Paper Citation Record · LEDGER

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction

As of 13 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2602.23312.

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

pith.paper-citation-record.v1
2602.23312 v3

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T20:26:41.236405Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

40 of 40 outbound references displayed

verified exact1
verified fuzzy0
unresolved39
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1c51ea1c-1d26-45cf-823f-839a23abe30f · outbound

This paper cites Redraw- ing boundaries: Systemic impacts of rehabilitation robots in clinical care settings,.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Redraw- ing boundaries: Systemic impacts of rehabilitation robots in clinical care settings,

Reference 1

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Source-reported events for the cited work

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Observation 5e98bafb-4b54-49a9-8074-5aa6e76914b0 · outbound

This paper cites Adebayo, J.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Adebayo, J

Reference 2

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Source-reported events for the cited work

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Observation 92d8afab-b854-4e37-a13d-6e42b01ca5df · outbound

This paper cites Exploring social robots for healthy older adults: Aging with companionship,.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Exploring social robots for healthy older adults: Aging with companionship,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T20:26:38.582150Z

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Observation ed10f2bc-adbc-4518-b12d-e493f2d79f52 · outbound

This paper cites Role spe- cialization enables superior task performance by human dyads than individuals,.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Role spe- cialization enables superior task performance by human dyads than individuals,

Reference 4

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Observation 62c25840-1707-4014-bb8b-8ce2ebda3140 · outbound

This paper cites Human leading or following preferences: Effects on human percep- tion of the robot and the human–robot collaboration,.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Human leading or following preferences: Effects on human percep- tion of the robot and the human–robot collaboration,

Reference 5

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Source-reported events for the cited work

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Observation 207a1dfc-5f99-4c7e-91cc-a4e3984189ab · outbound

This paper cites Influencing leading and following in human-robot teams.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Influencing leading and following in human-robot teams

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T20:26:38.844799Z

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Observation 63e12c95-1e14-4273-a5f6-64ceddbd06f1 · outbound

This paper cites Communication in human-robot interaction,.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Communication in human-robot interaction,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T20:26:38.913143Z

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Observation 2bce73f6-b1ad-40cd-93f2-1d59f069b5b1 · outbound

This paper cites Natural language processing in the era of large language models,.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Natural language processing in the era of large language models,

Reference 8

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Observation 8b73815a-bbf1-46d2-960a-f3d658220c2f · outbound

This paper cites FurChat: An embodied conversational agent using LLMs, combining open and closed- domain dialogue with facial expressions,.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction FurChat: An embodied conversational agent using LLMs, combining open and closed- domain dialogue with facial expressions,

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Observation d59270d3-fc72-4a4d-8082-6882d72ea042 · outbound

This paper cites Lami: Large language models for multi-modal human-robot interaction,.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Lami: Large language models for multi-modal human-robot interaction,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T20:26:39.205634Z

Source-reported events for the cited work

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Observation 4ffc4d95-d406-4d84-b34b-632f3b2d6c62 · outbound

This paper cites Enhancing human-robot collaborative assembly in manufacturing sys- tems using large language models,.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Enhancing human-robot collaborative assembly in manufacturing sys- tems using large language models,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T20:26:39.285150Z

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Observation 2546f05e-33fc-4ac1-8112-353d04cf452c · outbound

This paper cites An empirical analysis and resource footprint study of deploying large language models on edge devices,.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction An empirical analysis and resource footprint study of deploying large language models on edge devices,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T20:26:39.361205Z

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Observation a49d8066-d590-491a-a19a-a20f1b93e5b7 · outbound

This paper cites Small language models learn enhanced reasoning skills from medical textbooks,.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Small language models learn enhanced reasoning skills from medical textbooks,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T20:26:39.426905Z

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Observation 5b6bfde8-57b6-4884-84e6-c3ea0af9881b · outbound

This paper cites Are we there yet? a measurement study of efficiency for llm applications on mobile devices,.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Are we there yet? a measurement study of efficiency for llm applications on mobile devices,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T20:26:39.476406Z

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Observation 3e7b9f57-cc0b-4902-8488-fd5e76f108a4 · outbound

This paper cites Edgellm: Fast on-device LLM inference with speculative decoding,.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Edgellm: Fast on-device LLM inference with speculative decoding,

Reference 15

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Source-reported events for the cited work

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Observation 0f817568-d74f-4bb0-aa08-9cb91ef33139 · outbound

This paper cites Edgemoe: Empowering sparse large language models on mobile devices,.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Edgemoe: Empowering sparse large language models on mobile devices,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T20:26:39.584265Z

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Observation 19b2000c-7e0f-4ee6-8ca8-e204bf4b0673 · outbound

This paper cites Qwen2.5 Technical Report.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Qwen2.5 Technical Report

