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Paper Citation Record · LEDGER

Small Language Models: Survey, Measurements, and Insights

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 44 inbound Pith citation observations for arXiv:2409.15790.

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

pith.paper-citation-record.v1
2409.15790 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 44 of 44 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:01:33.874062Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T18:40:02.350725Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation f48af0ed-c7f3-4af7-ae84-f6e396f7a7eb · inbound

Do Large Language Models Advocate for Inferentialism? cites this paper.

Do Large Language Models Advocate for Inferentialism? Small Language Models: Survey, Measurements, and Insights

Reference 2019

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source=pdf_text observed=2026-08-11T12:14:34.724721Z digest=sha256:c647b4baa1146fee23b172731a1facfa4e082d8abaf2e1f46a5a41117436060b

Observation 3af79c5f-bf01-46df-9239-586d2db8efeb · inbound

AutoDroid-V2: Boosting SLM-based GUI Agents via Code Generation cites this paper.

AutoDroid-V2: Boosting SLM-based GUI Agents via Code Generation Small Language Models: Survey, Measurements, and Insights

Reference 25

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source=pdf_text observed=2026-08-11T05:06:49.308451Z digest=sha256:2382a2153c21a8dfd391c51669e6dc767b6ea5a027126114cc83ccf5909e3e16

Observation e6924393-6383-447f-a56f-4ab80bc97402 · inbound

Xmodel-2 Technical Report cites this paper.

Xmodel-2 Technical Report Small Language Models: Survey, Measurements, and Insights

Reference 11

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source=pdf_text observed=2026-08-11T00:11:19.523776Z digest=sha256:0b281c145b9d600d531788382788ad7edfd32676a2f8c46eba0270d16b1c170e

Observation 54862d05-d617-4258-b2e3-fcd356f940e6 · inbound

Language and Planning in Robotic Navigation: A Multilingual Evaluation of State-of-the-Art Models cites this paper.

Language and Planning in Robotic Navigation: A Multilingual Evaluation of State-of-the-Art Models Small Language Models: Survey, Measurements, and Insights

Reference 15

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source=arxiv_source observed=2026-08-10T21:47:58.983044Z digest=sha256:eaa82de47d4abdcf125bf85543b686f0a16a234cefbc30ed04949fbeb49e2496

Observation 89572614-f4c1-4db0-86e6-4783b6ba3a7a · inbound

OnionEval: An Unified Evaluation of Fact-conflicting Hallucination for Small-Large Language Models cites this paper.

OnionEval: An Unified Evaluation of Fact-conflicting Hallucination for Small-Large Language Models Small Language Models: Survey, Measurements, and Insights

Reference 11

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source=pdf_text observed=2026-08-10T16:40:09.368585Z digest=sha256:21ae25481a15d33fe53a132c06352c72ba3bf63b6e1f93a09c7e86537054af14

Observation dab7fc7a-8f53-4e60-b373-ee6db8ba20ed · inbound

Evaluating Small Language Models for News Summarization: Implications and Factors Influencing Performance cites this paper.

Evaluating Small Language Models for News Summarization: Implications and Factors Influencing Performance Small Language Models: Survey, Measurements, and Insights

Reference 35

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source=arxiv_source observed=2026-08-09T18:17:21.102623Z digest=sha256:228ed1786c7f87994a8334406993f801fa7c4bdff526e6adbdc2f5fad8102d3b

Observation cfcda5f3-4cfd-436c-aebc-ae509d71dbea · inbound

Division-of-Thoughts: Harnessing Hybrid Language Model Synergy for Efficient On-Device Agents cites this paper.

Division-of-Thoughts: Harnessing Hybrid Language Model Synergy for Efficient On-Device Agents Small Language Models: Survey, Measurements, and Insights

Reference 27

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source=pdf_text observed=2026-08-09T01:02:19.341794Z digest=sha256:0ddabb4f7659a68abcaee8e932eeb32d75f9922a551bbabb758db2ec7fc3313c

Observation 0c30b20a-164c-4071-8b26-38506567e574 · inbound

Every Software as an Agent: Blueprint and Case Study cites this paper.

