINT3: Raising the bar for intent detection in the wild

Reference 22

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Observation 0d62e54b-80ac-49ba-863f-3b93a1597db0 · outbound

This paper cites an unresolved cited work.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models Unresolved cited work

Reference 23

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Observation 4adbec8a-b82d-45e5-9975-796b4849fe8d · outbound

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Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models Unresolved cited work

Reference 24

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Observation 3f134bb1-19a7-41e7-b541-28fa532d8f95 · outbound

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Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models Unresolved cited work

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Observation f846067c-c9b7-4086-98d9-8faf59a126c7 · outbound

This paper cites an unresolved cited work.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models Unresolved cited work

Reference 26

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source=pdf_text observed=2026-07-31T01:27:14.986316Z digest=sha256:1e4161e8471e871ecb8c0d3f3d0c6f6362ba58cf48d9bd30baec13c147df19e3

Observation 6761f0ba-45a8-4887-a136-c24b195093ab · outbound

This paper cites an unresolved cited work.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models Unresolved cited work

Reference 27

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source=pdf_text observed=2026-07-31T01:27:15.234255Z digest=sha256:d316ca64fa21d7954fb918eded763422f67afb55b62749d52bfa494f9d3bbaa6

Observation 8d80c15b-7731-4163-9a6f-a53f933ce77b · outbound

This paper cites Dynamic Label Name Refinement for Few-Shot Dialogue Intent Classification.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models Dynamic Label Name Refinement for Few-Shot Dialogue Intent Classification

Reference 28

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source=pdf_text observed=2026-07-31T01:27:14.640350Z digest=sha256:4914e149c5d2b98642a5cd93273f323d6670148edd2ec5a6e28bec995784a657

Observation e577fb0e-1cf4-410f-a678-97bf08bd375d · outbound

This paper cites Qwen2 Technical Report.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models Qwen2 Technical Report

Reference 29

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source=pdf_text observed=2026-07-31T01:27:15.454389Z digest=sha256:cfb197e46754099878f4c6633050bd4e8db3eb4cd34e399614420940031e15a6

Observation 25c94043-b6b8-47b5-a0b1-09ba831eb835 · outbound

This paper cites Qwen2.5 Technical Report.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models Qwen2.5 Technical Report

Reference 30

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source=pdf_text observed=2026-07-31T01:27:15.566575Z digest=sha256:3488a838f853f85f5f126ef098c3ae7f6bfd894db5cddffba9983c5868841b4c

Observation d4c84980-d8b9-4c8d-8da3-5217b37bbcbd · outbound

This paper cites SessionIntentBench: A Multi-task Inter-session Intention-shift Modeling Benchmark for E-commerce Customer Behavior Understanding.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models SessionIntentBench: A Multi-task Inter-session Intention-shift Modeling Benchmark for E-commerce Customer Behavior Understanding

Reference 31

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Observation e5d33d2c-68e9-41a7-bd5b-65d7052bb74d · outbound

This paper cites ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools

Reference 32

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Observation bde8b37c-dd49-47d9-aeb3-ab800bc37327 · outbound

This paper cites an unresolved cited work.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models Unresolved cited work

Reference 33

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source=pdf_text observed=2026-07-31T01:27:15.833123Z digest=sha256:bcf416d85262e9d71fecc57d811173de4f717ad6e2848c2e60a562835fbd9150

Observation 29d1ea60-1ae3-4799-aa7c-58ce5b727063 · outbound

This paper cites Y.; Guu, K.; Yu, A.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models Y.; Guu, K.; Yu, A

Reference 34

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Observation 76adff53-cff3-4eb7-a893-d6fb10eaa878 · outbound

This paper cites Z.; Wallace, E.; Feng, S.; Klein, D.; and Singh, S.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models Z.; Wallace, E.; Feng, S.; Klein, D.; and Singh, S

Reference 35

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source=pdf_text observed=2026-07-31T01:27:16.132098Z digest=sha256:5a3c04da689769b3bbcfea5b8e24ca823713b0ac7bc554149299506488de12e1

Observation eaac4191-2e25-40be-bf8c-6a8ff7a041a1 · outbound

This paper cites IntentGrasp: A Comprehensive Benchmark for Intent Understanding.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models IntentGrasp: A Comprehensive Benchmark for Intent Understanding

Reference 38

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Observation 6f7680d9-0008-48c2-9f72-a14aa51e0e39 · outbound

This paper cites Yi: Open Foundation Models by 01.AI.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models Yi: Open Foundation Models by 01.AI

Reference 40

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This paper cites TinyLlama: An Open-Source Small Language Model.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models TinyLlama: An Open-Source Small Language Model

Reference 41

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This paper cites InSpeech and Natural Language: Proceedings of a Workshop.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models InSpeech and Natural Language: Proceedings of a Workshop

Reference 1990

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This paper cites In Proceedings of the 34th International Conference on Machine Learning.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models In Proceedings of the 34th International Conference on Machine Learning

Reference 2017

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Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models \n", "</s>

Reference 2021

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Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models InProceedings of the 29th Symposium on Operating Systems Principles

Reference 2023

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This paper cites InternLM2 Technical Report.

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models InternLM2 Technical Report

Reference 2024

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