Reference 17

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Observation 183069f3-af57-491e-aec2-3f9fae15c164 · outbound

This paper cites Tiny large language models in embedded NVIDIA portable hardware: Comparative analysis,.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Tiny large language models in embedded NVIDIA portable hardware: Comparative analysis,

Reference 18

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Observation be6270d5-25fa-41a7-87c2-2dbc9e5fc83a · outbound

This paper cites State of the art and future directions of small language models: A systematic review,.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction State of the art and future directions of small language models: A systematic review,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T20:26:39.783626Z

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Observation a6952528-da06-414a-8521-106249c9f517 · outbound

This paper cites An empirical evaluation of prompting strategies for large language models in zero-shot clinical natural language processing,.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction An empirical evaluation of prompting strategies for large language models in zero-shot clinical natural language processing,

Reference 20

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Observation 2016af28-4a8c-4218-911c-807364bb4fab · outbound

This paper cites Pre- train, prompt, and predict: A systematic survey of prompting methods in natural language processing,.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Pre- train, prompt, and predict: A systematic survey of prompting methods in natural language processing,

Reference 21

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Observation 5555565e-0355-4e8a-bdcc-31ff2532908a · outbound

This paper cites Multilingual Prompts in LLM-Based Recommenders: Performance Across Languages.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Multilingual Prompts in LLM-Based Recommenders: Performance Across Languages

Reference 22

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Observation b04c85f1-86be-4f07-949d-7089bb3a9d7d · outbound

This paper cites Simple LLM Prompting is State-of-the-Art for Robust and Multilingual Dialogue Evaluation.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Simple LLM Prompting is State-of-the-Art for Robust and Multilingual Dialogue Evaluation

Reference 23

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Observation 84efc320-845c-4838-98ee-9bbf82b5b8c6 · outbound

This paper cites Synthetic Data Generation Using Large Language Models: Advances in Text and Code,.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Synthetic Data Generation Using Large Language Models: Advances in Text and Code,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-02T20:26:40.146504Z

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Observation a95febf7-cb5f-4ece-abab-2aae9f6c3dbd · outbound

This paper cites Few-shot LLM Synthetic Data with Distribution Matching.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Few-shot LLM Synthetic Data with Distribution Matching

Reference 25

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Source-reported events for the cited work

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Observation 054089da-7f31-4158-8a2b-a51816d6d225 · outbound

This paper cites Exploiting Asymmetry for Synthetic Training Data Generation: SynthIE and the Case of Information Extraction.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Exploiting Asymmetry for Synthetic Training Data Generation: SynthIE and the Case of Information Extraction

Reference 26

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Observation bdba1843-4d47-49b5-9969-99c8af7d3dd3 · outbound

This paper cites Comparison of Prompt Engineering and Fine-Tuning Strategies in Large Language Models in the Classification of Clinical Notes,.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Comparison of Prompt Engineering and Fine-Tuning Strategies in Large Language Models in the Classification of Clinical Notes,

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Observation b9f6bf4f-1793-4d7b-a3ce-dbb06cbadbfa · outbound

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Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset

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Observation a659fb5e-e911-4f3a-ab29-9e12d0ff0099 · outbound

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Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Survey

Reference 29

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Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Data augmentation using llms: Data perspectives, learning paradigms and challenges,

Reference 30

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Observation 6a4bc9e1-b3c1-48e0-a420-d9822aa31d18 · outbound

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Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Fine-tuning BERT for Low-Resource Natural Language Understanding via Active Learning

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Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction RAFT: A Real-World Few-Shot Text Classification Benchmark

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Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Scarecrows in oz: the use of large language models in hri,

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Observation 67877d75-7ecb-4f40-a24b-9f300a320308 · outbound

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Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Gpt-4 as a moral reasoner for robot command rejection,

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Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction A survey on evaluation of large language models,

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Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Making pre-trained language models better few-shot learners,

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Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Llm-based nlg evaluation: Current status and challenges,

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Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Scaling instruction- finetuned language models,

Reference 38

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This paper cites The Ultimate Guide to Fine-Tuning LLMs from Basics to Breakthroughs: An Exhaustive Review of Technologies, Research, Best Practices, Applied Research Challenges and Opportunities.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction The Ultimate Guide to Fine-Tuning LLMs from Basics to Breakthroughs: An Exhaustive Review of Technologies, Research, Best Practices, Applied Research Challenges and Opportunities

Reference 39

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Observation c9334965-8551-404b-9505-e4aadd8d62a6 · outbound

This paper cites Hallucination detection in foundation models for decision-making: A flexible defi- nition and review of the state of the art,.

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction Hallucination detection in foundation models for decision-making: A flexible defi- nition and review of the state of the art,

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Resolution: unresolved; no resolver link, observed 2026-08-02T20:26:41.236405Z

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Pith citing papers

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