Every Software as an Agent: Blueprint and Case Study Small Language Models: Survey, Measurements, and Insights

Reference 13

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no resolver link, observed 2026-08-08T21:41:15.792493Z

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source=pdf_text observed=2026-08-08T21:41:15.792493Z digest=sha256:cc022d5fe6bf4e4f0f8bc149bee7e20b1f4f886ce62e6fb8a7d93312a9f37649

Observation 56aa619b-4f94-4e3d-8582-05cd8a2843bb · inbound

Will LLMs Scaling Hit the Wall? Breaking Barriers via Distributed Resources on Massive Edge Devices cites this paper.

Will LLMs Scaling Hit the Wall? Breaking Barriers via Distributed Resources on Massive Edge Devices Small Language Models: Survey, Measurements, and Insights

Reference 57

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arxiv_id, observed 2026-05-23T01:05:16.508630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-23T01:03:26.037233Z digest=sha256:34965543867b8c18406ae7a7857fbe1c9b78b29cb518c1c08d1c5fbf53ef461e

Observation 2662bc64-8916-49f0-b10b-dcf588fa1635 · inbound

RobotxR1: Enabling Embodied Robotic Intelligence on Large Language Models through Closed-Loop Reinforcement Learning cites this paper.

RobotxR1: Enabling Embodied Robotic Intelligence on Large Language Models through Closed-Loop Reinforcement Learning Small Language Models: Survey, Measurements, and Insights

Reference 27

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no resolver link, observed 2026-08-16T00:01:33.874062Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:01:33.874062Z digest=sha256:af814dff43984463276ab857fa1357803ad904a0aeb1a3a1c98175d3cb108ffb

Observation 13d96d9f-c7d1-4a6e-800b-a7b9cfb40c8c · inbound

Challenging GPU Dominance: When CPUs Outperform for On-Device LLM Inference cites this paper.

Challenging GPU Dominance: When CPUs Outperform for On-Device LLM Inference Small Language Models: Survey, Measurements, and Insights

Reference 20

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source=pdf_text observed=2026-08-15T22:44:35.231552Z digest=sha256:7a5799b7f80bdd82d36b7c26c993b08ade7be6c5b3d621d9526995861645b1c6

Observation dec85007-785b-45b8-804b-2b61ce4ec308 · inbound

Edge-First Language Model Inference: Models, Metrics, and Tradeoffs cites this paper.

Edge-First Language Model Inference: Models, Metrics, and Tradeoffs Small Language Models: Survey, Measurements, and Insights

Reference 15

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no resolver link, observed 2026-08-07T15:03:09.638551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:03:09.638551Z digest=sha256:1ba1d088ec27db39c1752055093082b6f841b55855e6d4f5bf484bfcee7ff6de

Observation d691ac56-8acc-4827-a1a6-67217070b33e · inbound

Making Sense of the Unsensible: Reflection, Survey, and Challenges for XAI in Large Language Models Toward Human-Centered AI cites this paper.

Making Sense of the Unsensible: Reflection, Survey, and Challenges for XAI in Large Language Models Toward Human-Centered AI Small Language Models: Survey, Measurements, and Insights

Reference 32

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no resolver link, observed 2026-08-15T20:36:55.293076Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-15T20:36:55.293076Z digest=sha256:622e0a41946a00651e96e4e0575022bbc647cc348415bfbdd6440ef645e1aa82

Observation 9f918744-43be-46b6-8204-d77dbadb40bb · inbound

Fast and Cost-effective Speculative Edge-Cloud Decoding with Early Exits cites this paper.

Fast and Cost-effective Speculative Edge-Cloud Decoding with Early Exits Small Language Models: Survey, Measurements, and Insights

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:40:17.090010Z digest=sha256:a6e0ac1b7947e3d7b870f3ab708a237beb92ff386e9a5a041297460cd1fbdb65

Observation 5389fa0a-b610-4eab-9374-a922df382df7 · inbound

Small Language Models are the Future of Agentic AI cites this paper.

Small Language Models are the Future of Agentic AI Small Language Models: Survey, Measurements, and Insights

Reference 49

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verified exact
arxiv_id, observed 2026-05-16T11:55:51.007130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-16T11:55:50.897500Z digest=sha256:761f00e9ba1cfce5258a540aca5ca01d167763a7762b39dbb3a9fc78aff0d343

Observation 705ffb18-8a22-4dbb-ab3e-2d78ff0716c8 · inbound

CRAWLDoc: A Dataset for Robust Ranking of Bibliographic Documents cites this paper.

CRAWLDoc: A Dataset for Robust Ranking of Bibliographic Documents Small Language Models: Survey, Measurements, and Insights

Reference 22

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no resolver link, observed 2026-08-07T10:57:27.870197Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:57:27.870197Z digest=sha256:136f1bb769164e9ea405283813950c66a2f8ff9eec4c4a49ea6339f417cf6095

Observation b66c68af-5e7d-4b6a-b49d-f98e1538b848 · inbound

Towards Efficient Multi-LLM Inference: Characterization and Analysis of LLM Routing and Hierarchical Techniques cites this paper.

Towards Efficient Multi-LLM Inference: Characterization and Analysis of LLM Routing and Hierarchical Techniques Small Language Models: Survey, Measurements, and Insights

Reference 59

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no resolver link, observed 2026-08-07T05:56:56.904953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:56:56.904953Z digest=sha256:1e61795364de00c8f775ed256231e10695cbbec34e580bf703cb804c63d440d3

Observation d3064679-5809-4fd9-82ec-ea219a2655bc · inbound

Plug-in and Fine-tuning: Bridging the Gap between Small Language Models and Large Language Models cites this paper.

Plug-in and Fine-tuning: Bridging the Gap between Small Language Models and Large Language Models Small Language Models: Survey, Measurements, and Insights

Reference 41

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source=arxiv_source observed=2026-08-07T05:40:24.461026Z digest=sha256:c788685256a73253edda74cb5b1c77b3859fd08e39f3e71c197ca2b23feddb36

Observation b697e34a-3625-4ea3-8b48-5adb76c24978 · inbound

TensorSLM: Energy-efficient Embedding Compression of Sub-billion Parameter Language Models on Low-end Devices cites this paper.

TensorSLM: Energy-efficient Embedding Compression of Sub-billion Parameter Language Models on Low-end Devices Small Language Models: Survey, Measurements, and Insights

Reference 27

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no resolver link, observed 2026-08-15T20:05:48.951738Z

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Observation dc2944b2-4f7c-498c-a016-15eb33dfcb2f · inbound

MobiEdit: Resource-efficient Knowledge Editing for Personalized On-device LLMs cites this paper.

MobiEdit: Resource-efficient Knowledge Editing for Personalized On-device LLMs Small Language Models: Survey, Measurements, and Insights

Reference 12

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:44:03.856408Z digest=sha256:03c9ed977589a1708166e50691feca8117c208c8ea8610f040654585b4a11d98

Observation 78df61d9-714a-43f4-b9da-f300032c2220 · inbound

S$^2$GPT-PINNs: Sparse and Small models for PDEs cites this paper.

S$^2$GPT-PINNs: Sparse and Small models for PDEs Small Language Models: Survey, Measurements, and Insights

Reference 26

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no resolver link, observed 2026-08-07T14:23:51.551308Z

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Observation 3e197c3c-4115-49ba-8867-0bb0abd59eab · inbound

Hallucination Detection with Small Language Models cites this paper.

Hallucination Detection with Small Language Models Small Language Models: Survey, Measurements, and Insights

Reference 6

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no resolver link, observed 2026-08-06T23:11:41.309503Z

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source=pdf_text observed=2026-08-06T23:11:41.309503Z digest=sha256:c06cac8ae1e4b3af1e9de76c2a93723c21e3933607806e35f2c8761debc80080

Observation 6d109e09-81e8-4223-a3f5-998bde44b3e6 · inbound

Investigating the Performance of Small Language Models in Detecting Test Smells in Manual Test Cases cites this paper.

Investigating the Performance of Small Language Models in Detecting Test Smells in Manual Test Cases Small Language Models: Survey, Measurements, and Insights

Reference 14

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no resolver link, observed 2026-08-06T16:37:41.109375Z

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source=pdf_text observed=2026-08-06T16:37:41.109375Z digest=sha256:4c51fbe6c3f9de2d8bf8dec3ae43ed9df8293e2adbb0befb9c28523d5c5245ab

Observation 73bc4bb5-8dc1-4625-8a96-fa81082683de · inbound

Do small language models generate realistic variable-quality fake news headlines? cites this paper.

Do small language models generate realistic variable-quality fake news headlines? Small Language Models: Survey, Measurements, and Insights

Reference 1

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source=pdf_text observed=2026-08-05T13:24:39.578589Z digest=sha256:c49b06ed3aef9252f8375592966b843fca5f0d2720c4f4103a91e6441bcc5b62

Observation acdecbb0-7f67-498e-96ff-6bdf79cb8cb7 · inbound

Advancing SLM Tool-Use Capability using Reinforcement Learning cites this paper.

Advancing SLM Tool-Use Capability using Reinforcement Learning Small Language Models: Survey, Measurements, and Insights

Reference 2

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no resolver link, observed 2026-08-05T11:10:01.164458Z

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source=pdf_text observed=2026-08-05T11:10:01.164458Z digest=sha256:7b08da11a3060ffedb2bd72d3da303abc8f8583174512b435b7fba6c02aaceb1

Observation 45a70466-d481-4df4-925e-564217aede9c · inbound

Sustainable Code Generation Using Large Language Models: A Systematic Literature Review cites this paper.

Sustainable Code Generation Using Large Language Models: A Systematic Literature Review Small Language Models: Survey, Measurements, and Insights

Reference 32

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arxiv_id, observed 2026-05-15T18:50:16.453907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 87f698f7-a104-409c-adbc-510bd6a299d3 · inbound

EdgeCIM: A Hardware-Software Co-Design for CIM-Based Acceleration of Small Language Models cites this paper.

EdgeCIM: A Hardware-Software Co-Design for CIM-Based Acceleration of Small Language Models Small Language Models: Survey, Measurements, and Insights

Reference 16

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arxiv_id, observed 2026-05-10T15:05:33.071698Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-10T15:04:49.793158Z digest=sha256:8bea1b0e6fa58487e931c4178197e93552ebeda03abca2f9cddcf43399f9abb7

Observation fda3e460-b468-4d0a-b8f4-abe6a7ab3b69 · inbound

Local-Splitter: A Measurement Study of Seven Tactics for Reducing Cloud LLM Token Usage on Coding-Agent Workloads cites this paper.

Local-Splitter: A Measurement Study of Seven Tactics for Reducing Cloud LLM Token Usage on Coding-Agent Workloads Small Language Models: Survey, Measurements, and Insights

Reference 16

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arxiv_id, observed 2026-05-11T10:26:01.780655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 02ef8966-523e-47fb-ba95-ca334820b464 · inbound

Taming Asynchronous CPU-GPU Coupling for Frequency-aware Latency Estimation on Mobile Edge cites this paper.

Taming Asynchronous CPU-GPU Coupling for Frequency-aware Latency Estimation on Mobile Edge Small Language Models: Survey, Measurements, and Insights

Reference 13

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arxiv_id, observed 2026-05-11T09:50:59.002513Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 9b73a2a8-e493-4dd0-bcfa-f5527cedf91c · inbound

Domain-Adapted Small Language Models for Reliable Clinical Triage cites this paper.

Domain-Adapted Small Language Models for Reliable Clinical Triage Small Language Models: Survey, Measurements, and Insights

Reference 18

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arxiv_id, observed 2026-05-12T08:56:26.514931Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-07T13:26:56.896673Z digest=sha256:4a46efcc2d416aff94c04c508b358ad9f29ea9e3544ef460a83a7432c3fb14e4

Observation 47c7e277-36e0-490f-a4c7-45b153be84b6 · inbound

AgentFloor: How Far Up the tool use Ladder Can Small Open-Weight Models Go? cites this paper.

AgentFloor: How Far Up the tool use Ladder Can Small Open-Weight Models Go? Small Language Models: Survey, Measurements, and Insights

Reference 26

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arxiv_id, observed 2026-05-11T15:21:10.368431Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-09T20:09:11.566825Z digest=sha256:394f4ff4c0cdbdb98a17e07fdb0f2de62521c5ed7f5f9a6102963c10d31e33fa

Observation 658c89f0-e6a8-409a-99d0-49ae94df182f · inbound

Benchmarking EngGPT2-16B-A3B against Comparable Italian and International Open-source LLMs cites this paper.

Benchmarking EngGPT2-16B-A3B against Comparable Italian and International Open-source LLMs Small Language Models: Survey, Measurements, and Insights

Reference 8

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arxiv_id, observed 2026-05-11T03:40:53.508032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-11T03:40:04.692279Z digest=sha256:e52fe300dbc1f7e37811718143282c5188f9cd476e0d58aaac770d0fc5290cfa

Observation c54f183d-862a-4f1a-bee3-f02f023c0e3b · inbound

Benchmarking EngGPT2-16B-A3B against Comparable Italian and International Open-source LLMs cites this paper.

Benchmarking EngGPT2-16B-A3B against Comparable Italian and International Open-source LLMs Small Language Models: Survey, Measurements, and Insights

Reference 8

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arxiv_id, observed 2026-05-21T08:19:52.872480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-21T08:14:55.858466Z digest=sha256:04be56afd96f782f19a766f4cde01da73413f6d5f216fbb375f09f1c0603d0e3

Observation b83862b5-b73f-4d2d-96f6-9d15abc37598 · inbound

Agents Should Replace Narrow Predictive AI as the Orchestrator in 6G AI-RAN cites this paper.

Agents Should Replace Narrow Predictive AI as the Orchestrator in 6G AI-RAN Small Language Models: Survey, Measurements, and Insights

Reference 29

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arxiv_id, observed 2026-05-13T02:17:07.004038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-13T02:12:21.409833Z digest=sha256:0c594067daa894bb63ee2651bdfd9cfb30d75afe2487488077cfeb2fb2ba2346

Observation 83004316-a34f-4694-b109-7ca78d75a894 · inbound

Does Mixture-of-Experts Actually Help Inference on Consumer and Edge Hardware? An Empirical Study cites this paper.

Does Mixture-of-Experts Actually Help Inference on Consumer and Edge Hardware? An Empirical Study Small Language Models: Survey, Measurements, and Insights

Reference 19

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arxiv_id, observed 2026-07-04T07:59:39.591156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 1da610fc-b1b1-4d2c-b779-ce2f18ee0754 · inbound

Does Mixture-of-Experts Actually Help Inference on Consumer and Edge Hardware? An Empirical Study cites this paper.

Does Mixture-of-Experts Actually Help Inference on Consumer and Edge Hardware? An Empirical Study Small Language Models: Survey, Measurements, and Insights

Reference 19

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unresolved
no resolver link, observed 2026-07-12T13:05:17.273287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 9e72f6c5-a0f7-418f-850c-ecc54521326a · inbound

To Isolate or to Score? Model-Adaptive Assessment for Cost-Efficient Multi-Agent RAG cites this paper.

To Isolate or to Score? Model-Adaptive Assessment for Cost-Efficient Multi-Agent RAG Small Language Models: Survey, Measurements, and Insights

Reference 53

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metadata mismatch
arxiv_id, observed 2026-07-04T18:40:02.352411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-06-25T22:44:43.951083Z digest=sha256:68410ed17aff351df3944bf01b78735805c4b867019f5a0f75b61335bf70fac1

Observation 974da967-5f5a-47eb-81e7-bccb6c88127e · inbound

Punching Above Their Weight: Classification-Head Fine-Tuning of Tiny Language Models (TLMs) for Verifiable Multiple-Choice Tasks cites this paper.

Punching Above Their Weight: Classification-Head Fine-Tuning of Tiny Language Models (TLMs) for Verifiable Multiple-Choice Tasks Small Language Models: Survey, Measurements, and Insights

Reference 10

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unresolved
no resolver link, observed 2026-07-11T23:52:16.201593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T23:52:16.201593Z digest=sha256:e5e8f857d32a193891253fe8b336e29c337af5d6a477d130fd4ee888bf31fbee

Observation 7bfb93da-6835-4217-a44f-03a30c983111 · inbound

Enhancing Small Language Models Reasoning through Knowledge Graph Grounding cites this paper.

Enhancing Small Language Models Reasoning through Knowledge Graph Grounding Small Language Models: Survey, Measurements, and Insights

Reference 8

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unresolved
no resolver link, observed 2026-08-02T06:22:35.840774Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T06:22:35.840774Z digest=sha256:6557650065d479fb28d29afa5f563f3ecaab44a06d29f8b4dd3501bc54697870

Observation 42f185e0-b07d-4a5f-a85a-8854712ac95b · inbound

In-Context Learning for Wound Classification with Small Multimodal Language Models cites this paper.

In-Context Learning for Wound Classification with Small Multimodal Language Models Small Language Models: Survey, Measurements, and Insights

Reference 44

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unresolved
no resolver link, observed 2026-08-01T14:16:00.802642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:16:00.802642Z digest=sha256:7896671d5d53a6cdf0e6571624732107ce35a2f5ab8258377999985331ba9f43

Observation 9f6a35a9-88ca-4602-bad2-d5b2842dac0b · inbound

Small, Free, and Effective: Orchestrating Open-Weight Small Language Models to Outperform Single LLM for Malware Analysis cites this paper.

Small, Free, and Effective: Orchestrating Open-Weight Small Language Models to Outperform Single LLM for Malware Analysis Small Language Models: Survey, Measurements, and Insights

Reference 35

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unresolved
no resolver link, observed 2026-08-01T10:30:43.932970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T10:30:43.932970Z digest=sha256:6290bff23999cff4d07d3709d5b41e3625ccb8c49807961edab18b920d6130c8

Observation b5254233-1282-4341-a464-53765346790c · inbound

Offline Vision-Language Navigation with Geometric Goal Localization for Outdoor Environments cites this paper.

Offline Vision-Language Navigation with Geometric Goal Localization for Outdoor Environments Small Language Models: Survey, Measurements, and Insights

Reference 7

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unresolved
no resolver link, observed 2026-08-01T05:28:48.034749Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-01T05:28:48.034749Z digest=sha256:81282a2c084d979d0325209dcce096fa6f159e45c1eed54fe78f814b79fdf999

Observation 84d2868c-3a70-4f1b-84a7-123555dccbe3 · inbound

MIITA: Memory-Induced Inference-Time Adaptation for Continual Learning with Small Language Models cites this paper.

MIITA: Memory-Induced Inference-Time Adaptation for Continual Learning with Small Language Models Small Language Models: Survey, Measurements, and Insights

Reference 14

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unresolved
no resolver link, observed 2026-08-02T13:35:45.803513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T13:35:45.803513Z digest=sha256:48ff361744cd4308667557d68fee718cbb89535463b476fa320171a021032aa9

Observation 1c09d827-bf61-4389-8d18-4dd95f5aaee3 · inbound

Energy- and Memory-Efficient PEFT Methods for Personalized On-Device SLMs on Consumer GPUs cites this paper.

Energy- and Memory-Efficient PEFT Methods for Personalized On-Device SLMs on Consumer GPUs Small Language Models: Survey, Measurements, and Insights

Reference 11

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unresolved
no resolver link, observed 2026-08-06T23:25:08.951439Z

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source=pdf_text observed=2026-08-06T23:25:08.951439Z digest=sha256:830d8dc7d6ffcb2a2bad63930da4c8b0c6dac9fc1b207dc0165312bbef797f15